DEVELOPMENT OF INFRA-RED

THERMOGRAPHY NDT DETECTION OF

DEFECTS IN CONCRETE AND STEEL

STRUCTURES EXTERNALLY BONDED WITH

CFRP SYSTEMS

By

Jawdat Mustafa Kamal Tashan

B.Sc. Eng. (Hon)

M.Sc. Eng.

A thesis submitted in fulfillment of the requirements for the degree of

Doctor of Philosophy

Faculty of Engineering and Industrial Sciences

Swinburne University of Technology

2012

III

To all people who made life at this stage of civilization, in

the hope that this work will contribute

Summary

V

SUMMARY

Carbon fibre reinforced polymer (CFRP) composites are currently used externally to

retrofit and strengthen concrete and steel structures. One of the most important

requirements of CFRP- strengthened structures is the bond at the interface surface.

Bond defects can have a significant influence on the behaviour of the CFRP composite

structure. Different non-destructive tests were used previously to detect these defects.

This research investigates the ability of infra-red thermography (IRT) non-destructive

techniques (NDT) to detect different defects involving unbond areas, debond areas,

delamination, wet areas and cracks that may occur at the CFRP-substrate bond surface.

The literature review covers the background of the IRT approaches and techniques

employed in different applications. A review of the different CFRP applications and

their related installation methods used currently to retrofit different civil engineering

applications is presented, and summaries and evaluations of current studies that utilize

IRT to detect CFRP-concrete bond defects are outlined.

A total of 32 CFRP strengthened concrete and steel samples were constructed and tested

in this study. Artificial bond defects with different shapes and sizes were implanted

under CFRP composites. The defects involve unbond, delamination and debond areas

created at the bond line. Groove defects were embedded on the concrete surface of

selected specimens to verify the capability of IRT NDT to detect humidity. Cracks of

different sizes were generated at the concrete surfaces of several specimens to

investigate the technique in crack detectability. CFRP fabrics of different types were

used in the strengthening process of concrete and steel specimens. CFRP laminates were

also used in different combinations. Single and multiple-layers in the CFRP system

were adopted in the retrofitting designs.

The experimental work was divided in two major studies: qualitative and quantitative

infra-red thermography assessments. The qualitative tests were conducted with IR

detector type FLIR B200. Passive and active IRT were developed. Lamps of 2000 watts

were used as excitation sources in the active thermography approach. The qualitative

Summary

VI

results showed that the IRT is suitable for the detection of bond defects. The results also

showed that humid areas at the bond interface can be recognized by means of IRT

NDT. Generally, the qualitative thermography test results make this technique a

candidate for rapid detection and especially for bond and debonding defects in the bond

zone in single CFRP systems (fabric or laminate) and the substructure (concrete or

steel). The results indicate that for the purposes of in-depth defect characterization,

qualitative thermography is not recommended.

The second phase of the experimental work focused on the IRT quantitative approach.

A total of 32 specimens were tested during this phase, and different excitation systems

were employed. The quantitative studies were subcategorized into eight parts, and each

part addressed a different task. These tasks involved: emissivity evaluations, the

investigation of different bond defects and crack detection. Moreover, water presence

detectability was examined, and different heating inputs were studied. Precise

measurements of defect sizes and IRT error elimination studies were performed in the

quantitative studies. The overall results show high defect detectability and reasonable

accuracy in defect size identification. The experimental results provide guidelines that

can help thermographers to conduct efficient IRT NDT involving thermal input that can

be used to generate the designed thermal response with minimum thermal detection

during the IRT NDT.

Numerical analyses were then conducted to simulate and gain a better understanding of

the key parameters that have the most influence on the thermal response of a defect

within retrofitted surfaces. First, verification studies of the experimental and numerical

results were performed. There was a very good correlation between the empirical results

and the simulated FE analyses. Two 3D models were built using ANSYS 13 finite

element software analysis. One was for a concrete specimen strengthened externally

with a single fabric sheet which had a bond defect and the other was attached with

double CFRP sheets. Parametric studies involving material thermal properties, material

thickness and thermal input loads were carried out for both models. The results of these

numerical studies can serve as guidelines for thermographers to enable them to design

the thermal load input to achieve desired thermal responses.

Acknowledgments

VII

ACKNOWLEDGMENTS

This work would not have been possible without the help and contributions of others.

First, I would like to express my great appreciation to my main supervisor, Prof. Riadh

Al-Mahaidi for his enthusiasm, patience, encouragement and support throughout my

research. The support and guidance of my co-supervisor, Prof. John Wilson, is also

greatly appreciated. Their continuous inspiration, guidance and advice on my research

have been invaluable.

I would like to express my sincere gratitude to Monash University staff members Mr.

Long Goh, Mr. Jeffrey Doddrell, Mr. Alan Taylor and Ms. Jenny Manson for their help

and willing assistance with the laboratory phase of this study. Dr. Alex McKnight

assisted by proofreading the final version of the thesis.

I would also like to thank my colleague, Mr. Asghar Habibnejad for his tremendous

support in the experimental program.

I am indebted to my wife Ava Sidiq Mamkak for her patience, sacrifice, support and

understanding.

I would like to thank my mother, Mrs. Najla Albaiaty, Mr. Ali Tashan, Mr. Tariq

Tashan, Mr. Muard Tashan, and Ms. Gihan Tashan for their constant encouragement

and love throughout the course of my life.

Declaration

IX

DECLARATION

The candidate herein declares that the research work presented in this thesis contains no

material which has been accepted for the award of any other degree or diploma in any

university or other institutions. I affirm that to the best of my knowledge, the thesis

contains no material previously published or written by another person, except where

due reference is made in the text in the thesis.

Jawdat Tashan

Table of contents

XI

TABLE OF CONTENTS

SUMMARY ............................................................................................................................................... V

ACKNOWLEDGMENTS ..................................................................................................................... VII

DECLARATION ...................................................................................................................................... IX

TABLE OF CONTENTS ......................................................................................................................... XI

LIST OF FIGURES ............................................................................................................................ XVII

LIST OF TABLES ............................................................................................................................. XXIX

LIST OF NOTATIONS ..................................................................................................................... XXXI

1 CHAPTER ONE: INTRODUCTION ............................................................................................. 1

1.1 BACKGROUND ................................................................................................................................ 1

1.2 RESEARCH OBJECTIVES ................................................................................................................... 3

1.3 RESEARCH PHASES.......................................................................................................................... 4

1.4 THESIS OUTLINE ............................................................................................................................. 4

2 CHAPTER TWO: LITERATURE REVIEW ................................................................................ 7

2.1 INTRODUCTION ............................................................................................................................... 7

2.2 INFRA-RED THERMOGRAPHY........................................................................................................... 7

2.2.1 Background .......................................................................................................................... 7

2.2.2 Fundamentals of infra-red radiation .................................................................................... 9

2.2.3 Fundamentals of IRT NDT ................................................................................................. 11

2.2.4 Theoretical principles ......................................................................................................... 11

2.2.4.1 Planck’s law .................................................................................................................................. 11

2.2.4.2 Emissivity ..................................................................................................................................... 14

2.2.5 Infra-red thermography techniques .................................................................................... 17

2.2.6 Passive techniques .............................................................................................................. 17

2.2.7 Active technique ................................................................................................................. 28

2.2.7.1 Pulsed thermography technique (PTT) .......................................................................................... 29

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XII

2.2.7.2 Step heating thermography ........................................................................................................... 32

2.2.7.3 Lockin thermography technique (LTT) ......................................................................................... 32

2.2.8 Noise in IRT ........................................................................................................................ 35

2.2.9 Errors in IRT ....................................................................................................................... 37

2.2.10 Qualitative and quantitative thermography ................................................................... 41

2.3 FRP SYSTEM AND MATERIALS ....................................................................................................... 41

2.3.1 Background ......................................................................................................................... 41

2.3.2 Fibre types .......................................................................................................................... 43

2.3.3 Types of polymer resin matrices ......................................................................................... 45

2.3.4 CFRP systems for retrofitting civil engineering applications ............................................. 45

2.3.4.1 Installation .................................................................................................................................... 45

2.3.4.2 CFRP applications ........................................................................................................................ 47

2.4 LITERATURE REVIEW OF INSPECTION OF FRP BOND DEFECTS BY IRT ........................................... 48

2.5 SUMMARY ..................................................................................................................................... 61

3 CHAPTER THREE: QUALITATIVE INFRA-RED THERMOGRAPHY EXPERIMENTAL

LABORATORY PROGRAM .................................................................................................................. 63

3.1 INTRODUCTION.............................................................................................................................. 63

3.2 DESIGN OF SPECIMENS .................................................................................................................. 63

3.2.1 Concrete specimens ............................................................................................................ 64

3.2.2 Steel specimens ................................................................................................................... 66

3.2.3 CFRP fabric ........................................................................................................................ 67

3.2.3.1 Wet lay-up process ........................................................................................................................ 68

3.2.4 CFRP laminate ................................................................................................................... 70

3.2.4.1 Carbon fibre laminate installation ................................................................................................. 72

3.2.5 Defects in CFRP systems bonded to concrete and steel structures ..................................... 73

3.2.6 Specimen-CFRP designs ..................................................................................................... 74

3.2.7 Identification of artificial defects ........................................................................................ 82

3.3 QUALITATIVE INFRA-RED THERMOGRAPHY SET-UP ....................................................................... 85

3.3.1 Infra-red detector for qualitative tests ................................................................................ 85

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XIII

3.4 QUALITATIVE IRT NDT ............................................................................................................... 86

3.4.1 Passive qualitative IRT ....................................................................................................... 86

3.4.2 Active qualitative IRT ......................................................................................................... 88

3.5 SUMMARY AND FINDINGS ............................................................................................................. 97

4 CHAPTER FOUR: QUANTITATIVE INFRA-RED THERMOGRAPHY EXPERIMENTAL

LABORATORY PROGRAM ................................................................................................................. 99

4.1 INTRODUCTION ............................................................................................................................. 99

4.2 DESIGN OF EXPERIMENTAL LABORATORY PROGRAM .................................................................... 99

4.3 QUANTITATIVE INFRA-RED THERMOGRAPHY SET-UP .................................................................. 100

4.3.1 Infra-red detector and data analysis process ................................................................... 100

4.3.2 Excitation systems ............................................................................................................ 102

4.3.2.1 Heating lamps ............................................................................................................................. 103

4.3.2.2 Air blower ................................................................................................................................... 104

4.3.3 Heat flux sensors .............................................................................................................. 104

4.3.4 Test configuration............................................................................................................. 106

4.3.5 Heating schemes ............................................................................................................... 109

4.3.5.1 Pulse scheme ............................................................................................................................... 109

4.3.5.2 Sinusoidal scheme ....................................................................................................................... 113

4.3.5.3 Long-pulse heating scheme ......................................................................................................... 114

4.4 CHARACTERIZATION OF INFRA-RED DETECTABILITY .................................................................. 115

4.5 QUANTITATIVE IRT STUDIES ...................................................................................................... 118

4.5.1 Part 1: Emissivity value validation of the FRP using IRT ................................................ 123

4.5.1.1 Test set-up ................................................................................................................................... 124

4.5.1.2 Emissivity values ........................................................................................................................ 125

4.5.1.3 Summary ..................................................................................................................................... 126

4.5.2 Part 2: Using PTT to detect different bond defects .......................................................... 127

4.5.2.1 Unbond defect detection ............................................................................................................. 127

4.5.2.2 Debonding and delamination detectability .................................................................................. 152

4.5.2.3 Far distance IR detection ............................................................................................................. 168

4.5.2.4 Transmission observation IRT .................................................................................................... 172

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XIV

4.5.2.5 Summary of Part 2 experimental program .................................................................................. 174

4.5.3 Part 3: Defect size measurement ...................................................................................... 176

4.5.3.1 Summary of Part 3 experimental program .................................................................................. 187

4.5.4 Part 4: Excitation system design ....................................................................................... 188

4.5.4.1 Lamps heating modes ................................................................................................................. 188

4.5.4.2 Air blower excitation system ...................................................................................................... 194

4.5.4.3 Summary of Part 4 experimental program .................................................................................. 204

4.5.5 Part 5: Infra-red errors and noise .................................................................................... 205

4.5.5.1 Errors in IRT ............................................................................................................................... 205

4.5.5.2 Noise in the IRT .......................................................................................................................... 216

4.5.6 Part 6: IR detection of the presence of water.................................................................... 221

4.5.6.1 Summary of Part 5 ...................................................................................................................... 228

4.5.7 Part 7: Long-Pulsed IRT and Lockin thermography approaches ..................................... 229

4.5.7.1 Long-Pulsed heating scheme ...................................................................................................... 229

4.5.7.2 Lockin thermography approach .................................................................................................. 234

4.5.7.3 Summary and findings ................................................................................................................ 238

4.5.8 Part 8: Detection of cracks ............................................................................................... 239

4.5.8.1 Summary and findings ................................................................................................................ 253

4.6 GUIDELINES FOR QUANTITATIVE IRT NDT ................................................................................. 254

5 CHAPTER FIVE: NUMERICAL ANALYSIS .......................................................................... 259

5.1 INTRODUCTION............................................................................................................................ 259

5.2 FEM STUDIES OF BOND DEFECTS IN SINGLE CFRP FABRIC .......................................................... 259

5.2.1 Modeling ........................................................................................................................... 259

5.2.1.1 Geometry .................................................................................................................................... 259

5.2.1.2 Meshing ...................................................................................................................................... 260

5.2.1.3 Thermal boundary conditions ..................................................................................................... 262

5.2.1.4 Thermal results ........................................................................................................................... 263

5.2.2 Parametric Study 1: Verification of analytical simulations .............................................. 264

5.2.3 Parametric Study 2: Influence of materials thermal properties on defect detection ......... 268

5.2.3.1 Influence of CFRP material thermal properties ........................................................................... 269

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XV

5.2.3.2 Influence of epoxy resin material thermal properties .................................................................. 274

5.2.3.3 Influence of concrete substrate material thermal properties ........................................................ 278

5.2.3.4 Summary of Parametric Study 2 ................................................................................................. 281

5.2.4 Parametric Study 3: Thickness of materials ..................................................................... 283

5.2.4.1 CFRP layer thickness .................................................................................................................. 283

5.2.4.2 Epoxy layer thickness ................................................................................................................. 286

5.2.4.3 Concrete layer thickness ............................................................................................................. 288

5.2.4.4 Summary and finding of Parametric Study 3 .............................................................................. 289

5.2.5 Parametric Study 4: Thermal loads and periods .............................................................. 290

5.2.5.1 Summary of Parametric Study 4 ................................................................................................. 295

5.3 FINITE ELEMENT STUDIES OF BONDING DEFECTS UNDER DOUBLE CFRP FABRIC LAYERS ........... 296

5.3.1 Modeling........................................................................................................................... 296

5.3.1.1 Geometry .................................................................................................................................... 296

5.3.1.2 Meshing ...................................................................................................................................... 297

5.3.1.3 Thermal boundary conditions, loading and results ...................................................................... 298

5.3.2 Parametric Study 5: Verification of analytical simulations ............................................. 299

5.3.3 Parametric Study 6: Influence of materials thermal properties on defect detection ........ 300

5.3.3.1 Influence of CFRP material thermal properties ........................................................................... 300

5.3.3.2 Influence of epoxy resin material thermal properties .................................................................. 304

5.3.3.3 Influence of concrete substrate material thermal properties ........................................................ 306

5.3.4 Parametric Study 7: Thickness of materials ..................................................................... 307

5.3.4.1 CFRP layer thickness .................................................................................................................. 307

5.3.4.2 Epoxy layer thickness ................................................................................................................. 309

5.3.4.3 Concrete layer thickness ............................................................................................................. 310

5.3.5 Parametric Study 8: Thermal loads and periods .............................................................. 311

5.3.6 Summary and findings ...................................................................................................... 313

6 CHAPTER SIX: CONCLUSIONS AND RECOMMENDATIONS ........................................ 317

6.1 INTRODUCTION ........................................................................................................................... 317

6.2 CONCLUSIONS ............................................................................................................................ 318

6.2.1 Experimental studies ........................................................................................................ 318

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XVI

6.2.2 Numerical studies ............................................................................................................. 320

6.3 RECOMMENDATIONS FOR FUTURE WORK .................................................................................... 322

REFERENCES ....................................................................................................................................... 323

APPENDIX A .......................................................................................................................................... 333

APPENDIX B .......................................................................................................................................... 337

LIST OF PUBLICATIONS ................................................................................................................... 343

List of figures

XVII

LIST OF FIGURES

Figure 2.1 Infra-red wavelength ranges .......................................................................... 10

Figure 2.2 Spectral blackbody emissive power (ASM 1992) ......................................... 13

Figure 2.3 Emissivity effect on radiation from surface of emissivity ε with hypothetical

intensity (Maldague and Moore 2001) ............................................................................ 15

Figure 2.4 Specular and diffuse radiation reflection [Reproduced from Lienhard (1981)]

......................................................................................................................................... 15

Figure 2.5 M51 imaged with the Spitzer Space Telescope and an image of the same

galaxy taken by the Herschel Space Observatory (European Space Agency 2011b) ..... 18

Figure 2.6 Thermogram of railway weld (Khauv 2011) ................................................. 19

Figure 2.7 Microchip connection checking using IRT (Khauv 2011) ............................ 19

Figure 2.8 IR image of the Sacred Heart building in Paris ............................................. 20

Figure 2.9 IR diagnosis of water leaks in ceiling (Chicago Infrared Thermal Imaging

Inc. 2011) ........................................................................................................................ 21

Figure 2.10 Gas leak thermography test from a pipe buried at 80 cm depth (Ljungberg

and Jonsson 2002b) ......................................................................................................... 21

Figure 2.11 Infra-red sensor for control of the leaf temperature, Thermograms indicate

deficiencies in the gas-IR heating system (Ljungberg and Jonsson 2002a).................... 22

Figure 2.12 Health problems diagnosed by IR thermal imaging, (a) Diagnosis of jaw

problem (Meditherm Inc. 2011a) ; (b) Football player with stress fracture (Meditherm

Inc. 2011b) ; and (c) Breast thermography diagnosis (Meditherm Inc. 2011c) ............. 23

Figure 2.13 The Virgin of the Rocks under-drawing infrared image ............................. 24

Figure 2.14 Australian region infrared satellite image (Australian Bureau of

Meteorology 2011) .......................................................................................................... 25

Figure 2.15 Hurricane Irene arrives in NYC (The City of New York 2011) .................. 25

Figure 2.16 Infra-red biological application: Brazilian free-tailed bat (Center for

Ecology and Conservation Biology-Boston University 2011) ....................................... 26

List of figures

XVIII

Figure 2.17 Aerial fire IR mapping (Khauv 2011) ......................................................... 26

Figure 2.18 Load traffic IR monitoring (Khauv 2011) ................................................... 26

Figure 2.19 US Navy IR imagery taken from a U.S. NavyP-3C Orion maritime patrol

aircraft, assisting in search and rescue operations for survivors of the Egyptian ferry Al

Salam Boccaccio 98 in the Red Sea (U.S. Navy 2006) .................................................. 27

Figure 2.20 High speed IR detector image for machine gun testing (Khauv 2011) ....... 27

Figure 2.21 Hot spot localization .................................................................................... 28

Figure 2.22 IR pulsed thermography test configurations, (a) line method, (b) point

method and (c) surface method ....................................................................................... 30

Figure 2.23 Schematic of (a) Reflection observation method (One-sided); (b)

Transmission observation method (Two-sided); (c) Reflection observation and hot spot

image; (d) Transmission observation and cold spot image ............................................. 31

Figure 2.24 Pulsed heat and IR recorded waves in pulsed thermography approach ...... 31

Figure 2.25 Sinusoidal input wave and IR recorded wave in LTT approach ................. 33

Figure 2.26 Basic locking thermography set-up, laser beam and lamp (Gerhard and

Busse 2006) ..................................................................................................................... 33

Figure 2.27 LTT set-up with ultrasonically modulated internal simulation ................... 34

Figure 2.28 Two means of generation of thermal waves in LTT ................................... 35

Figure 2.29 Background reflection [Reproduced from Childs (2001)] .......................... 38

Figure 2.30 Shielding the test to minimize the significant background reflection

[Reproduce from Childs (2001)] ..................................................................................... 38

Figure 2.31 The main gases responsible for infra-red radiation absorption. Atmospheric

transmittance (Maldague and Moore 2001) .................................................................... 39

Figure 2.32 IR windows in the spectrum ........................................................................ 40

Figure 2.33 Representation of CFRP materials [ Reproduced from Nanni (2004)] ....... 43

Figure 2.34 Scanning Electron Microscope (SEM) image of CFRP fabric .................... 43

Figure 2.35 The main FRP installation systems for rehabilitated structural members ... 46

List of figures

XIX

Figure 2.36 AASHTO Type II girder and load test set-up (Brown, J. R. and Hamilton,

H. R. 2004) ...................................................................................................................... 54

Figure 2.37 Test set-ups for long-pulse and modulated (lockin) heating (Brown, Jeff R.

and Hamilton, H. R. 2004) .............................................................................................. 58

Figure 3.1 Moulding the concrete ................................................................................... 64

Figure 3.2 Concrete specimen surfaces prepared by: (a) water blasting, (b) surface water

blasting, (c) sand blasting, (d) rough surface .................................................................. 65

Figure 3.3 Three-point load testing of cracked specimen ............................................... 66

Figure 3.4 Steel specimen prepared surface .................................................................... 67

Figure 3.5 Schematic of CFRP fabric waves, (a) Uni-directional wave, and (b) Bi-

directional ± 45 degree waves (Hearle 2001) ................................................................. 67

Figure 3.6 Schematic representation of a hand lay-up process ....................................... 70

Figure 3.7 MBrace wet lay-up of CFRP fabric (BASF 2011a)...................................... 70

Figure 3.8 MBrace laminate (BASF 2011b) ................................................................... 71

Figure 3.9 MBrace wet lay-up of CFRP laminate (BASF 2011b) .................................. 73

Figure 3.10 Potential bond defects in CFRP-concrete structure ..................................... 74

Figure 3.11 Specimen details .......................................................................................... 81

Figure 3.12 Specimen 3 artificial debond ....................................................................... 81

Figure 3.13 Groove in concrete of Specimen 4............................................................... 81

Figure 3.14 Specimen 5 CFRP laminates ....................................................................... 82

Figure 3.15 Specimen 11 loading-generated cracks ....................................................... 82

Figure 3.16 FLIR B200 camera with IRT testing set-up ................................................ 86

Figure 3.17 Specimen 1 thermogram- passive qualitative thermography...................... 87

Figure 3.18 Specimen 5 IR capture ................................................................................. 88

Figure 3.19 Active qualitative thermography excitation system ................................... 88

Figure 3.20 Specimen 1 thermogram- active qualitative thermography ........................ 89

List of figures

XX

Figure 3.21 Thermogram of Specimen 6 ........................................................................ 90

Figure 3.22 Thermogram of Specimen 7 ........................................................................ 90

Figure 3.23 Thermogram of Specimen 8 ........................................................................ 90

Figure 3.24 Thermogram of Specimen 13 ...................................................................... 91

Figure 3.25 Thermogram of Specimen 9 ........................................................................ 91

Figure 3.26 Specimen 5 IR image ................................................................................... 92

Figure 3.27 Delamination in Specimen 3 ........................................................................ 92

Figure 3.28 Specimen 4 IR record .................................................................................. 93

Figure 3.29 IR thermogram of Specimen 17 ................................................................... 93

Figure 3.30 Water injection in DB031 defect ................................................................. 94

Figure 3.31 Specimen 4 water investigation ................................................................... 94

Figure 3.32 GR053 IR image – water presence examination ......................................... 94

Figure 3.33 Thermogram of CR181 and CR182 artificial cracks ................................... 95

Figure 3.34 Embedded artificial cracks in Specimen 10 ................................................ 95

Figure 3.35 Specimen S1 IR capture .............................................................................. 96

Figure 3.36 IR record of Specimen S2 ............................................................................ 96

Figure 3.37 UBS41 defect in Specimen S4 thermogram ................................................ 97

Figure 4.1 (a) Thermo Tracer TH9260 thermal camera (b) Thermo Tracer TH9260 field

of view (NEC 2011) ...................................................................................................... 101

Figure 4.2 Halogen heating lamps (IANIRO 2011) ...................................................... 103

Figure 4.3 Variable auto-transformer (Variac) ............................................................. 104

Figure 4.4 PU-T thermal sensor series details (1) Sensitive area, (2) Guard, (3) Fixed

wire, (4) Minimum bending radius, and (5) Optional temperature sensor (Hukse Flux

2011) ............................................................................................................................. 106

Figure 4.5 Infra-red test configuration, (a) Rigid frame with insulated sliding shutters,

(b) Specimen holder details ........................................................................................... 107

List of figures

XXI

Figure 4.6 Schematic views of: (a) turned-on lamps, (b) turned-off lamps, and (c) dark

curtain tent covering the test site ................................................................................... 109

Figure 4.7 Pulses in PTT versus time at different distances and durations (Specimen 24)

....................................................................................................................................... 111

Figure 4.8 Pulse heating scheme ................................................................................... 113

Figure 4.9 Two cycles of input heat flux during the LTT testing of Specimen S1 ....... 114

Figure 4.10 Sinusoidal heating scheme ......................................................................... 114

Figure 4.11 Long-pulsed heating scheme ..................................................................... 115

Figure 4.12 Recognition of defect and defect- free ROIs ............................................. 117

Figure 4.13 Pixel line profile ........................................................................................ 117

Figure 4.14 Thermal signal patterns with time ............................................................. 118

Figure 4.15 Concrete-CFRP specimen inside oven ...................................................... 124

Figure 4.16 Thermogram of Specimen 2 shows the modified surface for emissivity test

....................................................................................................................................... 125

Figure 4.17 Defects in Specimen 1 ............................................................................... 128

Figure 4.18 Defect UB011 thermal responses at different ROI sizes ........................... 130

Figure 4.19 Defect UB011 thermal responses at different pulse intervals ................... 131

Figure 4.20 Heat flux versus maximum thermal signal in Specimen 1 for different pulse

intervals ......................................................................................................................... 131

Figure 4.21 Defects in Specimen 24 thermogram ........................................................ 132

Figure 4.22 Infra-red signals of Specimen 24 defects................................................... 134

Figure 4.23 Heat flux versus maximum thermal signal in Specimen 24 for different

pulse intervals................................................................................................................ 136

Figure 4.24 Thermal signals of defects in Specimen 6: (a) UB063, (b) UB064 ........... 137

Figure 4.25 Thermal contrast of Specimen 6 with 5 s pulse: (a) excitation at 50 cm, (b)

excitation at 120 cm ...................................................................................................... 138

List of figures

XXII

Figure 4.26 Contrast of UB063 with 5 s pulses at different distances .......................... 139

Figure 4.27 Contrast of UB063 with 1 m distance at different pulses .......................... 140

Figure 4.28 Specimen 5 unbonding artificial defects ................................................... 140

Figure 4.29 Thermal signal of Specimen 5 at 5 s pulse interval: (a) defect under a single

CFRP laminate, (b) defect under double CFRP laminates ............................................ 142

Figure 4.30 Specimen 5 unbonded areas maximum thermal signals recorded at different

distances ........................................................................................................................ 143

Figure 4.31 UB052 signals at 1 and 1.2 m with different pulses .................................. 144

Figure 4.32 Line ROI of Specimen 9 ............................................................................ 145

Figure 4.33 Line temperature profile of Specimen 9 .................................................... 146

Figure 4.34 Specimen 9 defect signals .......................................................................... 147

Figure 4.35 Specimen 16 thermal signals ..................................................................... 148

Figure 4.36 Specimen 16 thermal contrasts at 5 s pulse ............................................... 148

Figure 4.37 Specimen 16 thermal contrasts at 1 s pulse ............................................... 149

Figure 4.38 Defects: UB011 and UBS11 signals .......................................................... 150

Figure 4.39 Defects: UB051 and UBS41 signals .......................................................... 152

Figure 4.40 Thermogram of Specimen 3 ...................................................................... 153

Figure 4.41 Specimen 3 debonding area signals: (a) Pulse is 5 s, (b) pulse is 3 s, (c)

pulse is 1 s ..................................................................................................................... 154

Figure 4.42 Three dimensional profile of DB031: (a) before applying Gaussian filter, (b)

after applying 5 ×5 Gaussian filter ................................................................................ 156

Figure 4.43 Specimens 3 and 26 debonding responses ................................................. 157

Figure 4.44 Debond DB261 signals .............................................................................. 157

Figure 4.45 Contrast of DB261: (a) at 5 s pulse, (b) at1 s pulse ................................... 158

Figure 4.46 Steel Specimen 2 thermal signals .............................................................. 159

Figure 4.47 Comparison of Specimens’ 3 and S2 debonding signals ........................... 160

List of figures

XXIII

Figure 4.48 Thermal contrast for Specimen S2 ............................................................ 161

Figure 4.49 Defect DB131 (a) thermal signals at different pulse and distances, (b) heat

flux versus maximum thermal signal for DB131 at different pulse intervals ............... 162

Figure 4.50 Defect DL162: (a) location of DL162, (b) thermal signals, (c) contrast at 5

s, (d) contrast at 1 s ....................................................................................................... 167

Figure 4.51 Thermal image of Specimen 1 ................................................................... 169

Figure 4.52 Thermal responses of Defect UB011 ......................................................... 171

Figure 4.53 UB011 signals captured from different distances ...................................... 171

Figure 4.54 UBS41 transmission observation method thermal responses .................... 173

Figure 4.55 Defect sizes measurement in Specimen 1 .................................................. 177

Figure 4.56 Boundary outline method for defect area measurement- Specimen 3 ....... 178

Figure 4.57 Measuring defects in Specimen 1 in mm ................................................... 179

Figure 4.58 defect size of UB021 in mm ...................................................................... 180

Figure 4.59 Specimen 8 defect sizes in mm .................................................................. 181

Figure 4.60 Specimen 7 defect measurements in mm................................................... 181

Figure 4.61 Steel Specimen S1surface temperature profiles at different times ........... 183

Figure 4.62 Specimen 5 thermogram measurements in mm ......................................... 184

Figure 4.63 Specimen 9 defect size in mm ................................................................... 185

Figure 4.64 Specimen 16 defects measurement ............................................................ 186

Figure 4.65 Groove size detection in GR171: (a) the actual size of the groove under the

CFRP laminate, (b) the measured detected defect, (c) groove end details at the concrete

surface ........................................................................................................................... 186

Figure 4.66 Thermograms of Specimen 5 (a) before the test, (b) during the heat pulse,

and (c) 1s after the heat pulse ........................................................................................ 189

Figure 4.67 Specimen 24 after 1 s of pulse (a) using the spot light mode, (b) using the

flood light mode ............................................................................................................ 190

List of figures

XXIV

Figure 4.68 Thermal responses of UB021 in spot- and flood-lighting modes .............. 191

Figure 4.69 Specimen 3 during pulse time (a) using the spot-light mode, (b) using the

flood-light mode ............................................................................................................ 192

Figure 4.70 Thermal results of DB031 with different light modes (a) thermal signals, (b)

contrast at 5 s, (c) contrast at 1 s ................................................................................... 194

Figure 4.71 UB011 thermal response by using air blower excitation system for 10 s (a)

thermal signal, (b) thermal contrast .............................................................................. 196

Figure 4.72 Specimen 3 with air excitation (a) IR image, (b) thermal signal, (c) thermal

contrast .......................................................................................................................... 198

Figure 4.73 Thermal results of UB052 using air excitation of 20 s .............................. 199

Figure 4.74 Specimen 8 thermal responses via air blower excitation system ............... 201

Figure 4.75 Thermal responses in concrete and steel- CFRP systems .......................... 203

Figure 4.76 Views of the covered site location ............................................................. 208

Figure 4.77 Thermogram of the uncovered site with no shutter in use ........................ 209

Figure 4.78 Thermal signals of defect UB021 .............................................................. 211

Figure 4.79 Error in thermal signals of Specimen 5 defects ......................................... 213

Figure 4.80 Specimen 3 defect signals .......................................................................... 214

Figure 4.81 Specimen S3 defect signals ....................................................................... 215

Figure 4.82 DBS31 errors in signal of 5 s pulse length ................................................ 216

Figure 4.83 Noise evaluation of Specimen 5 ................................................................ 218

Figure 4.84 Specimen 26 IR images and 3D profile processing with different filters . 220

Figure 4.85 Water investigation in Specimen 4 ............................................................ 222

Figure 4.86 DB031 signal with water presence ............................................................ 223

Figure 4.87 Water escaping from the defect ................................................................. 224

Figure 4.88 Water injection process of GR171 before the pulse injection ................... 226

Figure 4.89 Specimen 17 IR results .............................................................................. 227

List of figures

XXV

Figure 4.90 Defect GR171 thermal result ..................................................................... 228

Figure 4.91 UB011 thermal signals .............................................................................. 230

Figure 4.92 Defects UB063 and UB064 thermal signals at 5 s and 10 s ...................... 231

Figure 4.93 Defects UB051 and UB052 thermal signals at 5 s and 10 s ...................... 232

Figure 4.94 Defect DB031 thermal signals at 5 s and 10 s ........................................... 233

Figure 4.95 Defect UBS11 thermal signals at 5 s and 10 s ........................................... 234

Figure 4.96 Specimen 1 thermal signals by applying LTT ........................................... 236

Figure 4.97 Defect UBS11 thermal signals by applying LTT ...................................... 236

Figure 4.98 Defect DB031 thermal signals by applying LTT ...................................... 237

Figure 4.99 Specimen S2 debonding defect thermal signals by applying LTT ............ 238

Figure 4.100 Schematic of IRT for crack detection ...................................................... 240

Figure 4.101 Artificial crack generation ....................................................................... 241

Figure 4.102 Cracks CR101 and CR102 profile trends ................................................ 243

Figure 4.103 Cracks CR103 and CR104 profile trends ................................................ 244

Figure 4.104 Cracks in Specimen 15 ............................................................................ 246

Figure 4.105 Specimen 25 IR image ............................................................................. 246

Figure 4.106 ROI thermal data in CR121 crack ........................................................... 249

Figure 4.107 ROI thermal data of Specimen 14 ........................................................... 250

Figure 4.108 IRT configuration to improve crack detection ........................................ 251

Figure 4.109 Specimen 11 thermal results .................................................................... 252

Figure 4.110 Crack measurement from thermograms................................................... 253

Figure 5.1 Mesh of Specimen 2 .................................................................................... 261

Figure 5.2 CFRP and epoxy layers mesh details .......................................................... 261

Figure 5.3 Faced meshing of Specimen 2 ..................................................................... 262

Figure 5.4 Model of Specimen 2 simulation ................................................................. 263

List of figures

XXVI

Figure 5.5 Coordination points system ......................................................................... 264

Figure 5.6 Comparison of experimental and simulated thermal signals at run 3 .......... 267

Figure 5.7 Three pulses durations of runs 1 to 3 ........................................................... 268

Figure 5.8 Maximum thermal signal versus different specific heat of CFRP fabric .... 272

Figure 5.9 Pulses of 5 s for different CFRP specific heat factors (a) Thermal signals

versus time; (b) Time of maximum thermal signals ..................................................... 272

Figure 5.10 Time for maximum thermal signal of different epoxy conductivities ....... 278

Figure 5.11 Pulse of 5 s for different concrete specific heat factors: Time of maximum

thermal signals .............................................................................................................. 280

Figure 5.12 Maximum thermal signal versus CFRP thickness ..................................... 285

Figure 5.13 Pulses of 5 s for different CFRP thicknesses (a) Thermal signals versus

time; (b) Time of maximum thermal signals ................................................................ 286

Figure 5.14 Maximum thermal signal versus epoxy thicknesses.................................. 288

Figure 5.15 Thermal signal versus input heat flux for different pulses ........................ 293

Figure 5.16 Thermal signals versus time at different input thermal loading ................ 295

Figure 5.17 Model for bond defect with double CFRP fabric simulation .................... 297

Figure 5.18 Meshing details of double CFRP layers model ......................................... 298

Figure 5.19 UB064 defect experimental versus simulation data .................................. 300

Figure 5.20 Thermal results versus different specific heats of defect under double CFRP

fabrics ............................................................................................................................ 302

Figure 5.21 (a) Maximum thermal signals versus different specific heats of epoxy, (b)

Changing rates for both single and double layers of CFRP .......................................... 305

Figure 5.22 Double CFRP layers simulation (a) Maximum thermal signal versus CFRP

thicknesses; (b) Thermal signals versus time; (c) Time of maximum thermal signals . 309

Figure 5.23 Maximum thermal signal versus epoxy thickness ..................................... 310

List of figures

XXVII

Figure 5.24 (a) Thermal signal versus input heat flux; (b) Thermal signal versus time of

different input heat flux ................................................................................................. 313

List of tables

XXIX

LIST OF TABLES

Table 2.1 Typical properties of fibres (CEB-FIP Bulletin 14 2001)............................... 44

Table 2.2 Typical mechanical properties of FRP composites (CEB-FIP Bulletin 14

2001) ............................................................................................................................... 44

Table 2.3 Summary of parameters studied in FRP-strengthened structures by IRT ....... 48

Table 3.1 Proportions of the concrete mix design .......................................................... 64

Table 3.2 CFRP fabric properties (BASF 2011a), (Varat 2011), (Fyfe-Co. LLC 2011) 68

Table 3.3 Epoxy manufacturers; material properties (BASF 2012a), (Huntsman

Advanced Materials 2011) .............................................................................................. 69

Table 3.4 CFRP laminate properties (BASF 2011b) ...................................................... 71

Table 3.5 Concrete - CFRP laminate adhesive properties .............................................. 72

Table 3.6 Identification of artificial defects .................................................................... 84

Table 4.1 Thermal sensors details (Hukse Flux 2011) .................................................. 105

Table 4.2 Heating designs (Specimen 24)..................................................................... 112

Table 4.3 Quantitative IRT tests ................................................................................... 122

Table 4.4 Specimens CFRP designs.............................................................................. 123

Table 4.5 Emissivity values of IRT tests ...................................................................... 126

Table 4.6 Debonding defects summary ......................................................................... 164

Table 4.7 Summary of maximum thermal signals for delamination defects ................ 168

Table 4.8 LTT frequencies applied ............................................................................... 235

Table 4.9 IR recommended thermal inputs for different CFRP composites ................. 256

Table 5.1 Materials properties (MBrace 2011; MBrace 2012) ..................................... 260

Table 5.2 Average of input heat flux waves for different pulse lengths in experimental

program ......................................................................................................................... 265

Table 5.3 Simulations thermal results ........................................................................... 267

List of tables

XXX

Table 5.4 CFRP specific heat simulations 4 to 36 ........................................................ 270

Table 5.5 CFRP conductivity simulations 37 to 69 ...................................................... 273

Table 5.6 Epoxy specific heat simulations 70 to 90 ..................................................... 275

Table 5.7 Epoxy conductivity simulations 91 to 108 .................................................... 277

Table 5.8 Concrete specific heat simulations 109 to 130 ............................................. 279

Table 5.9 Concrete conductivity simulations 131 to 148.............................................. 281

Table 5.10 CFRP thickness simulations 149 to 175 ..................................................... 284

Table 5.11 Epoxy thickness simulations 176 to 196 ..................................................... 287

Table 5.12 Concrete thickness simulations 197 to 214 ................................................. 289

Table 5.13 Thermal load studies 215 to 259 ................................................................. 292

Table 5.14 Double CFRP sheets specific heat simulations 261 through 271 ............... 301

Table 5.15 Double CFRP conductivity simulations 272 to 282 ................................... 303

Table 5.16 Epoxy specific heat simulations 283 to 289 ............................................... 304

Table 5.17 Epoxy conductivity simulations 290 to 295................................................ 306

Table 5.18 Concrete specific heat simulations 296 to 302 ........................................... 306

Table 5.19 Concrete conductivity simulations 303 to 308............................................ 307

Table 5.20 Double CFRP thickness simulations 309 to 315......................................... 308

Table 5.21 Epoxy thickness simulations 316 to 322 ..................................................... 310

Table 5.22 Concrete thickness simulations 323 to 326 ................................................. 311

Table 5.23 Thermal load simulations 327 to 341.......................................................... 312

List of notations

XXXI

LIST OF NOTATIONS

C = Thermal contrast

C (t) = Thermal contrast at specific time

Cmax = maximum thermal contrast

Ctmax = time that meet the peak of the thermal contrast

co = speed of light in vacuum

E = total emissive power

Eλ = spectral emissive power

Eλb = spectral emissive power for a blackbody

h = Planck’s constant

i , j = the x and y positions in an image of N ×M pixels

k = Boltzmann’s constant

n = constant refractive index

q = the input heat flux in watts per metre square

T = absolute temperature

T (t)defect = surface temperature above the subsurface defect at specific time

T (t)background = surface temperature in the surroundings defects-free area at specific time

t = time in seconds

Tambient = the ambient temperature

Tg = epoxy glass transition temperature

tmax = time for the maximum thermal signal

tmin = time for the minimum thermal signal

ΔT = thermal signal

ΔT (t) = thermal signal at specific time

ΔTmax = maximum thermal signal

ΔTmin = minimum thermal signal

ε = total emissivity

ε (T,λ) = spectral emissivity

λ = wavelength

µ = the mean of the noise distribution.

List of notations

XXXII

σ = Stefan-Boltzmann constant

Introduction

1

1 CHAPTER ONE: INTRODUCTION

1.1 Background

The use of carbon fibre reinforced polymer (CFRP) composites is expanding widely in

the strengthening of concrete and steel structures in civil engineering applications.

CFRP retrofit systems are two-phase materials that consist of micro-scale carbon fibres

saturated in a polymer matrix. The retrofitting can be applied with different types of

CFRP. Most CFRP products are applied to external surfaces of the structure to offer

additional strengthening. CFRP bars are also widely employed in structural concrete

members. This CFRP product can be used by grouting the bars with epoxy to provide

the required bonding forces within the existing structure.

The advanced properties of CFRP materials, involving their high strength, high

durability, high resistance to deterioration and light weight, have encouraged engineers

and manufacturers to employ these products in different industries, including aerospace

engineering and marine applications. CFRP systems have begun recently in civil

engineering structures to take the place of traditional methods of strengthening

structures like attaching external steel sections to existing concrete structures. Most of

the traditional methods of strengthening require the use of heavy steel sections that are

not easy to install at the site and may corrode easily when exposed to the weather.

According to the American Concrete Institute Committee 440 report (ACI Committee

440 2008), the advanced properties of CFRP composite materials make these products

ideal for use in different retrofitting processes in concrete structures, to enhance the

flexural and/or shear capacity of the structural member. However, the structural

mechanism and performance of these composite materials are still not fully understood.

The success of the strengthening or rehabilitation process with CFRP is crucially

dependent on the bonding conditions between the CFRP system and the substrate

structure. Bond defects due to improper CFRP application, delamination and cracking

can reduce the integrity and compatibility of the composite structure strengthened with

CFRP applications. The bond between adhesive and substrate structure is one of the

load path steps in the strengthening system, and it needs to be strong enough to transfer

Chapter One

2

the stresses to the carbon fibre materials adequately. If the retrofitted structures contain

these kinds of defects, the system will not provide the desired additional strength, and

the designed CFRP- system performance, durability and expected lifetime of the

strengthened structure will be under question. For these reasons, a process to detect and

study bond defects and to evaluate the installation quality of externally bonded CFRP

applications to civil engineering structures is urgently needed.

Different non-destructive methods have been used in bonding CFRP systems in

aerospace and mechanical applications. However, civil engineering structures differ

from other applications. Therefore, there is a need for a reliable and efficient method to

identify and detect bond defects and delamination of CFRP composites applied in civil

engineering structures.

There are several common non-destructive testing (NDT) methods to evaluate material

integrity and the overall composite structural consistency in civil engineering

applications. Nevertheless, because CFRP systems lack magnetism and electrical

resistance, some traditional non-destructive methods face major complexities in the

evaluation and detection of bond defects and delamination between CFRP and concrete

structures. According to the ACI 440 committee, several methods can be applied to

detect CFRP composite bonding defects, including acoustic emission, ultrasound, laser

shearography and infra-red thermography nondestructive tests methods. Acoustic

emission captures stress elastic waves produced by the development of cracks in

structures. Damage severity can by estimated through the study and analysis of these

waves. However, this method has limited capability to be applied in the field due to

reading errors that come from the noisy atmosphere of most civil engineering sites.

Ultrasound is a method which depends on injecting the structure with echo pulses and

receiving the reflected waves. These waves convey substrate defect data and provide

quantifiable information about the overall state of the structure. In spite of the

widespread use of this method in aerospace and mechanical applications, the use of this

method in civil engineering field conditions is limited for similar reasons to acoustic

methods. Moreover, because of the CFRP material's high attenuation [around 0.6

dB/mm (W. Hillger, R. Meier and Henrich 2004)] these materials have to be inspected

Introduction

3

with narrow band pulses and low frequencies. All these difficulties in meeting field

conditions requirements narrow the acoustic and ultrasound nondestructive methods

which can be applied widely to civil engineering applications. The laser shearography

method functions by projecting a laser beam onto the investigated surface and recording

images via a shearography camera. The method has promising abilities in terms of its

defect and flaw detection abilities, but, the high cost of the equipment is the major

reason that limits its use in civil engineering projects.

Infra-red thermography (IRT) nondestructive testing (NDT) has been suggested for the

detection of substrate defects and anomalies in CFRP-concrete and CFRP-steel

structures. The method is based on capturing the emission of infra-red radiation from

the investigated surfaces. Anomalies and defects under these surfaces can be localized

and observed in the thermal images (thermograms) with different temperature patterns

to the sound surrounding areas. IRT NDT can overcome the drawbacks and functional

difficulties of other nondestructive methods, including irrelevant sound information

coming from noisy field conditions. Moreover, the IRT equipment costs are reasonable.

IRT is easy to perform in different field conditions and can be used to evaluate and

inspect large areas. These advantages make IRT NDT a promising method for civil

engineering observation processes that can be executed effectively in most CFRP

strengthening applications.

1.2 Research objectives

Infra-red thermography has been promoted as an efficient method for the evaluation of

structural system integrity. Previous researchers have studied the use of IRT to detect

defects and anomalies at the FRP/concrete interface. However, most previous studies

have focused on qualitative IRT rather than quantitative assessment. A fully

comprehensive assessment of quantitative thermography in civil engineering

applications has not yet been provided. The application of the IRT in concrete and steel

structures strengthened with CFRP systems needs further investigation. Moreover, there

remains a lack of detailed scientific studies of the best test configuration and inspection

techniques for the thermographic evaluation of structures. If this NDT method is to

Chapter One

4

become widely used for the detection of bond defects and delamination in external FRP

composite bonded to concrete structures, a standard method with acceptable reliability

is required. The development of such a method requires a full understanding and deep

analysis of the parameters and factors controlling temperature re-distribution, heat flow

and radiation behaviours on the CFRP-substrate bond zone.

This thesis concentrates on experimental and numerical studies to develop a standard

methodology for the application of non-contact IRT NDT to assess concrete and steel

structures strengthened externally with different CFRP composites.

1.3 Research phases

Multiple approaches were presented in this research study. The research started with a

literature survey of IRT NDT and its application in CFRP strengthening in civil

engineering projects.

The next part of the study involved qualitative IRT studies applied to controlled-defect

specimens.

The third phase of this research investigation drew on the data gathered from an

extensive laboratory experimental program that using quantitative IRT techniques.

The final phase involved generating a finite- element numerical model to study the

different parameters influencing thermal responses in the IRT testing.

1.4 Thesis outline

This dissertation consists of six chapters, including this introductory chapter. Chapter 2

presents literature review including all the existing knowledge on IRT technology,

CFRP materials and systems and the use of IRT to evaluate bond defects in CFRP

retrofitted structures. Chapter 3 reports laboratory experimental work using the

qualitative IRT approach, and the deficiencies and drawbacks of this approach. Chapter

4 reports the results of a quantitative IRT laboratory experimental program on CFRP-

Introduction

5

strengthened concrete and steel specimens. The results of different quantitative studies

are reported in this chapter to help establish a standard for the use of IR NDT to detect

bond defects in structures strengthened externally with different CFRP products.

Chapter 5 presents a numerical approach to the study and assessment of the behaviour

of existing thermal models of retrofitted specimens. In addition, finite element modeling

is adopted to predict the thermal responses for other circumstances. A parametric study

is reported to examine the major factors influencing defect detection. Finally, in Chapter

6, major conclusions from this research are presented, with recommendations for future

studies.

Literature review

7

2 CHAPTER TWO: LITERATURE REVIEW

2.1 Introduction

Numerous studies on the detection of defects in the bonding area between FRP and

structures have been conducted using IRT NDT, and different approaches, parameters

and characteristics have been adopted. The literature review in this chapter is devoted to

IRT, FRP strengthening systems, and the inspection of defects in FRP composite

structures.

This chapter is divided into three main parts. The first reviews the principles of IRT

NDT and its applications; the next addresses the use of FRP composites for

strengthening structures; finally, the third part reviews the detection of FRP bond-

interface defects by IRT.

2.2 Infra-red thermography

2.2.1 Background

From the beginning of civilization, light was always an important issue in human life.

Man was curious about light and even gave it religious significance. Methods and

instruments for observing light have been recorded from early written history. One of

the oldest instruments in the world is the Nineveh Lens. It was discovered in northern of

Iraq, in deposits dated to 722 B.C. It was used as a lens to concentrate the sunlight (Kett

1958). At the beginning of the 1st century Ptolemy studied different properties of light.

He investigated the refraction of light for a series of materials with high transparency in

his book “Optics” (Ptolemy and Smith 1996). In 1021 Ibn Al-Haytham Alhazen

provided for the first time an explanation of twilight (Sabra 1989), and observed light

through a pinhole camera. As early as 1310 Dietrich von Freiberg gave the positions of

the primary and secondary colors of the rainbow. Most of light’s properties had been

highlighted and formulated after Willebrord van Roijen Snell stated his law of light

refraction, and Issac Newton delivered his Hypothesis of Light theory during the 1600s.

Chapter Two

8

The experiments of William Herschel in 1800 led to the discovery of infra-red radiation

(Herschel 1800a). On 13 March 1793 he accidentally discovered the planet Uranus

(Maldague and Moore 2001). During his work as an astronomer he tried to use a prism

to keep his eyes undamaged when examining the sun. This led him to discover infra-red

rays. He employed a glass prism to scatter the sunlight onto a number of mercury

thermometers. During his examination of the separated light he found that just beyond

the red colour, where there was no visible light, the thermometer recorded the highest

temperature. He concluded that there are invisible rays beyond the red colour of visible

light. He named these rays “the solar and the terrestrial rays that occasion heat”

(Herschel 1800b). Herschel demonstrated that the spread of these rays depends on the

medium or object properties. By using the newly invented thermocouple, Ampere stated

that both infra-red and visible light were the same phenomenon and had the same

optical characteristics (Hindle 2008).

There were several achievements during the nineteenth century after Herschel’s

experiments. The first infra-red image was created in 1840 by Herschel's son Sir John

Frederick William Herschel. He uses an evaporograph (Maldague and Moore 2001). In

1900 Max Planck formulated his law of radiation. Major improvements in the infra-red

industry sector were made during and after World War II. Most of these patents were

for military purposes, such as the detection of soldiers, ships and torpedoes (Maldague

and Moore 2001). Later, many innovations were applied in the medical, scientific and

environmental industries. Infra-red thermal imagers begun to supplied commercially in

the 1960s, and a giant leap in infra-red detection capability took place in the 1980s

when array detectors (a combination of several single detectors) were adopted and

integrated with microprocessors. This improvement significantly enhanced the

efficiency of infra-red capture and helped the upgrading of infra-red detection devices

with the ability to capture images more swiftly. The digital technology revolution has

significantly facilitated IRT. Advances in the control and calibration of infra-red devices

using computers and the in the capacity to manage and acquire infra-red data and

analyze infra-red images have promoted the use of IRT NDT.

Literature review

9

2.2.2 Fundamentals of infra-red radiation

Heat can transfer in a medium or between bodies by conduction, convection, radiation

or a combination of these. Conduction is the spread of heat energy whenever a

temperature difference exists between two solid materials in contact or among parts of a

material. Convection involves the mass movement of a fluid or gas molecules over a

distance. Radiation occurs when a material emits energy over a distance through a

material, fluid, gas or vacuum. The transfer of energy in electromagnetic wave form is

called radiative heat transfer (Bejan and Allan 2003).

All surfaces above absolute zero temperature emit electromagnetic radiation through the

movement of atoms. This radiation occurs when an electric charge accelerates. The

object's temperature and the surface conditions will influence the radiation spectrum and

intensity. The energy of the atomic particles will increase when the object’s surface is

heated. The atomic particles agitate thermally in a chaotic manner, which generates a

form of radiant electromagnetic energy known as infra-red radiation. The frequencies of

waves produced from this infra-red energy are located between the microwave and

visible light on the electromagnetic spectrum, as shown in Figure 2.1. The wavelengths

will be beyond the red visible light, from around 700 nm to 1 mm where the microwave

range begins. This infra-red range is subdivided into further regions. The International

Commission on Illumination (CIE) places the infra-red in three bands (Byrnes 2009):

IR-A (from 700nm to 1.4µm), IR-B (from 1.4µm to 3µm) and IR-C (from 3µm to

1mm). An international standard for the boundaries of the infra-red sub-regions is not

yet available. Different infra-red band classifications are available in astronomy that set

the IR regions in three bands (near, mid and far infra-red) with wavelengths from 700

nm to 350 µm (NASA ipac 2007). Another subdivision considers the infra-red

detector’s sensor response. However, the most accepted and common subdivision is

illustrated in Figure 2.1 and the infra-red bandwidth is distributed as follows:

Near-infrared (NIR): its wavelength varies from 750 nm to 1.4 μm

Short-wavelength infrared (SWIR): wavelength ranges from 1.4 μm to 3 μm

Mid-wavelength infrared (MWIR): 3–8 μm is the spectrum range of this IR

band. Intermediate infrared (IIR) is another name for this wavelength.

Chapter Two

10

Long-wavelength infrared (LWIR) wavelength is between 8 and 15 μm. Most

passive thermography works in this region of the infra-red rays.

Far infrared (FIR) band has wavelengths beyond 15 μm up to 1,000 μm.

Figure 2.1 Infra-red wavelength ranges

When the object is subjected to infra-red radiation, the part absorbed by the object will

convert to heat. Radiation intensity as a type of heat transfer is measured in watts per

square metre (W.m-2), and as mentioned above, depends on the temperature and the

object’s surface conditions and nature. Usually infra-red radiation has a constant

wavelength at a specific temperature range. At higher temperatures, the wavelengths of

the radiation intensity are shorter, while the band wavelengths become longer when

temperatures are low. All materials change their internal energy continuously at a

molecular level by emitting and absorbing photons and electromagnetic waves. Most the

visible light behaviours are applicable to infra-red radiation. Thermal radiation is

emitted in all directions: it reflects, moves in straight lines, bends, interferes, is

absorbed, and travels in an ideal vacuum at the same speed as visible light (≈

1,079,253,000 km/hour) (Maldague and Moore 2001). The absorbed part of thermal

radiation will transfer to heat and increase the surface temperature of the material.

Literature review

11

Energy radiation is exchanged continuously between surfaces and objects, even when

the surfaces and bodies are in temperature equilibrium.

2.2.3 Fundamentals of IRT NDT

IRT is a method which reads the emitted electromagnetic radiation from the object’s

surface or medium of interest. There are two modes of measuring the temperature:

contact and non-contact. The contact mode is commonly by means of sensors attached

to the object of interest. These sensors measure the temperature as electrical signals.

Thermocouples, thermistors, integrated circuit sensors, and resistance temperature

detectors are the most common transducers (Maldague and Moore 2001). Temperature

can be measured in a non-contact mode by using different kinds of sensors and detectors

including photonic detectors, quantum detectors, pyroelectric detectors, and infra-red

imaging devices. Most of these measurements are based on fundamental principles of

thermodynamic relationships. Infra-red imaging “thermometers” are the most widely-

used form of non-contact temperature measurement. The wide temperature ranges that

these imagers cover make them appropriate for use in many different applications.

However, the variety in these devices is based on the test environments and targets for

which the infra-red imager is designed. For that reason, it is essential for persons who

conduct IRT testing to have a very good understanding of the thermal test environment.

A testing program must take into consideration many parameters and factors before

infra-red testing can be conducted. However, the major task for the thermographer will

be interpretations after the collection of the desired results. Infra-red thermal detector

measurements are exposed to different kinds of faults including surface emissivity,

reflections and fluorescence. Special precautions need to be taken to reduce errors in

thermograms (thermal images) to minimize misreading of results.

2.2.4 Theoretical principles

2.2.4.1 Planck’s law

The thermal radiation that leaves a material’s surface is called the emissive power, and

it is measured per area of that surface. The total sum of emitted energy over the entire

spectrum is called total emissive power (E). The energy power at a given frequency is

Chapter Two

12

called spectral emissive power (Eλ). Many factors affect the total emissive power

including material surface properties, surface original temperature, and material type.

The ideal material that does not reflect any radiation is called blackbody (ASTM E 1965

2003). The surface of this blackbody is a perfect absorber which can absorb all radiation

in any wavelength and direction. Apart from being a perfect absorber, the blackbody is

also a perfect emitter. At a particular temperature and wavelength, no surface can emit

energy greater than a blackbody. In his law, Max Planck quantified the blackbody’s

emissive power, as shown in Equation 2.1 (Planck and Masius 1914; Bejan and Allan

2003):

( )

[ (

) ]

Equation 2.1

where,

Eλb = spectral emissive power for a blackbody (W/m3),

h = Planck’s constant (6.626×10-34 J.s)

co = The speed of light in vacuum

λ = wavelength (m),

T = absolute temperature (K),

n = constant refractive index (equal 1 in vacuum),

k = Boltzmann’s constant (1.3806 × 10-23 J/K).

By simplifying Equation 2.1:

[ (

) ] [ ]

Equation 2.2

where,

C1 = the first radiation constant (2πhco2) = 3.7419 × 10-16 (W/m2),

C2 = the second radiation constant (hco/k) = 0.01438769 (m.K).

Literature review

13

Figure 2.2 shows Equation 2.2 for a range of different wavelengths and temperatures. It

reveals that radiation energy is a function of the wavelength for a specific temperature.

In the figure the wavelength is in µm and the blackbody emissive power has been

plotted in W/m2.µm.

Figure 2.2 Spectral blackbody emissive power (ASM 1992)

As shown in this figure, the wavelength that corresponds to the maximum emissive

power is related to the absolute temperature. The maximum of Equation 2.2 is known as

Wien’s displacement law:

C3 = λmax. T = 0.028978 m.K Equation 2.3

where C3 is known as the third radiation constant.

Because the value of the [exp (C2/λT)] in Equation (2.2) is significantly greater than 1 in

infra-red thermography applications, Equation 2.2 can be re-introduced as:

Chapter Two

14

( )

[ (

)] [ ]

Equation 2.4

Equation 2.4 is known as Wien’s law. It provides approximate values for the original

equation.

By integrating Equation 2.2 over the entire spectrum length the total emissive power for

a blackbody can be shown as:

∫

[ (

)] [ ]

Equation 2.5

Resulting in

Equation 2.6

where σ is the Stefan-Boltzmann constant and has the value of ( 5.67051× 10-8

W/(m2.K4)). Equation 2.6 is known as Stefan-Boltzmann’s law and it calculates the

radiation emitted from an ideal blackbody surface.

2.2.4.2 Emissivity

Emissivity (ε) is a variable defined as the ratio of the electromagnetic radiation emitted

from a surface to the radiation that would be emitted from an ideal blackbody at the

same temperature. Emissivity of all materials is measured on a scale between 0 and 1.

Blackbody has an emissivity of 1. All other materials have absorptive values of less

than 1. The spectral distribution and the emissive power value are the factors that make

the difference in the spectral emissive power between a real material and a blackbody.

Figure 2.4 shows the effect of emissivity on radiation intensity. The figure shows that at

all temperatures and wavelengths, grey bodies have similar emissivity distributions but

less emissivity than blackbody. All other materials that have different distributions (not

similar to the grey body pattern) over the wavelength are defined as spectral radiators.

However, many materials exhibit approximately grey body behaviour.

Literature review

15

Figure 2.3 Emissivity effect on radiation from surface of emissivity ε with hypothetical

intensity (Maldague and Moore 2001)

The incoming radiation on a surface might depart in a specular or diffuse manner.

Figure 2.5 illustrates the reflection of both manners. These two manners apply for both

emittance and reflectance radiations. The radiation may also be reflected in a manner

between them, as shown in Figure 2.5b. Diffuse emittance has no favored directions,

and the angle of the incoming ray (α) in Figure 2.5c is assumed to not affect the

outgoing direction (Lienhard 1981). The radiation departs blackbodies diffusely.

Figure 2.4 Specular and diffuse radiation reflection [Reproduced from Lienhard (1981)]

Radiation emitted in all directions from material surface is known as hemispherical

spectral emissivity. The hemispherical spectral emissivity of a grey body is defined as:

Chapter Two

16

( ) ( )

( ) Equation 2.7

where,

ε (T,λ) = spectral emissivity,

Eλ = spectral emissive power for grey body (W/m3).

The total hemispherical emissivity of a real material is defined as the ratio of the total

emissivity on the material surface to that of an ideal blackbody at identical temperature,

( ) ( )

( ) Equation 2.8

where,

ε (T) = total emissivity at specific temperature,

E (T) = total emissive power for grey body (W/m3) at specific temperature.

From Equations 2.7 and 2.8 it can be noted that emissivity is a function of the

wavelength and temperature. However, emissivity at the same time is a function of the

material surface properties. Rough surfaces have higher emissivities than smooth

surfaces. These smooth materials are more difficult to test thermally than materials with

higher emissivities (Maldague and Moore 2001). Coated surfaces have different

emissivities depending on the coating properties. From Equation 2.6 and 2.8 the total

emittance of grey body at a particular temperature can be measured as shown in

Equation 2.9.

( ) Equation 2.9

The measurement of infra-red thermal radiation is influenced by many different

parameters. The material absorptivity, emissivity and reflection properties influence the

thermal reading continuously, even if the material is in a condition of thermal

Literature review

17

equilibrium. In addition, several features affect thermal detector performance and cause

errors in the thermal reading and results, including noise and atmosphere conditions.

For any thermal test, all these factors lead to thermal reading errors and need to be taken

into consideration by the thermographer during the IR test and in the analysis of the

results.

2.2.5 Infra-red thermography techniques

Many techniques are applied in IRT NDT; however, the most generally recognized

approaches that are used in different applications are passive and active techniques. The

test used depends in both techniques on the difference in temperature between the target

object Ttarget and its ambient. However, in the active approach the test is conducted with

an external heat source applied to the investigated surface. In contrast, a thermal steady-

state procedure is usually required in the passive technique.

IRT testing involves temperature and heat flow measurement to detect and calculate

defects or failures within materials. To interpret the temperature level and temperature

changes on a test specimen, a fundamental knowledge of the heat transfer pattern and

thermal properties of the test material is essential.

IRT imaging is the non-contact, non-destructive mapping of thermal behaviour on the

target test surface. Thermal imaging equipment is available in numerous conformations

and with varying degrees of complexity (Maldague and Moore 2001). The maps

recorded by thermal imaging equipment are usually termed thermograms. The

thermographer should have expertise in heat flow and infra-red radiation and must be

familiar with the thermal imaging equipment’s capability and functioning in order to

acquire the best thermal image and to enhance the analysis of the thermograms.

2.2.6 Passive techniques

In passive thermography materials are tested naturally, without applying any external

heat flow or using external excitation systems. No heating or cooling is applied to the

material. The approach depends on the natural difference in the temperature pattern

Chapter Two

18

between the material and the surrounding ambient. The evaluation of a material

according to its temperature distribution depends on its ideal temperature value, the rate

of temperature change, and the actual difference between the material and the ambient

or a reference.

Astronomy is the field of science where IRT started, and infra-red technology has

enhanced astronomical observations and encouraged qualitative assessment of telescope

performance. Figure 2.5 shows a comparison of the universal galaxy M51 imaged with

the Spitzer Space Telescope and an image of the same galaxy taken by the Herschel

Space Observatory which was launched in May 2009 with a state-of-the-art infra-red

imager. The Herschel Space Observatory has the ability to provide three colour far-

infra-red images of different wavelengths. The Herschel infra-red images reveal

structures that cannot be discerned in the Spitzer image (European Space Agency

2011a).

Figure 2.5 M51 imaged with the Spitzer Space Telescope and an image of the same galaxy taken by the Herschel Space Observatory (European Space Agency 2011b)

Passive thermographic testing is generally used to monitor the production and different

stages of manufacturing where non-standard temperatures may indicate potential errors

or problems. Different materials and applications have been tested using this approach

such as metal fabrication and steel quality, glass production and bottle forming (Wilson

1991), and welding quality control (Nagarajan, Banerjee, Chen and Chin 1992;

Nagarajan, Wikle and Chin 1992) (i.e. tracking of seams and checking their quality).

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Figure 2.6 shows the IR thermogram used as a tool to evaluate the quality of the

welding process in a railway.

Figure 2.6 Thermogram of railway weld (Khauv 2011)

IRT recently been applied to micro-scale industries. IR detectors are used in electronics

manufacturing product lines to monitor if there are any abnormalities within the

product, as shown in Figure 2.7. The IR images in this figure were captured with a

SC7600-M FLIR infra-red imager with G3 lenses that have zoom capability up to 5µm

to detect and evaluate microchip electronic connections.

Figure 2.7 Microchip connection checking using IRT (Khauv 2011)

Passive IRT is also used in the evaluation and rehabilitation of historical buildings. This

NDT is commonly used to investigate and evaluate the whole building structure and the

Chapter Two

20

structure beneath the plaster surfaces. Figure 2.8 shows a thermal image captured by a

FLIR team to diagnose problems with the Basilica of the Sacred Heart in Paris.

Figure 2.8 IR image of the Sacred Heart building in Paris

Passive techniques can also be used to evaluate insulation systems in buildings (Lyberg

and Ljungberg 1991) and monitor the maintenance of these buildings. For example,

water leaks as a serious problem that IRT can detect. The infrared detectors can

recognize the presence of water easily due to the differences in thermal properties

between water and building materials. Problems including water leaking into the

building through windows, sliding doors at balconies or even roofs can be monitored

using IR testing. Figure 2.9 shown as the IR image of water leaks in the ceiling of a

building in Chicago using a FLIR T300 infrared imager. The early detection of these

faults can minimize the repair process and cut costs.

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21

Figure 2.9 IR diagnosis of water leaks in ceiling (Chicago Infrared Thermal Imaging

Inc. 2011)

Passive IRT has also been used to investigate furnaces and heating structures to

diagnose the causes of heat losses (Ljungberg 1997). General thermal building

performance can also be investigated by this technique. Heat losses can be formalized

and estimated by adopting passive IRT techniques (Vavilov, Anoshkin, Kourtenkov,

Trofimov and Kauppinen 1997). Gas emission tracking and detection are usually

carried out in a passive testing scenario (Ljungberg and Jonsson 2002b). Figure 2.10

shows the tracking of emissions by thermal images in field. Although there are some

gases that cannot be distinguished by IRT imaging, the passive approach can be

supported with heated or cooled backgrounds to solve the problem of gas invisibility in

the thermal images. This application provides a valuable solution for the monitoring of

gas leaks in gas pipe- lines.

Figure 2.10 Gas leak thermography test from a pipe buried at 80 cm depth (Ljungberg

and Jonsson 2002b)

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22

More recently, passive thermographic techniques have been used to investigate and

calibrate greenhouse heating systems and to indicate any abnormality during plant

growth, as shown in Figure 2.11 (Ljungberg and Jonsson 2002a).

Figure 2.11 Infra-red sensor for control of the leaf temperature, Thermograms indicate

deficiencies in the gas-IR heating system (Ljungberg and Jonsson 2002a)

Applications of the passive approach are numerous. It has been employed in medicine

in the last two decades, and it has become a very efficient tool for medical and

veterinary applications. Thermal imaging is an effective means to detect anomalies and

abnormalities that cannot be identified with the naked eye, or even X-rays and

ultrasound in some circumstances. Thermographic devices allow the early diagnosis of

illnesses related to blood circulation problems, and the identification of problems

connected with rheumatology, neurology, orthopedics, and sinusitis. It has been shown

to be very efficient in sports medicine for the diagnosis of neuromusculoskeletal

damage (Meditherm Inc. 2009). Figure 2.12 shows how thermal imaging can assist with

the location of health problems. Because each part of the body has a particular

thermographic pattern, the observation of differential heat patterns helps oncologists to

monitor breast health and to diagnose breast cancer in the early stages (Head, Lipari,

Wang and Elliott 1997; Lipari and Head 1997). Figure 2.12-c shows a thermographic

cancer inspection of a woman’s breast. This approach is considered risk-free compared

with other tumor detection methods such as mammography and X-rays.

Literature review

23

(a) (b)

(c)

Figure 2.12 Health problems diagnosed by IR thermal imaging, (a) Diagnosis of jaw problem (Meditherm Inc. 2011a) ; (b) Football player with stress fracture (Meditherm

Inc. 2011b) ; and (c) Breast thermography diagnosis (Meditherm Inc. 2011c)

IRT detection helps art historians to check pentimento and painting alterations in

masterpieces beneath the surface of the painting. This process can help to distinguish

originals from copies and to study the previous trials of the drawing or the artist’s

guidelines. Figure 2.13 reveals the under-drawing infra-red image of the DaVinci

masterpiece “The Virgin of the Rocks”.

Chapter Two

24

Figure 2.13 The Virgin of the Rocks under-drawing infrared image

In meteorology, weather satellites equipped with infra-red technology scanning in the

range of 10.3 to 12.5 µm facilitate the calculation of water and land temperature, and

cloud monitoring. The Australian region infrared satellite image issued by the

Australian Bureau of Meteorology at 11:37 am EST Sunday on 28 August 2011 is

shown in Figure 2.14. Infra-red satellite images are used in weather warnings and

predictions. For example, people can receive advance warnings about possibly severe

hurricanes. Figure 2.15 shows the IR satellite image of hurricane Irene at 12 pm on

Sunday, 28 of August 2011 before hitting New York City. Such information helped the

New York City government to give the order for the evacuation off residents well

before the hurricane’s arrival.

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25

Figure 2.14 Australian region infrared satellite image (Australian Bureau of

Meteorology 2011)

Figure 2.15 Hurricane Irene arrives in NYC (The City of New York 2011)

Passive IRT techniques are also used in biology, for the detection of forest fires, the

monitoring of road traffic and for military purposes (Maldague 1993), as shown in

Figures 2.15 to 2.19.

Chapter Two

26

Figure 2.16 Infra-red biological application: Brazilian free-tailed bat (Center for

Ecology and Conservation Biology-Boston University 2011)

Figure 2.17 Aerial fire IR mapping (Khauv 2011)

Figure 2.18 Load traffic IR monitoring (Khauv 2011)

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27

Figure 2.19 US Navy IR imagery taken from a U.S. NavyP-3C Orion maritime patrol

aircraft, assisting in search and rescue operations for survivors of the Egyptian ferry Al Salam Boccaccio 98 in the Red Sea (U.S. Navy 2006)

Figure 2.20 High speed IR detector image for machine gun testing (Khauv 2011)

From all the above applications and uses, the passive approach is recommended in the

industry sector because it provides enhanced quality during the production process. The

use of this infra-red technology in civil engineering applications will reduce expenditure

on rehabilitation and repair operations and minimize the amount of energy consumed.

Chapter Two

28

In addition it has the potential to be used for other applications because of its accuracy

and speed.

2.2.7 Active technique

The active IRT technique generally depends on the fundamental principle that heat

transfer in material is changed by the presence of material discontinues or the

occurrence of debond and cracks. Alterations in heat transfer appear as different

temperature patterns on the surface of material subjected to external heat flux. Because

of the differences in surface temperatures, areas with underlying defects will appear

with different temperatures (hot or cold spots) with respect to the surroundings area.

Figure 2.21 illustrates the mechanism used to localize hot spots. If a constant heat flux

is applied to a homogenous surface that has no defects, the increase in the surface

temperature should be uniform in distribution. Therefore, if the surface has any kind of

anomaly or defect, such as delamination, cracks, and voids, it will affect heat flow

through that material (Malhotra and Carino 2004).

Figure 2.21 Hot spot localization

To investigate materials using this technique, an external heat source is required to be

integrated as an excitation system during thermal imaging. This approach is one of the

most popular thermal stimulation methods in infra-red thermal techniques. The term

“active thermography” is used as an encompassing term for all non-destructive

Subsurface defect

Subsurface defect

Hot spot

External Applied Heat

Literature review

29

evaluations carried out with thermal cameras and external excitation heat sources (Shull

2002). However, the three major active thermography techniques are:

Pulsed thermography,

Step heating thermography,

Lockin thermography.

2.2.7.1 Pulsed thermography technique (PTT)

The pulse thermography active procedure is based on exposing the material surface to a

short temperature simulation and recording the temperature pattern on the surface of the

heated material as thermal images. After short thermal injection the temperature on the

material surface alters quickly because of the material’s diffusivity properties and

radiation. The alteration in the rate of diffusion due to the presence of discontinuities

and defects will make these areas appear with different temperatures with regard to the

defect-free neighbouring areas observed with an IR thermographic imager. The areas of

discontinuities will appear with different temperatures relative to the non-defected areas

at the surface in the thermal image. Due to the test’s high speed and accuracy, infra-red

PTT is a very common method in the active approach (Vavilov and Maldague 1994).

There are several different active IR PTT test configurations and setups. Figure 2.22

shows the active test set-up by line, point and surface. Each type of configuration has its

advantages and disadvantages. The advantages of line pulse infra-red thermography for

instance include the homogeneity of the thermal simulation on the investigated area, and

continuous control over the heat transit. Nevertheless, this kind of test cannot be

employed on the entire surface. The line heating sources involve flashing lamps, laser

beams, or even air jets. This set-up is recommended for the inspection of cracks parallel

to the heating line (Lesniak 1995). Line pulse configurations are illustrated in Figure

2.22a. The point infra-red test involves heating the inspected point by a spot heat light

beam. This type of set-up is suggested for the IRT investigation of limited localized

areas. Like the line setup this configuration is not suitable for the inspection of entire

surfaces. Figure 2.22b shows the point test set-up. Figure 2.22c shows pulse IRT by

surface inspection. Although various heating sources can be used for this configuration,

Chapter Two

30

lamps and scanning lasers are the most common. The capability to test the entire surface

is the most important feature of this set-up. However, the homogeneity of the external

heating distribution is still a challenge during the thermogram analysis of this

configuration.

Figure 2.22 IR pulsed thermography test configurations, (a) line method, (b) point

method and (c) surface method

Cold thermal sources can be used if the material that needs thermal investigation is

already in a hot ambient. Sources like water line jets, ice or cold air jets follow the same

fundamental principles. The thermographic test is based on the variation between the

test material and the ambient, whatever that difference is.

There are two basic methods of observation for any infra-red active technique:

reflection (one-sided) or transmission (two-sided). Figure 2.23 shows both methods in

reflection and transmission configurations in the defect detection phase. In the reflection

method the excitation sources and the thermal detector are positioned on the same side

of the inspected target. The defects will appear as a hot spot, as shown in Figure 2.23c.

The thermal image captured by this test method offers higher resolution than the

transmission method. However, the reflection method’s ability to detect deep defects is

very low. In contrast, the transmission method reveals defects as cold spots in the

thermograms, as shown in Figure 2.23d. Thermograms obtained by this method provide

good information regarding the detection of deep defects while their resolution is

usually low. However, the signal observed in both methods will have the same

Field of view and observation area

Infrared Detector

Heating Source

Specimen under investigation

`

Processing

Line Heating Source

Infrared Detector

Specimen under investigation

Direction of scanning

`

Processing

`Processing

Infrared Detector

Spot Heating Source

Specimen under investigation

(a) (b) (c)

Literature review

31

behaviour. Figure 2.24 illustrates heat sources and the infra-red recorded wave shapes in

the PTT approach.

(a) (b)

(c) (d)

Figure 2.23 Schematic of (a) Reflection observation method (One-sided); (b) Transmission observation method (Two-sided); (c) Reflection observation and hot spot

image; (d) Transmission observation and cold spot image

Figure 2.24 Pulsed heat and IR recorded waves in pulsed thermography approach

Chapter Two

32

The active pulsed thermography technique is very widespread because inspection

requires short capture times (Vavilov and Maldague 1994), although the resolution

limitation for deep reading is its main drawback.

2.2.7.2 Step heating thermography

The step heating thermography technique involves monitoring the target surface for the

period of application of pulsed heating. This approach usually does not require high

heat. Temperature calibration as a function of time is one of the major features of this

approach (Aamodt, Spicer and Murphy 1990). The blur in the thermal image can be

reduced by using step heating thermography, which makes the detection of deep

material defects and discontinuities easier (Osiander and Spicer 1998). This technique is

also used to determine material thermal properties such as conductivity. The possibility

of early thermal calibration is the main feature of this method in respect to the pulsed

thermography technique. However, the decision of whether to test material using a

pulsed or step heating thermography approach usually depends on the accessibility of

heating sources and the capability to control and generate heat waves in steeply manner.

2.2.7.3 Lockin thermography technique (LTT)

The basic idea of the lockin thermography active technique is to generate thermal waves

within the tested material and monitor the surface closely (Busse 1994; Gerhard and

Busse 2006). This approach was derived from photothermal radiometry (Kanstad and

Nordal 1979). Thermal waves can be generated externally by optical periodical

illumination, for instance, by laser beams and halogen lamps, or internally by subjecting

the tested material to modulated acoustic waves. The lockin active technique allows

better energy control over the inspected surface. However, this approach normally takes

more time than pulsed thermography because the experiment must be conducted for

each depth of the specimen (Clemente Ibarra-Castanedo, Stéphane Guibert, Jean-Marc

Piau, Xavier P. V. Maldague and Abdelhakim Bendada 2007). This can be performed

by examining the material over a wide range of different frequencies. This active

technique has applications in coating thickness measurement, and sub-surface defect,

anomaly and discontinuity detection (Rantala 1996). The general test configuration of

Literature review

33

the lockin thermography active technique is illustrated in Figure 2.25. The introduction

of different frequencies in this approach leads to better analysis with respect to depth

and noise (Gerhard and Busse 2006). A laser beam is used to introduce modulated

thermal waves into the inspected material. Modulated halogen lamps can take the place

of the laser beam to provide low frequency thermal waves simultaneously to the entire

investigated area. At the same time as the thermal wave injection, an infra-red detector

monitors and captures the thermal wave’s response and decomposes it by a lockin

amplifier to extract the amplitude and the modulation phase. Figure 2.26 shows the

lockin setup with both laser beam and lamp. Sinusoidal thermal injected wave and the

infra-red recorded wave shapes produced by the lamp are shown in Figure 2.25.

Figure 2.25 Sinusoidal input wave and IR recorded wave in LTT approach

Figure 2.26 Basic locking thermography set-up, laser beam and lamp (Gerhard and

Busse 2006)

Chapter Two

34

Generation of thermal waves can be introduced internally by the simulation of elastic

modulated waves. The mechanical energy will change to heat due to the collision of the

internal free surfaces with defects, small discontinuities or even micro-cracks (Clemente

Ibarra-Castanedo, Stéphane Guibert, Jean-Marc Piau, Xavier P. V. Maldague and

Abdelhakim Bendada 2007). Ultrasonic waves are used because of their efficient ability

to transform into heat, and these waves will not increase the stress on the mechanical

discontinuities (Maldague and Moore 2001). The temperature surface map can be

provided by using an infra-red thermal camera or by coating the inspected structure with

temperature-sensitive liquid crystals (Broutman, Kobayashi and Carrillo 1969).

However, infra-red cameras are more flexible because there is no need for surface

preparation as in the liquid crystal system. Figure 2.27 illustrates the lockin

thermography technique with ultrasonically-modulated internal simulation. This

technique is applicable for revealing cracks in metals, detecting damaged areas in

laminates, and identifying corrosion in metals (Salerno, Wu and Busse 1997). A

comparison of optical and ultrasonic lockin thermography waves is shown in Figure

2.28. The ultrasonic scenario shows a potential capability to detect deeper defects with

respect to optical lockin. This is because the thermal waves generated in this scenario

have to transmit only half the distance (between the discontinuity and the surface) than

with optical means.

Figure 2.27 LTT set-up with ultrasonically modulated internal simulation

Processing

Ultrasonic transducer

Controlling

Amplifier

Infrared Camera

Literature review

35

Figure 2.28 Two means of generation of thermal waves in LTT

It is important to point out that more than one active technique can be used in the same

thermography test. For instance, one technique can be employed for general scanning

and once the discontinuity regions are detected, another scenario can be adopted for

deep inspection. Moreover, these techniques can be linked. Pulsed phase thermography

(PPT), for example, is a technique which links the pulsed and lockin thermography

active approaches. In the PPT technique a special thermal wave with specific frequency

is generated to target a specific material’s depth which will make a frequency-to-

frequency analysis similar to the lockin analysis based on pulsed thermography data.

This approach was introduced (Maldague and Marinetti 1996) to merge the advantages

of both the pulsed and lockin thermography techniques.

In summary, a collection of active infra-red thermography techniques to detect

subsurface anomalies and discontinuities is available for a wide variety of applications.

The nomination of the most adequate procedure depends on the particular application

and the availability of experienced staff and experimental resources.

2.2.8 Noise in IRT

Noise can be defined as unwanted signals that arise in infra-red thermography reading

(Hudson 1969). Noise can be categorized into two main kinds: fixed pattern noise and

random noise. Fixed pattern noise refers to noise that has individual patterns, whereas

Subsurface defect

Subsurface defect

Thermal wave

Ultrasonic wave

Mat

eria

l sur

face

Optical mean to generate

thermal waves for Lockin

thermography

Ultrasonic source to generate thermal waves for Lockin

thermography

Chapter Two

36

random noise has independent signal values to the following or preceding values in

terms of position or time which do not follow any determined pattern. Noise can be

defined according to its probability density function, which describes how often a

particular value of the random variant is detected (Maldague and Moore 2001). A

histogram noise population is usually calculated to predict the probability density

function. As the histograms usually show Gaussian distribution, Gaussian distribution is

often assumed in noise processes in infra-red thermography analysis. However, there is

still a chance of non-Gaussian noise occurring. Different filters are used to reduce noise

effects. The most common filters employed in noise processing are Gaussian,

neighbourhood averaging, Butterworth, median and harmonic filters.

To identify the noise content shown in infra-red images it is necessary to analyze two

images at pixel level (Haddon 1988). If the two thermal images have the same scene

under the same condition then noise will appear as the differences between the two

images. The ratio of signal power to noise power is defined as the signal-to-noise ratio

(average power image / average power noise), which can be evaluated from the

following equation (Maldague and Moore 2001):

∑ ∑

Equation 2.10

where,

√∑ ∑ ( )

Equation 2.11

| | Equation 2.12

i , j = the x and y positions in an image of N ×M pixels,

µ = the mean of the noise distribution.

Literature review

37

2.2.9 Errors in IRT

Radiation heat flow is a complex process. Any radiation measurement is subject to a

number of possible sources of error that can mislead image interpretation. These

potential errors are the result of radiation transmission across a medium that splits the

infra-red detector and the tested material surface. In that medium a part of the radiant

energy may be absorbed or change its direction. For that reason it is essential to have

knowledge of the properties of the medium as well as the surface properties of the

material. The errors that can affect infra-red measurement can be categorized into three

main groups (Childs 2001):

Process characterization errors involving: surface emissivity, reflections, and

fluorescence.

Transmission path errors involving: absorption, scattering, size of object effects and

vignetting.

Signal processing errors.

Emissivity is already identified for most materials; however, attention should be given

to the surface preparation and finishing of the material. Surface conditions such as

oxidization or polishing alter the emissivity value of the material. Several techniques

exist to increase material emissivity in terms of coating and surface modification.

Different techniques are employed to overcome low emissivity (Maldague and Moore

2001).

Recognizing and avoiding reflections from the background atmosphere is essential in

infra-red thermography recording to minimize errors. Background reflections are

defined as all undesired reflections from external sources that reflect on the surface of

the investigated material. Figure 2.29 shows the background reflections error. During

infra-red thermal capture, the infra-red detector is usually not able to distinguish

between the thermal radiations emitted from the heated material’s surface and the

background radiations that reflect on the same surface. The probability of occurrence of

background radiation reflection is increased for low emissivity materials and if the test

surface is not a plane (Maldague and Moore 2001).

Chapter Two

38

Although background reflections are commonly due to external sources hotter than the

target, reflective error from colder sources should also be taken into consideration. On

the other hand, background radiation from external sources will be hardly noticeable in

the thermal images if the medium of the test is heated well above these external sources

(Childs 2001). The elimination of these background reflections depends on their nature;

if it is point source reflection, the theromgrapher can relocate the infra-red detector until

its best position is identified. The thermographer can also block the line of sight

between the source and the surface. For significant extended source background

reflections, one possible solution to minimize undesired reflection is by shielding the

infra-red detector from these external radiation sources. Figure 2.30 illustrates the use of

a shield as a solution to minimize the background radiation reflections.

Figure 2.29 Background reflection [Reproduced from Childs (2001)]

Figure 2.30 Shielding the test to minimize the significant background reflection

[Reproduce from Childs (2001)]

Material surface

Reflected radiation

Infrared

Detector

Radiation emitted from material surface

Target

In this position the thermal detector is shielded from the additional source of

radiation by the target

Additional source of background radiation

In this position the thermal detector measures both the emitted and the

reflected radiation on the target

Literature review

39

Transmission path errors take place while the radiation is passing the medium between

the infra-red detector and the target investigated surface. Atmospheric effects on infra-

red measurements are complex due to the presence of various gases in the air (which is

the general medium between detector lenses and tested objects), and the differences in

concentration of these gases. Infra-red transmitted energy that crosses the air medium

may be subject to absorption or scattering at various levels which leads to errors in the

infra-red thermal reading. The nature of the medium will determine the number and

severity of these errors. The transparency of air is not 100 percent. All rays and

radiation crossing air will have some part of the transmitted radiation that will be

absorbed. The majority of the absorption in air is due to the presence of water vapour

(H2O), carbon dioxide (CO2) and ozone (O3). However, transmittance is heavily

dependent on radiation wavelength, reading distance, and meteorological conditions

(Maldague and Moore 2001). Figure 2.31 shows the transmittance percentage of these

gases with respect to wavelength.

Figure 2.31 The main gases responsible for infra-red radiation absorption. Atmospheric

transmittance (Maldague and Moore 2001)

From Figure 2.31 it is clear that the transmission patterns flow in a special manner

dependent on the application conditions. For that reason and to maximize the

transmittance percentage, each infra-red detector has specific band infra-red

wavelengths with which it can work, as shown in Figure 2.32. The wavelength range of

these devices is usually related to the application. For most infra-red investigations in

Chapter Two

40

civil engineering, the efficient infra-red spectrum ranges are in the windows of LWIR

and MWIR.

Figure 2.32 IR windows in the spectrum

As the solid particles suspended in the medium, such as dust and smoke have grey body

performance, it is essential for the thermographer to avoid dusty environments (Childs

2001). In addition, these solid particles accumulate on the infra-red detector lenses and

block the radiation or even cause damage to the device. Every infra-red device has its

usage and operational requirements in terms of the humidity, temperature and

environmental conditions in which it can work.

Vignetting is defined as obstruction of the field of view (Childs 2001). The field of view

is the image size with respect to the detector lens scanning angle. It is important to

remove any body that can cause a reduction in the amount of radiation recorded by the

infra-red device.

The last source of error is the probability of error during the recording of the thermal

data. Good quality control throughout IRT testing plays a key role in reducing this kind

of error. To minimize errors of this type, it is recommended to perform important IRT

NDTs twice. Further concerns can be reduced by conducting each test individually by

different thermographers.

Literature review

41

2.2.10 Qualitative and quantitative thermography

Infra-red detector performance is the heart of any infra-red NDT. Its capability in terms

of qualitative or quantitative measurement is the most essential feature of any infra-red

detector. Qualitative thermography is a process by which thermal images exhibit an

infra-red radiation map of the target surface, uncorrected for target, instrument and

media characteristics (Maldague and Moore 2001). Therefore, qualitative infra-red

detectors cannot provide thermograms with accurate temperatures. However, qualitative

detectors can be used for many applications when temperature accuracy is not crucial,

and the development of qualitative detectors means that they are of modest cost

compared with quantitative detectors. In contrast, quantitative infra-red images show the

distribution of the infra-red radiance on the surfaces, correct for target, instrument and

media characteristics and present a true temperature map of the tested surface.

Other parameters affect infra-red detector performance. These parameters control the

process of instrument selection. The infra-red thermography camera will be selected on

the basis of its features according to the application so that it will perform adequately.

Temperature range, temperature sensitivity, speed of response, spectral range,

repeatability, working distance and total field of view are the main performance

characteristics of radiation thermometers.

In this study, both qualitative and quantitative non-destructive infra-red thermography

tests were applied. Thermal sensors were used with advanced uncooled infra-red

detectors to detect differences in temperature (if any) on the surface of interest.

2.3 FRP system and materials

2.3.1 Background

The use of composite materials to enhance structural performance is not a new concept.

The Babylonians used straw to reinforce mud structures, as in the Dur-Kurigalzu

ziggurat in old Mesopotamia near Baghdad. Heavy modern industries in different

sectors like naval, aerospace, and the military always demand new composite materials

Chapter Two

42

with lighter weight and better strength. Carbon fibre composite materials started being

used in Japan and Europe in the mid 1980s (Nanni 1999). In the last decades there has

been an increasing tendency in civil engineering applications to develop new materials

that have better qualities and superior performance. Fibre composite materials are one

of these advanced new materials that are starting to be applied to concrete, steel and

masonry structures. FRP materials have advanced performance in the construction of

civil engineering structures in terms of the following:

High strength

High ductility

High resistance to deterioration

High durability

Low cost

Light specific weight

Small thickness that does not change the volume

Design freedom.

FRP composites are produced by embedding continuous fibres in a resin matrix which

combines the fibres. The fibres as a main load-bearer give the FRP composite its

strength and stiffness to resist different loads. Polymer matrix or resin ensures loads

have homogenous distribution between the fibres. Standard carbon fibre-reinforced

polymer (CFRP) composite is a combination of materials formed of unidirectional

continuous micro-fibres and adhesive matrix. A diagram of a CFRP uni-directional

fibres structure with its component materials is shown in Figure 2.33. The micro-scale

carbon fibres are arranged in one direction in this CFRP type. An electronic scanning

magnification of this CFRP type is shown in Figure 2.34. The scanning electron

microscope enlarged the image in this figure 150 times to reveal the arrangement of

fibre.

Literature review

43

Figure 2.33 Representation of CFRP materials [ Reproduced from Nanni (2004)]

Figure 2.34 Scanning Electron Microscope (SEM) image of CFRP fabric

2.3.2 Fibre types

Glass fibre reinforced polymer (GFRP), aramid fibre reinforced polymer (AFRP) and

carbon fibre reinforced polymer (CFRP) are the major types commonly used in civil

engineering applications. They are usually employed in civil structures in the form of

(CEB-FIP Bulletin 14 2001):

Unidirectional fibre strips prepared by pultrusion.

Flexible fabric sheets prepared with uni- or multi-directional fabrics.

Chapter Two

44

Typical ranges of FRP properties and static strengths are given in Tables 2.1 and 2.2.

Glass fibres can be formed of E-glass, S-glass and Alkali-Resistant (AR) glass fibres.

The diameters of fibres embedded in the matrix in the glass types range from 5 to 20

µm, whilst aramid fibres are usually around 12 µm in diameter. Carbon fibre diameter

sizes are basically dependent on the manufacturing process of the raw materials, usually

the range 5-18 µm.

Table 2.1 Typical properties of fibres (CEB-FIP Bulletin 14 2001)

Type Elastic

modulus (GPa)

Ultimate tensile

strain (%)

Tensile strength

(MPa)

Carbon high strength 215-235 1.4-2.0 3500-4800

Carbon Ultra high strength 215-235 1.5-2.3 3500-6000

Carbon High modulus 350-500 0.5-0.9 2500-3100

Carbon Ultra high modulus 500-700 0.2-0.4 2100-2400

Glass E 70 3.0-4.5 1900-3000

Glass S 85-90 4.5-5.5 3500-4800

Aramid Low modulus 70-80 4.3-5.0 3500-4100

Aramid High modulus 115-130 2.5-3.5 3500-4000

Table 2.2 Typical mechanical properties of FRP composites (CEB-FIP Bulletin 14 2001)

Type Fibre content (% by weight) Density (kg/m3)

GFRP laminate 50-80 1600-2000

CFRP laminate 65-75 1600-1900

AFRP laminate 60-70 1050-1250

In civil engineering applications, aramid fibres are not used very commonly. For glass

fibre, its durability and resistance to environmental cycles are currently under

Literature review

45

investigation. It is recommended for seismic applications in the construction industry

(Nanni 1999).

Carbon fibres presently have a rich product range, and for that reason their mechanical

properties vary broadly. The most common commercial production form of carbon

fibres is polyacrylonitrile (PAN) based fibre technology (Hearle 2001). Pitch and

vapour-grown fibre forms of carbon also show promise for mass commercial

production. However, carbon fibres of the PAN type provide better performance and

have higher strength.

Generally, carbon fibres are the most expensive type (Nanni 1999) compared with glass

and aramid fibres. Carbon fibre has high strength, exceeding 10 times of steel

reinforcement in typical constructions. Apart from their strength, carbon fibre products

can contend with severe environmental condition and high resistance to acid and/or

alkali attack (Teng, Chen, Smith and L. 2002). For all these reasons, carbon fibre

reinforced polymer fabrics and laminates were chosen for use in this study.

2.3.3 Types of polymer resin matrices

Two different types of matrices can be used in FRP composite systems; the

thermosetting type or thermoplastic type. However, thermosetting is the most

commonly used type (CEB-FIP Bulletin 14 2001). Epoxy resin, vinylester, and

polyester are the main thermosetting matrices. FRP composite system performance is

significantly influenced by the physical and chemical properties of the matrix. In CFRP

systems, polymeric resins are the most common adhesive used as a matrix and in

bonding between the CFRP fabric sheet and/or laminate and the substrate structures.

2.3.4 CFRP systems for retrofitting civil engineering applications

2.3.4.1 Installation

The installation of the FRP systems varies with the applied application. There are

several FRP installations in engineering structures. The most common systems are wet

lay-up systems using fabric or tapes, pre-preg fabric or tapes, procured jackets, resin

Chapter Two

46

infusion, and fibre strips prepared by pultrusion. Figure 2.35 shows different ways of

applying different FRP composites for strengthening different structural elements. The

lay-up installation process is carried out by wrapping fibre tow or tape manually around

the structural member to be strengthened, followed by wet bath/spray resin

impregnation in place using rollers and/or squeegees. This approach is common in

CFRP installation because it can be applied to different member shapes, and is

economical (Karbhari and Seible 1999). However, because the bond forces are

developing simultaneously with the FRP installation, the homogeneity of the system can

vary and defects such as air voids can occur due to improper installation.

Laminates pre-preg (or prefabricated strips) have the same installation principles as the

wet lay-up method. They typically are in the form of resin-pre-impregnated fibre sheets,

which minimize installation defects.

Figure 2.35 The main FRP installation systems for rehabilitated structural members

The procured jackets are first fabricated and then externally bonded in the field. This

installation is adequate for column strengthening. However, the manufacture of these

jackets requires critical adhesive quality control.

Installation by resin infusion consists of the application of dry fibres to the area of the

structure to be strengthened, and vacuum pressure is then applied to infuse the resin.

The advantages of this approach are that the infusing resin will be uniform across the

Procured column jacketing Wet layup warrping Prepregs wall strengthening

Literature review

47

section and there is no room for any air voids to be generated. Moreover, the cracks in

the member can be filled with the pressurized resin.

Pultruded FRP manufactured at a factory is externally bonded to the structure on-site in

sections. Laminates and rods are the FRP pultruded strengthening components most

commonly used in structural elements.

2.3.4.2 CFRP applications

The properties of advanced CFRP composite materials enable different products to be

used in different civil engineering strengthening applications. According to the ACI 440

committee (ACI Committee 440 2008), the three major areas of application for CFRP

are:

To enhance the flexural strength of structural members.

To improve the shear capacity of members.

To increase concrete structure durability by providing additional confinement.

The CFRP fabric or/and laminate is usually attached externally to the tension face for

flexural strengthening purposes. For shear enhancement, CFRP materials may be used

to wrap the structural element web along its axis. The improvement of structural

member durability is usually recommended in active seismic areas and CFRP material is

used to confine the concrete which increases the durability. Column wrapping with

CFRP fabric is a common method for this application. Fibre direction must be designed

carefully in all applications and for specific purposes of flexural, shear and column

wrapping to achieve the desired additional strength.

The entire CFRP strengthening system is dependent on the bonding quality between the

CFRP and the substrate structure. For that reason, bonding is considered a crucially

important factor and it should be monitored, evaluated and repaired to achieve the

requirements of the strengthening process. Bonding defects generally occur due to

improper CFRP composite application, delamination and crack development. These

bond defects can reduce the compatibility, durability and integrity of the strengthened

Chapter Two

48

structure and the system may not work as desired. Previous studies have addressed the

inspection of these defects by using different methods of non-destructive testing (NDT).

Most of these studies have attempted to determine a reliable method to identify and

detect bond defects and delamination. IRT has promising potential to detect debonded

areas of composite systems at the CFRP/concrete interface.

2.4 Literature review of inspection of FRP bond defects by IRT

A review of previous experimental and theoretical studies into the use of IR non-

destructive methods to test composite FRP systems attached to concrete structures is

presented in this section. Most previous researchers have attempted to investigate the

effectiveness of the IRT as a non-destructive test to detect FRP-concrete structure

defects. However, experimental studies are still needed to have in-depth understanding

of different parameters. Table 2.3 summarizes the different parameters of the previous

studies highlighted in the present thesis.

Table 2.3 Summary of parameters studied in FRP-strengthened structures by IRT

Studied Parameters

(Hu,

Shi

h, D

elpa

k an

d Ta

nn

2002

)

(Lev

ar a

nd H

amilt

on 2

003)

(Hal

abe,

Vas

udev

an,

Gan

gaR

ao, K

linkh

acho

rn a

nd

Shiv

es 2

003)

(Sta

rnes

200

2; S

tarn

es, C

arin

o an

d K

ause

l 200

3)

(Bro

wn,

J. R

. and

Ham

ilton

, H.

R. 2

004;

Bro

wn,

Jeff

R. a

nd

Ham

ilton

, H. R

. 200

4)

(Grin

zato

, Tre

ntin

, Bis

on a

nd

Mar

inet

ti 20

07)

(Val

luzz

i, G

rinza

to, P

elle

grin

o an

d M

oden

a 20

09)

CFRP fabric

Mat

eria

ls

Para

met

ers

CFRP laminate

GFRP composite E-Class

Numbers of layers Cracked section

Test

con

figur

atio

n

Different NDT Under-loading

Excitation system L Q HL,K HL H,IRL A HL

Passive approach PTT approach

Literature review

49

LTT Heat Flux sensors

IR test at different distances Using shutter

Numerical simulation Noise analysis/control

Excitation Systems: Air blower (A), halogen lamps (H), heating lamps (HL), IR lamps (IRL), kerosene

heaters (K), light bulbs (L), quartz heaters (Q)

An investigation of artificial debonded areas between the bond-line of CFRP laminate

with concrete was conducted by Hu, Shih et al (2002). A small mock-up 500 mm × 100

mm concrete strip was constructed to test the ability of the IR technique to detect

artificial unbonded areas. These artificial air-voids were embedded blisters with

different sizes of 16 mm, 18 mm, 20 mm and 30 mm. A thermographic Thermovision

900 camera system with resolution of 0.1 oC was used to detect these blisters from

different distances up to a maximum of 20 m. The thermal test was conducted one week

after the application of the CFRP laminate on the concrete to allow sufficient time for

curing. The investigators used an active thermographic approach (ATA) for the

acquisition of the thermal images, which needed external thermal perturbation in order

to stimulate thermal distribution. Radiant heat (powerful light bulbs) and electrical

resistance heating elements were attached to the bonded FRP. Areas lacking epoxy were

clearly indicated by the IRT. The researchers concluded that if the distance between the

camera and the object is known, the size of the blister can be estimated.

These researchers also tested the ability of the thermal test to predict crack instigation

and propagation in a 100 mm × 200 mm ×1200 mm reinforced concrete beam at an

early stage of failure. The beam was reinforced with three T10 mm tension bars. A two-

part epoxy was used to apply the fibre glass (GFRP) laminate. The loading test was set

up with 3 points to load the beam to the ultimate level. The setting of the static load was

about 20 % of the load peak-to-peak amplitude. Frequency of 3 Hz was adapted for the

vibration ode. The beam was continuously applied during static and cyclic loading.

After the end of each phase (static and cyclic) the displacements at the centre of the

Chapter Two

50

beam were collected. The thermal sensitivity used in this part of the study was about

0.02 oC with an accuracy of ± 0.1 oC, ± 1%.

With the intention of identifying potential failure areas during the different stages,

thermographic monitoring was employed and series of thermal images were captured.

For this stage a passive thermographic approach (PTA) was chosen, so there was no

need for the use of additional thermal stimulation. Hu et al. (2002) concluded that the

potential failure planes can be identified, depending on the dissipated energy due to the

cyclic loading effect.

Research by Levar and Hamilton (2003) involved IRT inspection of a CFRP system

applied to reinforced concrete beams. Four reinforced concrete beams 102 mm × 305

mm × 4900 mm strengthened with CFRP in different layouts were tested in shear and

flexural modes. The CFRP strengthening designs varied from single strip to 50 % U-

shape wrap for the fabric CFRP and single strip CFRP laminate. Loading in four-point

bending was carried out for the flexural specimens, whilst single point testing was

loaded in the shear test with shorter spans to guarantee diagonal cracking and failure in

shear mode. The tests in both flexural and shear modes were prepared so that the

flexural tension face was oriented upward to render infra-red examination more

accessible and convenient. IR inspection was conducted before the tests and at different

loading stages with instrumentation for collection loading deflection, including two 44.5

kN load cells, dial gauges and multimeters to determine the reactions and the output

data. The thermal package consisted of an infra-red camera, infra-red thermometer, 8

mm VHS camcorder, and television connected to the IR package. The infra-red camera

was utilized to capture IR images during the tests, and at the same time an infra-red

thermometer was used to acquire surface temperature readings in order to scale the

results. To obtain the best selection of images, the infra-red images were recorded with

a VHS camera.

The researchers chose the areas with the maximum moment for examination by infra-

red inspection during the flexural tests. Heat was applied by using a 500 W lamp at a

distance of 152 mm from the surface. The heating time was about 15 s to 20 s, then

Literature review

51

temperatures were immediately recorded by the infra-red thermometer. IR images were

acquired directly after removing the heating sources to detect the unbonded/debonded

areas between the CFRP and the concrete. This process was conducted during the

loading at 60 %, 80 % and 100 % of the designed load. The same IR inspection was

carried out on the samples before the flexural test to identify existing defects.

The shear tests were focused on the area of the beam located within the three point load.

The same infra-red thermal detection procedure was used as that conducted in the

flexural tests was used. However, the stages of loading at which thermal images were

acquired were 25 %, 50 %, and 75 % of the maximum load. This maximum load was

designed to be above the calculated capacity in these shear tests due to CFRP bond

strength variability within the host structure (Levar and Hamilton 2003). Moreover,

thermal images were acquired for the beam during the unloading period between each

two loading steps.

For the laminate CFRP the researchers used a 79 MJ (75000 BTU) kerosene heater to

discover if there were major changes in the detection results. The study showed that the

boundaries of the unbonded and damaged areas have the same measurements as in the

flexural test. There was only one test in which the failure mode was debonding. All

other tests failed with rupture in CFRP, shear or even crushing in concrete. However, in

this study there was no adequate design for the specimens to ensure or control failure

mode. The experiments attempted to address IR inspection only.

Infra-red detection identified the loss of bond between the CFRP and the concrete with

load increase in both flexural and shear testing; however, the shear test specimens

revealed a great deal of delamination and debond which were diagnosed as being due to

the shortage of shear reinforcements in the beams, which allowed heavy cracks to occur.

Generally the unbonded areas grew rather than developed a new area between the CFRP

(fabric and laminate) and the concrete.

One of the approaches used in this research to verify the ability of IR thermographic

cameras to detect defects was the construction and testing of several mock-ups with

Chapter Two

52

known unbonded areas. Differences in the thickness of epoxy layers lead to slightly

different surface temperatures being recorded in the thermal images. The unbonded

areas were examined by IR inspection before the epoxy reached full cure stage.

In addition, acoustic sounding was used in parallel with IR thermography to verify the

results of thermographic inspection. The acoustic sounding inspection was carried out

by providing an impact on the specimen surface while the inspector listened for hollow

sounds. However, the study illustrated that 20 % to 30 % of the defects detected with IR

inspection were undetectable using acoustic sounding. The study concluded that

acoustic sounding is inadequate for detecting small irregular voids. Control tests were

also carried out on beams that were not strengthened with CFRP.

Levar and Hamilton (2003) used different heat resources to create the temperature

differential as the thermal process proceeded, and found that the most efficient heat

source for the indoor testing of the CFRP system was the quartz lamp. The study

showed that the best indoor ambient temperature for a thermography test should be

below 23.9 oC and heating for the target surface should be between 35oC and 43.3 oC,

using a 500 W lamp positioned at 152 mm from the surface. Significantly, the

researchers attempted to go a further step by using the IR thermography inspection test

and by trying to locate and track flexural cracks under loading. However, crack

enlargement was undetectable during the load testing.

In their laboratory experiments, Halabe et al. (2003) explored a glass fibre reinforced

polymer (GFRP) bridge deck specimen using digital infra-red thermography. The size

of the bridge deck module was 600 mm × 300mm. Two subsurface debonded defects 75

mm × 75 mm were embedded at the top surface during the casting of this bridge deck

specimen. These defects were prepared by joining two polypropylene sheets with an

enclosed air pocket between them. The thickness between these two sheets was around

1.5 mm. FRP was then applied with a 9.5 mm thickness covering the whole surface. A

Thermal cam S60 FLIR camera system was used in the investigation. The specimen was

subjected to a quartz tower heater for a few minutes. Thermal images were acquired

after the tower heater was removed.

Literature review

53

The MATLAB software image processer was used to enhance the contrast of the

thermal images and to increase the ability to identify the debonding area precisely. A

series of image and reference subtraction were adopted to decrease the noise from the

thermal images. Filtration was also used on the thermal images. The researchers

reported that the infra-red thermographic camera can detect artificial debonded areas

and the image processing that was used increased the sensitivity of the infra-red thermal

performance.

Starnes and co-researchers (Starnes 2002; Starnes, Carino and Kausel 2003) studied the

basic parameters that might affect the IR image results. They performed experimental

and finite-element studies of controlled-flaw specimens. A concrete specimen of 610

mm × 250 mm× 45 mm was constructed with two CFRP laminates 609 mm ×102 mm×

1.3 mm applied on the top surface. Eight artificial defects were implanted at the bond

interface. The size of each defect was 25 mm × 25 mm. Different materials and

thicknesses were used to imitate these flaws. The aim of using different materials in

this study was to test if any material can imitate the air void. Two thermocouples and a

heat flux transducer with an internal thermocouple were also implanted and connected

to a data acquisition system. Two 250 W IR heating lamps were installed at a distance

of 33 cm from the target surface. The researchers used a lower intensity heat flux with

longer heating period to introduce the balance between the surface maximum

temperature and the thermography signal. To prevent radiation from the lamps after

they were turned off, an aluminum shutter was used. An electrical trigger controlled the

shutter, and turned off the lamps at the end of the heating period. The heating was also

measured to ensure homogeneous distribution of the heat. A nitrogen-cooled mercury

cadmium telluride (HgCdTe) detector with sensitivity of 0.08 oC and accuracy of ± 1 oC

was used with the IR camera which was connected to the data acquisition system. Real

time software was utilized to analyze the temperature on the target surface. The

researchers depended on ASTM standards (ASTM E 1316 2001) and (ASTM E1933-

99a(2005)e1 2007) to determine emissivity and to describe the thermometer contact

method. The temperature on the FRP laminate surface was recorded using

copper/constantan thermocouple 0.01 mm in diameter. A shallow groove was cut so that

Chapter Two

54

the thermocouple was implanted with epoxy resin in the FRP laminate surface.

Consistent with ASTM E1933 (ASTM E1933-99a(2005)e1 2007) the surface of the

specimen was heated to 10 oC higher than the temperature of the ambient. The research

presents a preliminary assessment of testing and analytical procedures that will aid the

development of a standard method of IR NDT for FRP systems bonded to concrete.

In the finite element program, Starnes (2002) studied different parameters that might

affect the thermal response. Both single and multi- parametric studies were performed.

Defect depth, size and CFRP properties were studied as parameters. The researcher

simulated and studied only CFRP laminate. ANSYS 5.6 was used to simulate the finite

element 2D-model, and some finite element analyses were performed on 3D-model. The

model was simplified by taking half of the 2-dimensional model for analysis and

assuming symmetry around the defect location. Pulses with very high heat flux

intensities (100,000 W/m2) were used in the input thermal loadings which are very hard

to supply in the experimental field IRT testing. The use of FRP laminate material only

and the very high pulse intensity are the major drawbacks of this study.

Brown and Hamilton (2004) conducted a study of six full-scale AASHTO girders by

infra-red thermography NDT to explore the performance of bonded CFRP used to

alleviate vehicle impact damage, and whether this strengthening system could regain the

capacity of a damaged girder to its original strength. Figure 2.36 illustrates the

dimensions of loading set-up for these girders.

Figure 2.36 AASHTO Type II girder and load test set-up (Brown, J. R. and Hamilton,

H. R. 2004)

Literature review

55

Only one girder was tested to failure in an undamaged condition, and the other five had

simulated vehicle impact damage. The damage was imitated by removing a small

section of concrete at the girder’s mid-span and cutting four pre-stressing tendons. The

FRP systems were applied to strengthen these girders and to restore the flexural

capacity loss introduced by the cutting of the prestressing strands. Four different FRP

composite strengthening systems were applied by the wet lay-up method. The number

of layers of these systems was between 1 and 4, and a combination of fibres and

matrices were used. Carbon and E-glass were used for the strengthening FRP. For the

matrix epoxy, polyurethane and polyester resin were applied. Loadings to failure stage

were carried out for these strengthened girders with IR monitoring during the loading to

identify if there were any installation bonding defects, to monitor their expansion, and at

the same time to observe if any new debonded areas developed. A FLIR Thermal Cam

PM 695 infra-red camera was used for this purpose. A 500 W halogen lamp and 125 W

infra-red heating lamps were utilized as excitation sources. A rolling cart driven at 20

mm/s corresponding to the girder was employed with the IR camera to make access to

the tension face more convenient. The heating source stood on the same cart at a

distance of 76 mm from the FRP external surface. The position of the heating source

was designed so that the thermal images were collected immediately after the area had

been heated. The IR thermography test detected a number of defects with different

sizes up to 3000 mm2. The comparison between the thermal images before the loading

test and after failure showed that no change in the size of the defects was detected

before the loading. At the same time, no new debonded areas developed under loading.

The effect of FRP system thickness on the ability to detect surface defects by using IR

thermography testing was studied in a more controlled laboratory setting. This part of

the research was achieved by constructing five 305 mm × 305 mm × 51 mm concrete

block specimens. Various sizes of artificial holes were drilled and then filled with

materials that had different thermal conductivity factors than the thermal conductivity of

the concrete. The diameter of the holes varied from 10 mm to 51 mm and the depth

ranged from 6 mm to 25 mm. The filler materials were steel, PVC, wood, silicone,

insulating foam and epoxy. Some of the holes were left empty to simulate an air void.

Chapter Two

56

An FRP composite of the size of 254 mm × 254 mm was applied to the prepared

surfaces of the specimens. The FRP system also varied in these specimens. A single

layer of carbon fibre was used in Specimens 1 and 2 while three and four layers of

carbon fibre were applied to Specimens 3 and 4 respectively. Specimen 5 was covered

with 9 layers of multi-directional chopped E-glass mat. A halogen lamp of 500 W

provided heat for each specimen. The distance from the investigated surface and the

heating source was 280 mm. The thermal camera saved images at the rate of one

frame/s from a distance of 910 mm from the FRP surface.

The series of thermal images were analyzed later and subtracted from the first image to

remove the reflection of the heat source detected by the IR thermal camera. The heating

times needed to recognize the implanted defects varied considerably. The defect signal

strength, ΔTdefect, was estimated by (ΔTdefect = Tdefect – Tbackground). The largest epoxy

defect implanted needed around 180 s of heating time to emit a Tdefect of 3 oC, while the

foam insulation defect needed only 10 s to develop a Tdefect of more than 5 oC. Other

heating times were considered, but detection did not take more than 240 s for all the

defect types.

The research showed that IR inspection can be used to locate defects in CFRP

containing a single layer of fibre. The experiments demonstrated the influence of the

fibre and matrix type and the thickness of the FRP layer on the ability of the thermal

camera to indicate and locate surface defects. However, this study did not improve the

reliability of the acquired thermal images and the confidence to use the IR

thermography technique to indicate surface defects, because the thermographic scanning

procedure used in this study was insufficient since the IR camera was not in position to

record images when the maximum thermal signal was being produced (Brown, J. R. and

Hamilton, H. R. 2004). At the same time, the comparison between the thermographic

images acquired in the single system and those in the multi-layer FRP composite system

needed extra work because the defect signal strength and the time to maximum signal

varied considerably between these two different systems. In addition, the researchers

indicated the capability of IR thermography to detect implanted defects in small-scale

specimens under multi-layer FRP composite systems.

Literature review

57

Brown and Hamilton (2004) performed another thermographic tests on multi-layer FRP

composite bonded to concrete. Three specimens 305 mm × 305 mm × 51 mm were

constructed and 25.4 mm × 25.4 mm of FRP was applied to the top surface. The same

five holes were drilled in the concrete surface, however this time the entire holes were

filled with a thickened epoxy paste (1:2 epoxy/cabosil by volume). The first specimen

consisted of 9 layers of multi-directional E-Glass/polyester resin. A three-layer

unidirectional carbon/epoxy specimen was used in specimen 2; and a single-layer

unidirectional carbon/epoxy specimen was used in the last specimen. An additional two

holes were drilled from the rear of the specimens. The diameters of these two holes

were 95 mm and 38 mm. The 95 mm hole was drilled first along the concrete thickness

up to the FRP system. A fractured plane was generated at the interface of the FRP

system and the concrete through the first hole by applying loads inside it to push the

FRP system away from the concrete. The noise was a good indication of adequate

separation at the bonded line. The same route was followed in the second hole but with

2 mm less depth than the first hole. The final defects were implanted by placing three 25

mm× 25 mm square patches of masking tape on the concrete with thicknesses ranging

from 0.5 mm to 1.25 mm.

A sensitive IR camera (FLIR PM696 with SC2000 upgrade) collected the thermal

images with single phase images for each modulation frequency. The minimum image

save rate used was 0.08 frames per second and the maximum was 2 frames per second.

The experiments were performed in long-pulse heating and modulated heating by using

full power 500 W Halogen lamps. The heating time that was required to specify the

artificial defects was approximately 180 s.

The researchers used modulated heating as another procedure for heating the

experiments. Figure 2.37 shows the test setup for both long-pulse and modulated

(lockin) heating experiments.

Chapter Two

58

Figure 2.37 Test set-ups for long-pulse and modulated (lockin) heating (Brown, Jeff R.

and Hamilton, H. R. 2004)

To control the two 500 W halogen lamps, a four-channel analog dimmer was used in the

modulated heating experiments. Lab View software with a laptop computer was used to

control the input signal. Each frequency was applied in a signal modulation cycle. Two

to ten seconds cooling period separated each modulation cycle. Equations and curves to

transform the thermal images in the time domain into a single phase image were

established after the thermograms/modulation frequencies were acquired. Non-uniform

heating effects on image quality were enhanced by these results. However, discernibility

of the implanted defects was found to be difficult for the deeper defects, especially

when the defects were small in size. The defects became more detectable when the

specimens moved the cooling stage. In general, the series of thermal images gave

valuable figures about all the implanted defects. This study also indicated that the high

frequencies distinguished only the shallow defects, while the deeper defects can be

revealed at lower frequencies. However, no more than one experiment was conducted

for each frequency.

Another important study of IR thermography inspection for improper installation of

CFRP and bond defects was performed by Grinzato et al. (2007). Experiments were

conducted both on preliminary and full-scale samples. A mathematical simulation was

developed for different conditions with numerical method simulation for the pulsed

thermography and modulated tests. The depths of the defects were simulated differently

Literature review

59

to gain better understanding. Two preliminary reduced-scale concrete plates 400 mm×

400 mm× 50mm were strengthened with CFRP laminate of 1.2 mm thickness. The

specimens were constructed with fabricated defects implanted under the resin layer with

different sizes, depths and conductivity factors. To create these fabricated defects and

imitate air gaps, Teflon material was used. 30 μm thickness and 10 mm wide, Teflon

strips were applied with lengths of 1 mm, 2.5 mm, and 5 mm. Two overlapping layers

of Teflon strips 10 mm wide and 1 mm, 2.5 mm, and 5 mm long were used for the

central strip. Square nylon patches of 2.5 mm × 2.5 mm and 100 μm thickness were

adhered to the samples with silicon grease. Thermal images were acquired after one

month to detect the defects by using pulse phase thermography (PPT) with different

heating periods. The study demonstrated that IRT method has the ability to reveal

delamination up to 1 cm2.

In the second phase of this study, two full-scale beams 30 mm × 50 mm × 10000 mm

strengthened with CFRP laminates of 1.2 mm thickness were subjected to

thermographic analysis. The thermal images were collected before and during the

loading bending tests. The beams were reinforced using ordinary and pre-stressed

reinforcement bars and strands. Scanning heating and a thermal recording camera

moved parallel to the beam’s axis during a bending test to track the CFRP detached

surface. A 2 kW linear hot air blower was used as a heat source. A mirror was attached

with a sliding support side-by-side with the heat source and the IR camera to record the

thermal images on the facedown tension beam intrados, exactly where the CFRP

laminate was applied. At each diagnosed debonding area a series of thermal images

were collected at 1 Hz for 120 s after a special hot air gun was manually applied to the

area. The thermal images showed that the largest defects were located at 1 m from the

beam mid-span. The research revealed that debonding occurred progressively, starting

from the edges due to CFRP shrinkage.

Valluzzi and his group of researchers analyzed the interface of pre-tensioned CFRP

laminates externally bonded to reinforced concrete beams by IR thermography NDT

(Valluzzi, Grinzato, Pellegrino and Modena 2009). The interface quality between

laminates and the strengthened substrate was assessed before loading and under loading.

Chapter Two

60

Preliminary thermographic testing was conducted on two concrete reduced samples 400

mm× 400 mm× 50 mm strengthened with CFRP strips. Artificial defects were

implanted at the interface surface of the CFRP strips. These defects differed in material,

location and depth; some were at the interface between CFRP and resin while others

were at the resin-concrete line. Teflon, silicon and packaging nylon were used in

different sizes. Shapes of 20 mm × 50 mm, 20 mm × 30 mm, 20 mm× 20 mm, 20 mm ×

25 mm and 10 mm × 10 mm were located for these defects. The thickness varied from

30 μm to 100 μm.

A FLIR ThermaCAM SC3000 thermographic camera was used to perform the

thermography test. Principal Component Analysis (PCA), PPT and Thermal

Tomography (TT) algorithms were selected to detect the surface defects. These

algorithms showed considerably different analyses in the central areas of the samples’

rough surfaces. However the study recommended PCA as the most appropriate process

to detect defects for in-field analysis.

On the full scale samples, two beams 300 mm × 500 mm × 10000 mm were tested

under binding loading. The beams were strengthened with CFRP laminate (1.2 mm

thick, 80 mm wide) at the tension beam face. The laminates were applied with the ends

inserted in the slots of the anchoring plates. One sliding and one fixed end were located

at the beam ends. By using a hydraulic jack, the CFRP laminates were pre-tensioned.

When the tension in the laminates reached the desired level, the bolts of the sliding

plates were tightened.

Thermal images were captured before the loading test and at 67 % of the ultimate load,

and finally when the test reached its failure stage at 155 kN and 206 kN for the two

beams respectively. The laminates suffered from large scale deformation at the failure

stage. The sudden debonding and delaminations were correlated to sliding of the FRP at

the anchored ends. The thermographic images revealed that thermography is an

efficient method to distinguish actual and potential weak or debonding areas at the bond

line. The study illustrated that debonding enlargement can be recognized during

loading.

Literature review

61

An investigation was carried out by Brown and Hamilton (2010) on the use of IR on

applied concrete. Twenty- seven specimens were constructed using CFRP and GFRP

with different resin thickness. The IR was performed by halogen lamps for 60 s. Step

heating thermography was applied in this study. The heating was applied in

homogenous distribution to reduce the effects of non-uniform heating. Quantitative

single pixel analysis was performed on the acquired thermal images The study showed

that the heating has a considerable effect with regard to basic detection.

2.5 Summary

Its superior properties have led to the use of CFRP for many civil engineering

applications. Rehabilitation and renovation of existing structures is one of the

significant civil engineering areas in which the benefits of CFRP features can be

applied. Externally-bonded CFRP reinforcement, fabrics, and laminates are widely used

for strengthening concrete and masonry structures. To guarantee the overall structural

performance of the strengthened member, it is important that the appropriate FRP

strengthening system is fully bonded to the structural sub-system. Bonding defects due

to improper CFRP installation, delamination or the development of cracks can reduce

the capability of the composite CFRP system and the entire system may not perform as

designed. CFRP composites in civil engineering are installed manually in field

environments. Although IRT NDT has been used increasingly in the last few years to

detect areas of unbond/debonding between the CFRP and the substrate structures, to

date, standard procedures for the evaluation of the compatibility of this strengthening

system still need more investigation. Work is needed to test in-depth its effectiveness

and accuracy. Moreover, investigation of the ability of IRT testing to explore the

development and enlargement of defect areas in CFRP composite systems is required

for verification purposes. Little effort has been made up to date to investigate bond

defects under multi layers of CFRP. Delamination size, location, and quality need to be

detected more accurately relative to the overall area of the structure (ACI Committee

440 2008). Very few studies have been conducted on fine crack detection and the

measurement of cracks in the substrate structure beneath CFRP composites. Errors of

IRT have not been comprehensively considered in previous research. Action to

Chapter Two

62

minimize reflection error in IR results has been rarely considered in the majority of the

reviewed studies. Different studies have investigated defects by filling them with

silicon, sand and air. However, to the knowledge of the author, none of the previous

studies have taken account of the presence of water within the bond defect area. The

investigation of the effect of the presence of water in defect on the thermal response is

required.

The CFRP materials industry is developing fast. More products have become available

recently, which makes the study of the effect of changes in CFRP thermal properties

essential. For that reason, analytical finite element simulations are required to

investigate the effect of using different new CFRP products and how the change in these

material thermal properties can influence the detectability of thermal responses.

Qualitative IRT experimental laboratory program

63

3 CHAPTER THREE: QUALITATIVE INFRA-RED

THERMOGRAPHY EXPERIMENTAL LABORATORY

PROGRAM

3.1 Introduction

As indicated in Chapter Two, although IR thermography has been used in the last few

years, more work is needed to test the effectiveness of this method in providing

consistent and reliable results (ACI Committee 440 2008) with different defect sizes and

different CFRP strengthening applications.

The experimental laboratory program in this study focused on two main infra-red

approaches. The first dealt with qualitative infra-red thermography non-destructive

tests, while the other concentrated on a quantitative approach to IRT NDT. Each

approach involved a number of IRT NDT.

The experimental tests reported in this chapter was focused only on using qualitative

IRT NDT to detect and identify different bond defects and cracks and investigate the

presence of water within the defect area.

FLIR B200 infra-red detector was used to conduct the qualitative NDT for different

CFRP-composite systems applied externally to concrete and steel specimens. Passive

and active IRT techniques were applied to specimens strengthened with single and

multi-layer CFRP fabrics and laminates. Different defects were fabricated within the

bond zone of the CFRP and the host structure and between the different CFRP

composite layers.

3.2 Design of specimens

Twenty - seven concrete specimens 300 mm ×300 mm × 50 mm and five steel

specimens with dimensions 300 mm ×300 mm × 3 mm were constructed for the

Chapter Three

64

experimental program. Different CFRP fabrics and laminate designs were attached

externally to the prepared surfaces of these specimens.

3.2.1 Concrete specimens

The concrete specimens were 24 plain concrete and 3 reinforced concrete specimens

with dimensions of 300 mm ×300 mm × 50 mm. The mix design proportions are

presented in Table 3.1. Wooden mould frames were used, as shown in Figure 3.1. The

cure duration of the concrete was about 7 days, and the average strength of the concrete

was 65 MPa.

Table 3.1 Proportions of the concrete mix design

Material Quantity

Water / Cement ratio 0.3

Water 5 kg

Cement 19.25 kg

Coarse Aggregate 46.9 kg

Fine Aggregate 18.2 kg

Figure 3.1 Moulding the concrete

Qualitative IRT experimental laboratory program

65

Before applying the CFRP, the surface of the substrate structure was prepared to

provide the best surface conditions for bonding. As the bond plays a major role in the

CFRP strengthening system, careful surface preparation was applied to each specimen

to provide the best installation process without any loose material on the surfaces of

interest. Water and sand-blasting were used for surface preparation as they are the most

common methods of surface preparation before the application of the epoxy, as shown

in Figure 3.2. Two concrete specimens’ surfaces were prepared using a very rough

process to study the influence of surface preparation on the IRT results. Figure 3.2d

illustrates one of the specimens with intense surface blasting.

(a) (b)

(c) (d)

Figure 3.2 Concrete specimen surfaces prepared by: (a) water blasting, (b) surface water blasting, (c) sand blasting, (d) rough surface

Three reinforced concrete specimens were constructed to study crack detection. A mesh

of 6 mm bars at 60 mm spacing was used as reinforcement for these specimens. Each

Chapter Three

66

specimen was loaded with a three-point load flexural test to generate cracks on its

tension surface, as shown in Figure 3.3.

Figure 3.3 Three-point load testing of cracked specimen

3.2.2 Steel specimens

Five steel specimens 300 mm ×300 mm × 3 mm were investigated in this study. All

steel specimens were prepared using the sand blasting method. Figure 3.4 reveals the

prepared steel specimen’s surface before applying the CFRP system. The steel plate

thickness was 3 mm to allow the application of the transmission IR observation method,

as in the case of thick steel sections, this observation method IR will usually show poor

detectability results. No cracks were inserted or generated on the steel specimens'

surfaces, and only unbonding and debonding defects were investigated.

Qualitative IRT experimental laboratory program

67

Figure 3.4 Steel specimen prepared surface

3.2.3 CFRP fabric

Three carbon Fibre (CF) fabric types were used in this study: unidirectional wave

MBrace CF 130, CF 140 and TYFO BCC bidirectional ± 45 degree waves. Figure 3.5

illustrates the two fabric patterns the strengthening CFRP fabric systems. In this

research study, all of the unidirectional CFRP fabrics and laminate products and resins

were supplied by BASF Construction Chemicals Pacific- Australia (BASF 2012a). The

bi-directional fabric was provided by Fyfe Co. LLC (2011). The CFRP fabric

mechanical properties are provided in Table 3.2. The wet lay-up method was employed

in the application of the three CFRP fabric types.

(a) (b)

Figure 3.5 Schematic of CFRP fabric waves, (a) Uni-directional wave, and (b) Bi-directional ± 45 degree waves (Hearle 2001)

Chapter Three

68

Table 3.2 CFRP fabric properties (BASF 2011a), (Varat 2011), (Fyfe-Co. LLC 2011)

Materials

Properties Te

nsile

St

reng

th (G

Pa)

Tens

ile

Mod

ulus

(G

Pa)

Ulti

mat

e El

onga

tion

(%)

Den

sity

(g

/cm

3 )

Wei

ght (

g/m

2 )

Ther

mal

C

ondu

ctiv

ity

(W/m

.o C)

Thic

knes

s (m

m)

MBrace

CF 130

CF 140

4.9 230 1.55 1.76

300

400

9.38

0.176

0.235

TYFO

BCC (±

45o)

3.79 230 2.1 1.8 607

9.38 0.55

3.2.3.1 Wet lay-up process

The wet lay-up system was selected for the CFRP fabric application. The MBrace wet

lay-up system is achieved by following of a number of steps (BASF 2012b). First, all

specimen surfaces were ensured to be spall-free. All concrete and steel surfaces were

then cleaned to remove any dust, oil, and grease. The wet lay-up method was carried out

by inserting the CFRP fabric sheet between two layers of epoxy. MBrace adhesive,

primer and resin saturant were used as epoxy materials in the application of the CFRP to

the substrate structures. Table 3.3 summarizes the properties of the epoxy materials

utilized in attaching the CFRP fabric to concrete and steel specimens.

Qualitative IRT experimental laboratory program

69

Table 3.3 Epoxy manufacturers; material properties (BASF 2012a), (Huntsman Advanced Materials 2011)

Mat

eria

ls

Properties

Res

in T

ype

Spec

ific

Gra

vity

Subs

trate

mat

eria

l

Mod

ulus

of E

last

icity

(GPa

)

Com

pres

sive

Stre

ngth

(MPa

)

Num

ber o

f co

mpo

nent

(Mix

ratio

)

Col

or

Flex

ural

Stre

ngth

(MPa

) Full Cure at

(days)

25 o

C

40 o C

MBrace

Saturant Epoxy 1.12 Concrete 3.0 80

2 (3A:1B

by

volume)

Opaque

Grey 120 7 -

MBrace

Primer Epoxy 1.08

Concrete

+ Steel 0.7 -

2 (3A:1B

by

volume)

Transparent 24 0.208 0.125

Araldite

2014 Epoxy 1.2 Steel 4 -

2 (2A:1B

by

volume)

Dark green 61 7 0.167

The first step in this method was to apply the MBrace Primer to the prepared surface

(concrete or steel). The primer is prepared by mixing two components. To minimize air

inclusion, slow speed mixing was followed until a homogenous mix was achieved. A

roller or brush is usually used for the application of the primer. As soon as the primer

layer became tacky, the MBrace saturant was applied. The saturant is also prepared by

mixing two parts. The MBrace fibre was then gently applied with a threaded roller to

squeeze out natural air-voids at the interface. Then, to give enough time for the epoxy

resin to impregnate the fibres the system was allowed to set for 10 minutes (BASF

2012a). The standard procedure to mix and prepare the epoxy in the wet lay-up

installation method for MBrace carbon fibre is shown in Figure 3.6. To ensure that no

resin crossed to the artificial defect areas in specimens, a careful application procedure

was followed. Figure 3.7 demonstrates the standard cross sections of CFRP fabric lay-

up application. However, some sections needed more than one layer of CFRP sheet to

Chapter Three

70

achieve the required strengthening design. In this case a topcoat of MBrace saturant was

applied.

Figure 3.6 Schematic representation of a hand lay-up process

Figure 3.7 MBrace wet lay-up of CFRP fabric (BASF 2011a)

3.2.4 CFRP laminate

The CFRP laminate used in this study was MBrace Laminate 80 mm wide and 1.4 mm

thick. Figure 3.8 shows this CFRP laminate. The MBrace laminate is pultruded carbon

fibre laminate, and it is ready to use as an external strengthening system for structural

elements using MBrace laminate adhesive. Table 3.4 shows the mechanical properties

of the CFRP laminates used in this study. The same MBrace primer used in the wet lay-

up method was applied to the prepared concrete and steel surfaces before the application

of the laminate adhesive. The adhesive also consist of two parts that need to be mixed

first. The adhesive properties when used with CFRP laminates are recorded in Table

3.5.

Part 1

Specimen

Resin apply to the specimen before the installation of CFRP fabric

Threaded roller squeeze out air-void

from interface

Part 2

Resin in two parts mixing by roller

Fabric lay up

Qualitative IRT experimental laboratory program

71

Figure 3.8 MBrace laminate (BASF 2011b)

Table 3.4 CFRP laminate properties (BASF 2011b)

Mat

eria

ls

Properties

Tens

ile S

treng

th (G

Pa)

Tens

ile M

odul

us (G

Pa)

Ulti

mat

e D

efor

mat

ion

(%)

Wid

th (m

m)

Den

sity

(g/c

m3 )

Ther

mal

Con

duct

ivity

(W/m

.K)

Thic

knes

s (m

m)

MBrace

Laminate 2.5 165 1.3 120 1.6

X 7

1.3 Y 0.8

Z 0.8

Chapter Three

72

Table 3.5 Concrete - CFRP laminate adhesive properties M

ater

ials

Properties R

esin

Typ

e

Spec

ific

Gra

vity

Gla

ss T

rans

ition

Te

mpe

ratu

re (o

C)

Mod

ulus

of E

last

icity

(GPa

)

Com

pres

sive

Stre

ngth

(M

Pa)

Num

ber o

f co

mpo

nent

(M

ix ra

tio)

Col

or

Flex

ural

Stre

ngth

(MPa

) Full Cure at (days)

25 o

C

40 o C

MBrace

Laminate

Adhesive

Epoxy 1.5 > 65 10 60 2 (3A:2B

by weight) Red 30 7 3

3.2.4.1 Carbon fibre laminate installation

The two-part laminate adhesive mixed at slow speed by means of a notched steel trowel.

After the mixed adhesive became homogenous, it was applied to substructure surfaces

with thicknesses ranging from 1 to 2 mm. Light pressure was exerted on the MBrace

CFRP laminate attached to the adhesive by using a hard roller until fresh adhesive

exuded from both sides of the CFRP laminate strip. This process was repeated several

times to ensure that any air-voids were squeezed out. The excess adhesive was removed

with cloth rags. The final thickness of the adhesive layer was very hard to control,

however the measured average thickness of this layer was around 1.8 mm. Figure 3.9

illustrates a standard cross-section of MBrace laminate layers applied to concrete

substrate structure.

Qualitative IRT experimental laboratory program

73

Figure 3.9 MBrace wet lay-up of CFRP laminate (BASF 2011b)

3.2.5 Defects in CFRP systems bonded to concrete and steel structures

Most bond defects in concrete and steel structures are due to imperfections in the

installation process of the CFRP system. Poor surface preparation and sharp edges on

the surface can lead to severe bonding fault in the bonding zone. In the long term

environmental degradation can also cause bond defects. The defects presented and

investigated in this research are of five types: unbonded defects, debonded defects,

delaminations, spalls in concrete substrate structure, and cracks in concrete surface.

Unbonded areas are defined as the areas of the CFRP system that were not bonded

adequately during the CFRP installation. Debond faults refer to CFRP areas that were

fully bonded to the structure in the first place, but later the bonding in that specific area

was reduced to un acceptable level. Usually debonding defects occur due to excessive

loading. The absence of bond between the multi-CFRP layers is denoted as

delamination. Impact or excessive loading are the main reasons for this kind of failure.

Spall is a kind of debonding in which the bond does not fail in the bonding zone but the

failure occurs below the concrete surface. This leads to the separation of the CFRP

system with a thin layer of concrete from the whole concrete structure. The concrete-

reinforcement cover is the area where most spall defects happen. Cracks in the concrete

surface can lead to debonding faults in the CFRP-concrete bond region. Generally, spall

and cracks occur due to loading. Figure 3.10 presents the locations of unbonded defects,

debonded defects, delaminations, and spall that can occur in CFRP- concrete structures.

Chapter Three

74

Figure 3.10 Potential bond defects in CFRP-concrete structure

3.2.6 Specimen-CFRP designs

A total of twenty - seven concrete specimens and five steel specimens were constructed

during this experimental program with dimensions of 300 mm ×300 mm × 50 mm for

concrete and 300 mm ×300 mm × 3 mm for steel. Different CFRP fabric and laminate

designs were attached externally to the prepared surfaces of these specimens. Figure

3.11 details all the concrete and steel specimens' design features. As shown in this

figure, Specimen 1 was constructed from concrete material. Single unidirectional CFRP

fabric type CF130 was attached to the prepared surface of this specimen. Three kinds of

unbonded artificial defects were embedded in the bond zone between the concrete and

the CF130 single CFRP layer. CFRP fabric CF140 type was used in Specimen 2 with a

strip-shaped implanted artificial defect. A 70 mm wide unbonded strip located

approximately at the middle of Specimen 2 was inserted, as shown in Figure 3.11-2.

Single CF130 fabric was fully bonded to concrete Specimen 3. An artificial random

debonding fault was created in this specimen by inserting a small wide-headed nail in

the CFRP fabric layer. The nail was then pulled slightly up for 50 minutes until the resin

hardened. The intention was to create a random-shaped debonding area and to

understand how debonding detection in an existing epoxy layer may differ from

unbonding detection. Figures 3.11-3 and 3.12 illustrate Specimen 3 details. A 5 mm

deep groove was cut in Specimen 4 with planar size of 30 mm × 100 mm. The purpose

was to check if the technique is capable of detecting smaller imperfections in concrete

Delamination defectDebond defect Unbond defect

CFRP layersAdhesive

Concrete substrate structure

Spall defects

Reinforcement bars

Crack defect

Qualitative IRT experimental laboratory program

75

substrate. The groove was filled with water during the IR test to investigate the ability

of the technique in detecting a defect containing moisture under CF130 fabric. Figures

3.11-4 and 3.13 illustrate the details of this groove.

Two CFRP laminate strips 80 mm × 300 mm × 1.4 mm were applied to Specimen 5,

one strip with a single layer and the other with double layers of CFRP laminate. Areas

were left unbonded during the resin application between the CFRP laminates and the

concrete. Unbonded areas were implemented with a size of 80 × 70 mm at the middle of

the laminates. Grooves in the concrete surface were also cut before the attachment of

the CFRP laminates. Figures 3.11-5 and 3.14 show Specimen 5 details with the

laminates applied. Two layers of unidirectional CFRP fabric CF140 were used in the

Specimen 6 concrete strengthening system. Unbonded and delamination areas were

used in the designed defects to study the different in bond defects under single and

multiple CFRP sheets of CF140, as shown in Figure 3.11-6. A similar unbond strip was

fabricated in Specimen 7, however, the second CFRP fabric in that specimen was of the

TYFO bi-directional ± 45 degree wave type. The intention of inserting a bond

imperfection defect in this specimen was to observe the ability of IR NDT to detect

defects under a thick combination of CFRP fabric composites. The design of the

unbonded area of Specimen 7 is demonstrated in Figure 3.11-7.

Unbond area was left under double layers of CF140 unidirectional fabric in Specimen 8.

The fabric sheets were attached in a design such that the fibre directions would be

perpendicular to each other, as shown in Figure 3.11-8. A combination of CFRP CF140

fabric and CFRP laminate was utilized in Specimen 9, as shown in Figure 3.11-9. The

unbonded flaw was located under both the fabric and the laminate systems. Two

artificial grooves were cut in Specimen 10 before applying the CFRP to imitate cracks

on the concrete surface. Each groove was 3.6 mm wide and 13.2 mm deep. A single

MBrace CF 130 CFRP strip was attached first to the concrete surface of Specimen 10. A

second layer of MBrace CF 130 CFRP fabric sheet was then bonded to the top of the

first layer with opposite fibre direction. Figure 3.11-10 illustrates the combination of the

FRPs in Specimen 10.

Chapter Three

76

Specimen 11 was a reinforced concrete sample. A mesh of 6 mm bars at 60 mm spacing

was used as reinforcement for this specimen. The specimen was loaded with a three-

point load flexural test to generate cracks on its tension surface. Figure 3.15 reveals the

cracks generated by loading in Specimen 11 before attaching the CFRP fabric. The

specimen’s surface was then strengthened with two single MBrace CF 130 CFRP fabric

strips, as shown in Figure 3.11-11. A fine loading crack was generated in the reinforced

concrete surface of Specimen 12. CFRP CF130 fabric sheet was attached on the cracked

surface with the dimensions shown in Figure 3.11-12. The concrete surface of this

specimen was not prepared by any means before the application of the CFRP fabric in

order to provide a smooth surface to help to detect the very fine crack generated. Two

CFRP bi-directional fabric layers with ± 45 degree wave type were attached to concrete

Specimen 13. Irregularly-shaped bond and delamination defects were inserted between

the concrete and the first CFRP layer and between the first and the second CFRP layers

respectively. Figure 3.11-14 reveals the details of Specimen 14. Cracks were produced

via loading in the concrete surface. Crack widths were generally narrow varying from

0.6 to 1 mm. Single unidirectional CFRP CF130 sheet was attached to that specimen’s

surface.

A combination of MBrace laminate and CF 140 fabric was applied to Specimen 15, as

shown in Figure 3.11-15. CF 140 MBrace fabric sheet was applied first to the

specimen’s concrete surface. The FRP laminates were then attached to the surface of the

concrete above the artificial cracks and on the fabric CFRP sheet. The same CFRP

laminate design as for Specimen 5 was adopted in Specimen 16. However, there were

no cuts in the concrete surface, and bond and delamination fabricated defects were used

in this laminate. After the application of the laminate, a CF130 fabric composite was

attached on top of the concrete-laminate system. Figure 3.11-16 illustrates the CFRP

composites of Specimen 16. Two grooves were engraved in Specimen 17 with planar

size of 30 × 100 mm and 5 mm in depth to be filled later with water to examine the

moisture detection ability of IRT. These grooves simulated concrete defects on the

surface. Two single CFRP laminates strips 80 mm × 300 mm × 1.4 mm were applied to

Specimen 17, as shown in Figure 3.11-17. Specimen 18 was designed with the same

artificial cracks as Specimen 10, but with a single CF130 fabric sheet.

Qualitative IRT experimental laboratory program

77

Specimens 19, 20 and 21 were embedded with different debond flaw thicknesses under

a single CF140 sheet. The thickness of the debond areas ranged from 0.1 to 1 mm, as

shown in Figure 3.11-19 to 3.11-21. Artificial deep spalls in the concrete were made in

Specimens 22 and 23 to test the detection of spall in concrete-CFRP systems. Different

CFRP fabric and laminate systems were employed in these two specimens, and Figures

3.11-22 and 3.11-23 demonstrate their designs. Bonding deficiency under different

CFRP fabric types was investigated in Specimen 24. CF130 and CF140 fabrics were

attached to that concrete specimen as shown in Figure 3.11-24. A strip was left without

applying epoxy. Three artificial cracks were generated during the construction of

Specimen 25 by inserting narrow plastic sheets in the concrete wood framing before

placing the concrete. The sizes of these cracks were 0.2, 1 and 2.5 mm, as shown in

Figure 3.11-25. Specimen 25’s surface was prepared to a very rough level, and later

covered completely with a single MBrace CF130 fabric sheet to investigate the effect of

the rough preparation level on the IRT results. A debond defect was generated in

Specimen 26 by the same means as in Specimen 3. The CFRP material used in

Specimen 26 was a CF140 fabric single sheet. Finally, Specimen 27 was prepared with

the exact design of Specimen 24. The only difference was in the direction of the unbond

strip area. Figure 3.11-27 shows the design of Specimen 27.

Five steel specimens were constructed with dimensions of 300 mm × 300 mm × 3 mm.

Different sizes and patterns of bond, debond and delamination defects were implanted

in these specimens. Figure 3.11-S1 reveals the unbonded embedded defects in Specimen

S1. The defects were in rectangular shapes and with small and moderated sizes. A

CF130 unidirectional fibre sheet was used on the top of the steel surface. Debond under

the CF130 CFRP was constructed in Specimen S2, as shown in Figure 3.11-S2. The

same technique as for Specimen 3 was followed to create this debonding. Two unbond

strips were inserted under a combination of CF130 and CF140 CFRP layers in

Specimen S3. A small delamination was also generated in that specimen between the

CF130 and the CF140 sheets. A single CFRP laminate strip was attached to the steel

surface in Specimen S4 with an unbonded area of 80 mm × 70 mm, as demonstrated in

Figure 3.11-S4. Specimen S5 was made by bonding a combination of CF130 CFRP

Chapter Three

78

fabric with CFRP laminate on top of it. Two bond defects were designed in this

specimen.

Pictures of different specimens and details are presented in Appendix A.

1

50

50

50

50

50 50 100

2

100 70

3

UB021

UB011

UB012

DB031

UB013

7

210

120

70

8

220

100

180

100

UB081 9

UB091

50 80

UB071DL072 UB092

Qualitative IRT experimental laboratory program

79

Chapter Three

80

Labels:

50 50S1 S2 S350

50

DLS31DBS21UBS11

UBS12

UBS13UBS14

UBS15UBS32

S4 40 80

140

70

S5

UBS51

UBS41

UBS52

UBS53

UBS54

Qualitative IRT experimental laboratory program

81

Figure 3.11 Specimen details

Figure 3.12 Specimen 3 artificial debond

Figure 3.13 Groove in concrete of Specimen 4

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82

Figure 3.14 Specimen 5 CFRP laminates

Figure 3.15 Specimen 11 loading-generated cracks

3.2.7 Identification of artificial defects

The embedded defects were categorized in groups and labeled. The series of unbond

defects was labelled UB followed by two digits for the specimen number. The final

number in the defect identity label was for the defect number within the selected

specimen. An example of this defect identification is UB013: UB refers to unbonded

defective area, 01 refers to Specimen 1 and the final number 3 states that this defect is

the third defect within Specimen 1. As shown in Figure 3.11 defect identification

starting with DB refers to all debonding areas generated between the CFRP composites

and substructures. DL refers to delamination defects between multiple CFRP layers.

Qualitative IRT experimental laboratory program

83

Grooves cut in the concrete surfaces before applying the CFRP are marked GR, and

both artificial cracks and cracks generated via loading are labelled CR.

Finally, the artificial spalls within the concrete structure labelled SP, and steel

specimens are distinguished by adding the letter S after the defect identity letters, as

demonstrated in Figure 3.11-S1 to 3.11-S5.

Table 3.6 summarizes and identifies all artificial defects and anomalies that were

implanted within the concrete and steel specimens.

Chapter Three

84

Table 3.6 Identification of artificial defects

Spec

imen

Unbonding

defects

Debonding

defects Delaminations

Grooves in

concrete

Cracks in

concrete

Spalls in

concrete

1 UB011–UB013

2 UB021

3 DB031

4 GR041-GR042

5 UB051-UB052 GR053-GR054

6 UB063-UB064 DL061-DL062

7 UB071 DL072

8 UB081

9 UB091-UB092

10 CR101-CR104

11 CR111-CR112

12 CR121

13 DB131 DL132

14 CR141-CR142

15 CR151-CR156

16 UB161 DL162

17 GR171-GR172

18 CR181-CR182

19 DB191-DB192

20 DB201

21 DB211-DB212

22 SP221-SP222

23 SP231-SP232

24 UB241-UB242

25 CR251-CR253

26 DB261

27 UB271-UB272

S1 UBS11-UBS15

S2 DBS21

S3 UBS32 DLS31

S4 UBS41

S5 UBS51-UBS54

Qualitative IRT experimental laboratory program

85

3.3 Qualitative infra-red thermography set-up

As mentioned in Section 2.2.10, the main purpose of the qualitative study was to detect

the presence of subsurface defects. For that reason, reading the real surface temperature

was not required in the qualitative thermography tests. The test set-up focused on the

evaluation of the IR technique to detect different kinds of defects without the need to

read the input thermal time-dependent function or the thermal signal response. Both

passive and active thermography approaches were performed in the qualitative tests

conducted in Part One of the experimental program. A FLIR B200 infra-red detector

was used in the qualitative testing.

3.3.1 Infra-red detector for qualitative tests

Infra-red radiation can be detected by special equipment that contains sensors. These

sensors can generate electrical signals in proportion to the amount of infra-red radiation

received. The infra-red equipment can convert the reading of the internal sensors to

temperatures. The applications IRT NDT depend to a large extending on the abilities

and specifications of these infra-red detectors.

The FLIR B200 infra-red detector shown in Figure 3.16, functions in the long

wavelength infra-red spectral band between 7.5 µm and 13 µm (FLIR 2011). The

measurement range of this camera varies from -20 oC to 120 oC. This detector has an

uncooled focal plane array (FPA) microbolometer detector. The resolution of this

imager is 200 × 150 pixels. The resolution of the infra-red thermograms plays a pivotal

part in the interpretation of results. The scalable picture-in-picture feature of this camera

(combined IR and visible light images) helps to reveal hidden defects in the structure.

This detector cannot record sequences of thermal images or a subtraction process. Only

five boxes can be measured as regions of interest within the thermogram imaged with

the ability to read maximum, minimum and average temperature points. No time history

measurement can be recorded with this camera. The FLIR B200 is considered too

simple for quantitative research purposes. It is specially designed for qualitative

thermography such as building inspections, heating-/-cooling problems, gas leakage

Chapter Three

86

detection, and the detection of moisture. However, it is much cheaper compared with

other more sophisticated infra-red imagers.

(a) General view of FLIR B200 (b) The IR camera testing Specimen 1

Figure 3.16 FLIR B200 camera with IRT testing set-up

For the excitation system, 2000 watt tungsten halogen light lamps were employed. The

specifications of these lamps are detailed in the next chapter.

3.4 Qualitative IRT NDT

A qualitative, non-destructive IR test was examined in this part of the experimental

laboratory program. The detection of bond defects, delamination, cracks, and water

were the aims of this phase of the tests. As mentioned in the qualitative test set-up, a

FLIR B200 camera was used and the time history of the thermal injection heat wave and

its response as a heat flux on the specimens’ surfaces were not recorded. Passive and

active thermography techniques were applied to different specimens to examine and

evaluate the IR ability to detect unbonbed areas, debond defects, delaminations and

artificial cracks implanted in the FRP systems.

3.4.1 Passive qualitative IRT

Specimens were tested during the day-time and at night when the change in temperature

reached its peak. Tests in day-time were performed under sun light and in shade.

Qualitative IRT experimental laboratory program

87

The results of the FLIR B200 infra-red imager demonstrate lower pixel resolution, as

expected from the camera’s specifications. However, the thermal image was good

enough to identify the defects approximately.

Different specimens were examined during the qualitative tests. Figure 3.17 shows the

thermogram of Specimen 1 which was tested with passive IRT. It is easy to distinguish

unbond embedded areas. However, the boundaries of these unbonded areas are not

determined accurately. This test was conducted during the change in the normal weather

temperature at the beginning of the daylight.

Figure 3.17 Specimen 1 thermogram- passive qualitative thermography

Specimen 5 was also tested passively to examine the ability of this thermographic

technique to detect any spalling of concrete in the CFRP laminate-concrete bond zone.

The captured images show that it is impracticable to detect this kind of defect beneath

CFRP laminate. Figure 3.18 illustrates the picture-in-picture (combined IR and visible

light images) thermal image for Specimen 5, and as shown in the figure the groove area

GR053 was undetectable.

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88

Figure 3.18 Specimen 5 IR capture

3.4.2 Active qualitative IRT

In the active approach, heating halogen lamps were used in the excitation system. The

input heat flux wave details were not under investigation due to the requirements of the

qualitative test and limitations of the IR camera employed. Active pulse thermography

was applied to different specimens. Figure 3.19 presents an IR image of the active

thermography test.

Figure 3.19 Active qualitative thermography excitation system

Figure 3.20 shows the thermal image of Specimen 1 after its surface was subjected to

heat from the two 2000 watt lamps. The figure shows that the images recorded using the

active approach show enhanced details compared with the passive approach for the

same defect in Specimen 1. The unbonded areas in this specimen are easier to identify.

Nevertheless, the measurement of these artificial defects was not possible due to the

limitation of the infra-red image resolution.

Qualitative IRT experimental laboratory program

89

Figure 3.20 Specimen 1 thermogram- active qualitative thermography

Unbonded areas in different specimens’ CFRP fabric designs were also detectable by

qualitative thermography. Figures 3.21, 3.22, 3.23, and 3.24 show the infra-red results

of Specimens 6, 7, 8, and 13. The results show that qualitative testing can provide the

location of the artificial unbond defects and a general view of the shapes of the unbond

defects. However, this infra-red approach is not able to provide in-depth information

about defect type, or accurate dimensions. It also cannot identify small unbonded areas

or spalls in concrete. The test cannot distinguish between the different CFRP fabrics

attached to these specimens, or show different temperature distributions between

unbond and debond defects. For example, Figure 3.21 shows that IR image cannot

distinguish between fabricated flaws DL061 and UB063. Bond defects in the bi-

direction CFRP–concrete system are not easy to detect, as shown in Figure 3.22,

possible due to the increase in the fabric thickness compared with the uni-directional

CFRP. The surface of Specimen 13 was prepared using powerful water jets, which

caused the external CFRP fabric to not attach smoothly. The qualitative infra-red

approach is unable to detect unbond and delamination areas with this imperfect surface

preparation. The thermogram of Specimen 13, shown in Figure 3.24, reveals broad

areas as hot spots, not the actual location and size of the embedded defects DB131 and

DL132.

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90

Figure 3.21 Thermogram of Specimen 6

Figure 3.22 Thermogram of Specimen 7

Figure 3.23 Thermogram of Specimen 8

Qualitative IRT experimental laboratory program

91

Figure 3.24 Thermogram of Specimen 13

Bond defects in CFRP laminate–concrete specimens were investigated in Specimens 9

and 5. Figures 3.25 and 3.26 show the thermal images for these specimens. In Specimen

9, the unbonded area UB091 beneath the FRP fabric is noticeable. However, the UB092

defect is undetectable through the FRP laminate. The same detection performance was

noticed for Specimen 5, in which the unbond fault UB051 beneath the single FRP

laminate layer is easy to identify while the IR image shows very small differences in the

surface temperature map on the bond defect area UB052 of the double FRP laminates.

Figure 3.25 Thermogram of Specimen 9

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92

Figure 3.26 Specimen 5 IR image

The qualitative NDT that investigated the detection of debonding show that debond

defects are easy to see by using this technique. Specimen 3 was constructed with an

artificial debond flaw, as shown in Figure 3.11-3. This specimen was tested

qualitatively with the FLIR camera with long pulsed active thermography. Figure 3.27

illustrates the recorded image of that test. As can be seen from the image, the debonding

DB031 is easily detected. However, the test shows no differences in the temperature

within the debonding area which can give an indication of the severity of the debonding.

Moreover, distinguishing between the unbond areas and debond defects in the

thermogram images is incapable.

Figure 3.27 Delamination in Specimen 3

Specimens 4 and 17 were tested to check the capability of the technique to locate

grooves in the concrete surface beneath CFRP fabric and laminate respectively. As

Qualitative IRT experimental laboratory program

93

shown in Figures 3.28 and 3.29, it is easy to identify the location and size of these

grooves. The temperature difference between the area of the GR041 defect and the

surrounding areas was higher beneath the CFRP fabric compared to CFRP laminate

GR171, due to the difference in the FRPs’ thermal properties in these two specimens.

Figure 3.28 Specimen 4 IR record

Figure 3.29 IR thermogram of Specimen 17

The capability of IRT to detect water and humidity within the defect area was also

examined. Water at room temperature was injected into debonds and grooves of

Specimens 3, 4, 5, and 17. Figures 3.30, 3.31, and 3.32 show these experiments. The

images indicate that in the debonding region, the areas with water presence are

generally undistinguishable. For water in concrete grooves, the qualitative approach is

able to detect it in the single CFRP fabric layer only (see DB031 in Figure 3.30). For

CFRP laminate, the presence of humidity or water in the grooves in Specimens 5 and 17

Chapter Three

94

is completely undetectable using this technique. The thermogram of Specimen 5 in

Figure 3.32 shows no indication of the injected water in the defect area.

Figure 3.30 Water injection in DB031 defect

Figure 3.31 Specimen 4 water investigation

Figure 3.32 GR053 IR image – water presence examination

Qualitative IRT experimental laboratory program

95

Crack tracing was investigated by using qualitative IR NDT. Specimens 10 and 18 were

subjected to active thermography tests for this purpose. The results shown in Figures

3.33 and 3.34 indicate that artificial cracks are detectable if they are under a single layer

of CF fabric and more than 3 mm wide. Cracks embedded in concrete with multi-CFRP

fabric layers like CR103 and CR104 cannot be distinguished, as shown in Figure 3.34.

Cracks of less than 3 mm like CR111 and CR112 cannot be identified.

Figure 3.33 Thermogram of CR181 and CR182 artificial cracks

Figure 3.34 Embedded artificial cracks in Specimen 10

Steel specimens strengthened with CFRP fabric and laminate were also tested using

active qualitative IRT NDT. Specimens S1, S2 and S4 were investigated to study the

ability to detect bond defects, debonding and delamination implanted in CFRP fabric

and laminate. Figures 3.35, 3.36, and 3.37 illustrate the thermograms of these

specimens. Due to steel’s thermal properties, the generated heat wave in active

Chapter Three

96

thermography usually fades within a short period. For that reason, detection in steel

specimens needs more time for capturing the IR images. The bond defect UBS15 in

Specimen S1with an area smaller than 9 mm2 is invisible in the image, as shown in

Figure 3.35. The test is able to show delamination in the CFRP-steel bond zone. The

debonding severity within the DBS21 defect area in steel specimen S2 is better

recognized than DB031 in concrete Specimen 3, as shown in Figure 3.36, possibly due

to the differences in the heat wave behaviour between steel and concrete.

Bond deficiency was identified in the bond surface between CFRP laminate and steel.

Figure 3.37 demonstrates the IR capture for Specimen S4, where a bond defect was

implanted in the CFRP system with steel. As can be seen from that figure, its detection

is trouble–free. However, due to the low control on the time-history in qualitative IRT

NDT, the precise size of the unbond area cannot be measured accurately.

Figure 3.35 Specimen S1 IR capture

Figure 3.36 IR record of Specimen S2

Qualitative IRT experimental laboratory program

97

Figure 3.37 UBS41 defect in Specimen S4 thermogram

3.5 Summary and findings

The experimental program reported in this chapter concentrated on investigating the

ability of qualitative IRT to detect different kinds of defects and anomalies including,

unbonded areas, debonds, delamination, cracks, and water within the defect zone. IRT

tests were conducted both passively and actively using FLIR B-200 IR detector.

Based on the IR thermal images several conclusions can be drawn as follows:

For qualitative thermography assessment, the infra-red images show a reliable

capability to detect unbond areas, debond, and delamination defects. However,

qualitative IRT testing is unable to detect bond defects beneath multiple layers

of CFRP fabric or laminate.

The study highlights the modest capabilities of qualitative thermography to

address debonding severity or to distinguish between debond and unbond faults.

Study of the different CFRP fabric designs including the influence of changing

the CFRP fabric thickness and fibres direction was impracticable due to the IR

detector’s low resolution.

The detection of water is successful using qualitative techniques, but with

limitations. Detection is not easy in debonding areas, and in CFRP laminate, the

presence of water in any form is undetectable.

Chapter Three

98

In general, most artificial cracks under multi-layers of FRP composites are

untraceable using qualitative IRT NDT. The cracks are detectable only beneath a

single layer of CFRP fabric Type CF130.

Strengthened CFRP -steel specimens show the same behaviuor in terms of

detection abilities for different defects. Bond defects with small areas are very

hard to detect.

Precise measurement of implanted unbonded areas is not possible.

The results of the qualitative thermography tests show that this technique can be very

useful for the rapid detection of bond and debonding defects in the bond zone between

CFRP systems (fabric or laminate) and the substructure (concrete or steel). However,

for research purposes, with need to characterize and study the defects in depth,

qualitative thermography is inadequate. The next chapter report an experimental

program conducted using quantitative IRT NDT.

Quantitative IRT experimental laboratory program

99

4 CHAPTER FOUR: QUANTITATIVE INFRA-RED

THERMOGRAPHY EXPERIMENTAL LABORATORY

PROGRAM

4.1 Introduction

The literature review in Chapter 2 reported a number of studies on the use of IRT to

detect defects in substrates. However, test accuracy is still under question, and different

parameters and aspects need more work. Various points were identified as requiring

further detailed study, including humid bond defect detection, crack identification and

measurement, and the control of heating waves from the excitation system.

This chapter reports on 27 plain and reinforced concrete specimens and five steel

specimens strengthened externally with different CFRP applications which were

investigated using different IRT approaches. The major main aim of all the tests was to

help to establish a standard IRT test design suitable for different CFRP products and

different substrate structures. The quantitative studies are reported in eight parts, each

addressing different goals of investigation.

4.2 Design of experimental laboratory program

The experimental program reported in this chapter was divided into eight different

research foci, each involving numerous IRT experiments. Quantitative IRT was used in

the program reported in this chapter. An NEC Thermo Tracer TH9260 thermal camera

was used for the IR tests in this chapter. Both concrete and steel were used as substrate

structures for the FRP strengthening systems. 27 concrete specimens and five steel

specimens were examined. The aims were as follows:

1 To investigate the capability of IRT NDT to detect unbond, debond and

delamination defects in different CFRP composite systems and study different IR

active techniques for concrete and steel substructures.

2 To study the ability of the tests to identify defect size and shape.

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100

3 To design an appropriate configuration for the IRT excitation system.

4 To study the IR reading errors and noise that can lead to misinterpretation of

results.

5 To examine the ability of IRT NDT to identify wet areas and the presence of

water within bond zones and substrate cracks.

6 To study defect characterization by applying long PTT and LTT.

7 To investigate the capability of IRT to identify, locate and measure cracks under

CFRP systems.

4.3 Quantitative infra-red thermography set-up

A special design was adopted to conduct the quantitative IR tests. In the tests, it was

planned to detect, study and characterize the defects. Both passive and active

approaches were carried out to obtain in-depth quantitative thermography analyses.

Quantitative active IRT test equipment includes a suitable infra-red imager, efficient

excitation systems, and temperature and heat flux sensors. In addition, a special full-

frame shutter was built to control unwanted heat form the excitation sources while the

passive thermography testing was achieved without any external excitation resources.

Special arrangements were made for the testing site to manage the reflection from other

objects in the laboratory.

4.3.1 Infra-red detector and data analysis process

The TH9260 infra-red detector, Figure 4.1-a, operates in the long wavelength infra-red

spectral band between 8 µm and 13 µm (NEC 2011). The camera has a thermal

sensitivity of 0.06 oC at 30 oC. The measurement accuracy is ± 2 oC or 2% of the

reading at ambient temperature 0 oC ~ 40 oC. The detectable measurement can reach up

to 30 frames per second. The measurement range of this camera varies from -20 oC to

60 oC. This detector has an uncooled focal plane array (FPA) microbolometer detector

with 640 (horizontal) × 480 (vertical) pixels. The field of view diagram of this decoder

Quantitative IRT experimental laboratory program

101

is shown in Figure 4.1-b. The minimum detectable area that this imager can detect is

0.18 mm2. The emissivity correction is between 0.1 and 1.0. The detector provides

ambient temperature correction, background temperature correction, and distance from

object correction. The camera is supported by many image processing functions and can

read the temperatures for different points and provide the IR readings with different

shapes as regions of interest. The data also can be recorded with real time interval

measurement.

(a)

(b)

Figure 4.1 (a) Thermo Tracer TH9260 thermal camera (b) Thermo Tracer TH9260 field of view (NEC 2011)

According to Planck’s Law, as objects with high temperature emit radiation in short

wavelengths, the detector with long wavelength receives radiation with minimal

atmospheric effects. Therefore, the TH9260 IR detector shows minimal noisy images.

The obtained data are digitized and displayed as shades of color or grey with many

different patterns. The control of these display patterns can greatly affect the detection

2 2 22

Chapter Four

102

process. Cooler or hotter regions of interest are identified by different shading or colour

compared with neighboring areas. To confirm that the temperature differences in the IR

records are not due to the emissivity differences of different surfaces, a digital video

camera is used in parallel with the TH9260 infra-red detector to provide a record of the

regions of interest and monitor and compare the IR and visual captures.

The IR camera is connected to a computer in video mode. The IR software Image

Processor ProII was used in this study. This software works in two modes: online when

the camera is connected to the PC, or offline when it is not. The package has different

advanced capabilities providing different digital capture framing rates and image

acquisition and analysis. Emissivity is established according to the thermal properties

of the investigated material. The software has the following capabilities: real-time

subtraction from selected thermal images; detection of abnormal temperature by

maximum/minimum temperature; temperature display within a specified area (up to 16

points); data transfer.

4.3.2 Excitation systems

To perform active IRT NDT, an external heating system is required. Theoretically, the

excitation heating system should distribute the heat uniformly across the entire area of

the investigated surface within the field of view of the IR detector. However, this is

limited by the need to capture thermograms at the same time as the injection of the heat

wave (Brown and Hamilton 2007). Different heating methods studied in the present

research include: pulse heating and long-pulse heating for the PTT approach and

sinusoidal heating for the LTT approach.

Two systems were constructed for use as excitation sources for this study. Halogen

heating lamps and hot air blower were utilized as they represent likely heat sources for

performing IRT in the field. Most of the active quantitative IRT tests were carried out

using halogen lamps.

Quantitative IRT experimental laboratory program

103

4.3.2.1 Heating lamps

Two tungsten halogen light lamps with steel housing were used in the active IRT set-up

as an excitation source to generate heat waves. The maximum capacity of these 240

volts lights is 2000 watts with varibeam capability. The light beam can vary from spot

to flood mode. Both modes were utilized in the quantitative active thermography tests to

homogenize the heating waves. The light centre values of these lamps at 3m distance

and 2000 watts are 3250 and 1646 for spot and flood modes respectively (IANIRO

2011). The light beam can be adjusted to different angles with respect to the specimen’s

surface, which creates different temperature patterns. This excitation system was also

adopted in the active qualitative IRT. However, the record of the thermal signal was not

necessary in that phase of the tests. Figure 4.2 shows the halogen lamps used in the

quantitative and qualitative active thermography tests. The lamps were placed at

different distances from the specimens’ surfaces.

Figure 4.2 Halogen heating lamps (IANIRO 2011)

A variable auto-transformer (variac) HSN M-303, shown in Figure 4.3, was connected

to the 2000 watt lamps to manage the heating flux intensity. The variac has the ability to

provide a continuous voltage from 0 to 260 volts (Varat 2011) to produce heating

intensities between 0 and 2000 watts. This device is essential during lockin

thermography testing.

Chapter Four

104

Figure 4.3 Variable auto-transformer (Variac)

4.3.2.2 Air blower

A linear hot air blower was used as a second heating source in the IR investigations.

The capacity of the fan blower was 2000 watts with 50 Hz frequency. For the qualitative

phase of the IR tests, scanning heating parallel to the specimens’ surfaces by means of

this air blower was used. The blower was positioned at a distance of 70 cm from the

investigated area during the IRT NDTs.

4.3.3 Heat flux sensors

Heat flux sensors were used to read and calibrate the output thermal intensity received

from the specimens’ surfaces during the FRP composite emissivity evaluation tests and

quantitative IRT runs. Two polyurethane PU-T thermal sensors (PU 11 T and PU 22 T)

from Hukseflux Thermal Sensors Company (Hukse Flux 2011) were attached to the

surface of all specimens during the active IRT tests. The positions of these sensors were

arranged to represent the actual heat flux detected on the investigated areas with

artificial implemented subsurface defects.

A data acquisition system was connected to these sensors to record the input heat flux

magnitude and temperature. These heat flux sensors helped to control the test set-up

parameters, including the angles of the heating beams, the intensity of the varibeam

Quantitative IRT experimental laboratory program

105

lighting (spot or flood), and the distance between the heating source and the surface of

interest. Table 4.1 and Figure 4.4 summarize the heat flux sensor data.

Table 4.1 Thermal sensors details (Hukse Flux 2011)

Model PU 11 T PU 22 T

Properties Unit

Thickness mm 1 1

Overall diameter mm 25 50

Dimensions sensitive

area mm2 Ø 15 Ø 30

Sensitivity µV/Wm-2 8 30

Electrical resistance Ohm 433 1850

Temperature range oC -20 ~ +90

Thermal conductivity W/mK 0.2

Expected accuracy % 5

Cable connection m Fixed wires 2 metre

Minimum bending

radius mm 15 25

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106

Figure 4.4 PU-T thermal sensor series details (1) Sensitive area, (2) Guard, (3) Fixed wire, (4) Minimum bending radius, and (5) Optional temperature sensor (Hukse Flux

2011)

4.3.4 Test configuration

A rigid steel frame with sliding shutters was constructed for the IRT testing with the

dimensions of 3 m wide and 1.8 m high. The sliding shutters were made from insulated

material (Styrofoam) to control the heat flow by cutting off the unwanted radiation

emitted after the thermal injection. Figure 4.5-a illustrates the schematic of the

constructed frame. The steel frame was coated with matt black paint, to simulate black

body emissivity and reduce the radiation reflected form the steel. The IR detector was

positioned about 0.7 m from the tested specimens and on the same level as the centre of

the specimen. However, the specimen level could be adjusted for height and angle by

adjusting the specimen holder. The specimen holder was made from steel and had an

adjustable height of 1.3 m as a maximum with controlled angle positions, as shown in

Figure 4.5-b. Like the rigid steel frame, the holder was painted matt black.

Quantitative IRT experimental laboratory program

107

(a) The insulated sliding shutters [not to scale]

(b) Specimen holder details [not to scale]

Figure 4.5 Infra-red test configuration, (a) Rigid frame with insulated sliding shutters, (b) Specimen holder details

1.85

m

0.8 m

Styrofoam Sliding Shutter

(50 mm)

Rigid Frame

Rigid Frame

3 m

Front View

Top View

Styrofoam Sliding Shutter

(50 mm)

Styrofoam Sliding Shutters

Rigid Frame 305 * 305 mm

Rigid Holder

Angle controller

0-90 o

specimen 300 * 300

mm

1.3 m

Chapter Four

108

In the active IRT phase and after the target specimens received the injected thermal

wave from the excitation source, one sliding shutter was moved and the window

between the heat source and the specimen closed to stop the specimen surface receiving

any extra radiation from the turned off lamps. Figure 4.6 demonstrates the test

procedure. The test site was covered with dark curtains to minimize the reflection from

objects inside the laboratory, as shown in Figure 4.6-c. The testing was performed in a

temperature- and humidity-controlled laboratory.

(a)

(b)

Sliding ShutterRigid Frame

Specimen

Infra-Red Detector

Processing

Excitation System

Sliding Shutter

Infra-Red DetectorSpecimen Processing

Rigid Frame

Excitation System

Quantitative IRT experimental laboratory program

109

(c)

Figure 4.6 Schematic views of: (a) turned-on lamps, (b) turned-off lamps, and (c) dark curtain tent covering the test site

4.3.5 Heating schemes

Different heating scheme were applied to the active IRT tests including: pulse heating

and long-pulse heating for the pulse thermography approach and sinusoidal heating for

the lockin thermography technique.

4.3.5.1 Pulse scheme

The input heat flux applied in the pulse thermography technique (PTT) was measured as

a function of time. The excitation heat resources were positioned at different distances

from the investigated surface to provide different heat flux intensities. These distances

were chosen to be 50 cm, 70 cm, 100 cm and 120 cm, as results showed the best thermal

responses were in this range of distances. If the heat source was placed at less than 0.5

m, the temperature of the object will increase to be higher than the epoxy glass

transition temperature (Tg) in long pulse active PTT. Poor thermal signals were obtained

when the distance between the excitation system and the medium of interest was more

than 1.2 m. PTT was applied by using the excitation sources described in Section 4.3.2.

Three pulse durations were adopted in the PTT, with intervals of 1 s, 3 s and 5 s. The

Chapter Four

110

flux intensity of the injected heat waves was measured by using the sensors detailed in

Ssection 4.3.3 to maintain and monitor the value of the heat pulses. These sensors were

attached externally to the CFRP composite surfaces. A data logger was connected to

these sensors to record the voltage and transform the data into heat flux units in watts

per square metre. To track and calibrate the received heat flux continuously and to

ensure heating consistency, this procedure was implemented for every quantitative IR

test conducted in this research program.

The change in locations of the heat flux sensors can alter the reading of the heat flux

amount. To reduce this variation, the location of these sensors was fixed for most of the

tested specimens. Figure 4.7 and Table 4.2 present the model pulse waves t introduced

to specimens. Different intensities with different pulse intervals were recorded as a

function of time, as shown in this figure. The range of inserted heat flux varied from

150 W/m2 to 150 W/m2. However, the heat received on specimens’ surfaces can vary by

the changing of parameters other than pulse times and lamp distance, including: ambient

temperature, humidity, and gases between the excitation source and the tested surface.

Quantitative IRT experimental laboratory program

111

(a) Pulse length of 1 s

(b) Pulse length of 3 s

(c) Pulse length of 5 s

Figure 4.7 Pulses in PTT versus time at different distances and durations (Specimen 24)

0

100

200

300

400

500

600

700

800

900

1000

0 1 2 3 4 5 6 7H

eat F

lux

(W/m

2 )

Time (s)

1s Pulse at 120cm

1s Pulse at 100cm

1s Pulse at 70cm

1s Pulse at 50cm

0

200

400

600

800

1000

1200

1400

1600

0 1 2 3 4 5 6 7

Hea

t Flu

x (W

/m2 )

Time (s)

3s Pulse at 120cm

3s Pulse at 100cm

3s Pulse at 70cm

3s Pulse at 50cm

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 1 2 3 4 5 6 7

Hea

t Flu

x (W

/m2 )

Time (s)

3s Pulse at 120cm 3s Pulse at 100cm

5s Pulse at 70cm 5s Pulse at 50cm

Chapter Four

112

Table 4.2 Heating designs (Specimen 24)

Pulse length (s) Lamp distance (cm) Max. heat (W/m2)

1 120 230

1 100 300

1 70 580

1 50 620

3 120 400

3 100 540

3 70 900

3 50 1250

5 120 460

5 100 600

5 70 1040

5 50 1490

The total of the IRT tests conducted with the pulse heating scheme was 372, and

thermal images were recorded for all these tests. The image capture rate was 0.25 s.

Each test was recorded by capturing a series of 600 thermograms. A laptop computer

was connected to the IR imager to record thermograms and controls the test set-up. The

thermal analyses were performed later using a powerful personal computer. Figure 4.8

shows a block diagram of the final set-up of the pulse heating used in the PTT tests.

Quantitative IRT experimental laboratory program

113

Figure 4.8 Pulse heating scheme

4.3.5.2 Sinusoidal scheme

The lockin thermography technique (LTT) was carried out by applying sinusoidal heat

waves to selected specimens. The same heating lamps at those used for PTT were used.

However, to control and produce the sine shape for the heating waves, the variac

described in Section 4.3.2.1 was employed. The variac was used mainly to control the

intensity of the 2000 watt lamps. The variac regulates these lamps’ productivity by

adjusting the input voltage. The entered voltage varies from 0 to 260 volts.

A total of 34 IR tests was performed using this heating scheme. The introduced thermal

loads ranged in intensity and frequency. These sinusoidal heat waves were applied to

the specimens’ surfaces in two frequencies of 10 s and 20 s. Two cycles of sinusoidal

waves were set using the halogen lamps. The lamps in this heating scheme were

positioned at 70 cm from the specimens’ surfaces. Figure 4.9 shows the shape and

intensity of two cycles of sinusoidal heating waves that were utilized in the LTT thermal

heat flux applied to Specimen 1. The block diagram in Figure 4.10 illustrates the

sinusoidal heating scheme used in the LTT tests.

Chapter Four

114

Figure 4.9 Two cycles of input heat flux during the LTT testing of Specimen S1

Figure 4.10 Sinusoidal heating scheme

4.3.5.3 Long-pulse heating scheme

A long-pulse heating scheme was carried out in the quantative IRT approach. The same

test configration as that used in the PTT and shown in Figure 4.8 was adopted in the

long-pulse heating method. However, pulses had longer duration intervals. A total of 20

specimens was exposed to a 10 s pulse length. Another four selected steel specimens

were subjected to 20 s pulses. The excitation system was mounted at 50 cm and 70 cm.

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

0 10 20 30 40

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

UB011-0.05Hz

Quantitative IRT experimental laboratory program

115

The IR camera captured thermograms from a distance of 70 cm from the investigated

specimen. The temperatures on the surface were observed and continuously monitored

to ensure that the temperature on the specimen surface did not exceed the epoxy glass

temperature limit. The model of heating pulse waves versus time that used in this

scheme is shown in Figure 4.11. In general, it was found that applying this heating

system for more than 10 s from a distance of less that 0.5 m increased the CFRP’s

surface temperature to more than the Tg limit.

Figure 4.11 Long-pulsed heating scheme

4.4 Characterization of infra-red detectability

The investigation of the detectability of defects was performed by analyzing and

examining the results of IR images in terms of thermal signals (ΔT). The relationships

of ΔT versus time were generated for all defects in all inspected specimens. The thermal

signal is defined as:

ΔT(t) = T(t)defect – T(t)background Equation 4.1 where,

ΔT(t) = thermal signal in Celsius degree at specific time,

0

200

400

600

800

1000

1200

1400

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Hea

t Flu

x (W

/m2 )

Time (s)

Chapter Four

116

T(t)defect = the recorded surface temperature above the subsurface defect at specific time

in Celsius degree,

T(t)background = the recorded surface temperature in the surroundings defects-free areas at

specific time in Celsius degree,

t = time in second.

The defect detection was also presented by using the thermal contrast number (C) which

can define as:

C(t) = ΔT(t) / ( T(t)background - Tambient) Equation 4.2 where,

C(t) = Thermal contrast at specific time,

ΔT (t) = thermal signal of the defect at specific time in Celsius degree,

T(t) background = the record surface temperature in the surrounding defect-free areas at

specific time in degree Celsius,

Tambient = the ambient temperature, most of the tests were conducted at 20 oC.

Area measurement functions were used in the analysis to record the surface temperature

above the defect. These functions are able to determine the maximum, minimum and

average temperature with its region. These functions are denoted as regions of interest

(ROIs) within the body of this thesis. The thermal signal was used mainly to measure

and present the thermal responses of all defects for all specimens.

As determined in Equation 4.1 the thermal signals were calculated by recording the

temperatures on pixel sizes in small ROI above the selected defect zone and another

ROI in a defect-free area near the defect. The value of the thermal signal is the

difference of these two recorded temperature values. The designs of the selected ROIs

greatly affect the thermal signal values. However, the skilled thermographer can

identify the locations of the maximum ΔT value within the series of thermal images by

choosing the true spots for both the investigated defect and defect- free areas. In this

study, the choice of the ROI areas above the defect was made by drawing a rectangular

ROI in the thermogram surrounding the defect. ROI number 1 shown in Figure 4.12

Quantitative IRT experimental laboratory program

117

reveals a model defect measurement. The defect- free temperature was recorded in the

same way by acquiring the average temperature, as in ROI 2 in Figure 4.12. For all

tests, efforts were made to make the two ROIs receive the same heat flux by choosing

ROIs close to each other. ROI sizes reflecting the thermal data on the defect or the

defect-free areas were designed to give sufficient information of pixel amounts to

appropriately represent the heterogeneous surface temperature. However, the number of

pixels per ROI was not constant; it varied by the size of the defect area investigated.

Another method of presenting the ROI defect area is the line pixel profile where the

temperatures are recorded over a whole line drawn in the IR image. Narrow cracks can

be characterized efficiently using the line ROI. Figure 4.13 demonstrates a ROI line

profile used in the IR analysis to characterize crack detectability in Specimen 12.

Figure 4.12 Recognition of defect and defect- free ROIs

Figure 4.13 Pixel line profile

Chapter Four

118

The IR results are presented by constructing thermal signal versus time maps. Thermal

signals or thermal contrasts respond in different patterns with time. Three patterns were

identified in the time-dependent thermal signal response as follows:

Pattern A: where the defect detection has a pulse curve shape and thermal

response maximum value of ΔTmax or Cmax at time equal to tmax and minimum

value ΔTmin or Cmin at the end of the recording. Figure 4.14a sketches this

pattern.

Pattern B: This pattern starts with decreasing thermal response behaviour untill a

local minimum value is reached at t = tmin, then the recorded signals follow the

same behaviour as pattern A. Figure 4.14b illustrates this pattern.

Pattern C: This pattern starts with a negative slope and the thermal response

continues to shrink until the end of the test. Figure 4.14c illustrates a model

curve of this pattern.

(a) Pattern A (b) Pattern B (c) Pattern C

Figure 4.14 Thermal signal patterns with time

4.5 Quantitative IRT studies

The experimental quantitative program concentrated on the investigation of the ability

of IRT NDT to detect different defects between CFRP composites and concrete or steel

structures, and between the different layers of attached CFRP composites. The

tmintmax Time Time Time

Ther

mal

resp

onse

(ΔT

or C

)

tmax

Ther

mal

resp

onse

(ΔT

or C

)

Ther

mal

resp

onse

(ΔT

or C

)

Maximum response Maximum

response

Quantitative IRT experimental laboratory program

119

objectives of the experimental program presented in this chapter are divided into eight

parts as follows:

Part 1 The first set involved testing and validating the emissivity values of the CFRP

surfaces. The ASTM E 1933 method of applying the IRT to obtain emissivity

was adopted (ASTM E 1933-99a 2005). For emissivity calculation and

calibration purposes, different specimens were modified by painting half black

to simulate a blackbody which has a known emissivity value. An oven was used

to increase the specimens’ temperatures and PTT tests were applied with 1 s and

5 s durations to determine the emissivity values for the selected specimens.

Excitation sources were also used and placed at 50 cm distance for both painted

and unpainted specimen.

Part 2 In the second set of experimental test runs, the aim was to study in detail the

detection of different unbond, debonding and delamination areas within CFRP

single- and multi-layer designs. PTT was chosen for the IRT tests. Pulses with

intervals of 1 s, 3 s, and 5 s were used as a thermal loading to all specimens and

halogen lamps were positioned at 50 cm, 70 cm, 100 cm, and 120 cm from the

investigated surfaces. A total of 372 IR tests were performed in this IRT phase.

Each test involved analyzing 600 IR images. Thermal responses were recorded

to detect and study defect characterizations. The transmission IR observation

method was used for steel specimens. Far distance detection and measurement

of bond defects were also investigated with pulses of 1 s, 3 s, and 5 s intervals

applied to different specimens. The excitation system was located at 70 cm. The

IR camera captured thermograms from distances of 5 and 10 m from the

investigated specimen.

Part 3 The third part of the experimental IRT program investigated the ability of IRT to

detect correctly the size of faults. Specimens implanted with known defect sizes

were tested and defect sizes were measured. The PTT approach was used mainly

to read these defect measurements. Measures from the thermograms captured

from different PTT tests were recorded and verified.

Chapter Four

120

Part 4 The effect of using different excitation systems was investigated in the fourth

part of the experimental program. Tungsten halogen lamps and hot air blowers

were employed as excitation sources to generate heat waves. Investigation of the

different light distributions was conducted. Different excitation intensity modes

were used by means of the two halogen lamps. The lamps were able to distribute

the light in spot and flood modes. All the PTT IR tests were conducted with light

distribution in spot mode. However, a number of selected specimens were tested

with flood light beam thermal loads. The injected thermal intervals were 1 s and

5 s. Hot air was used as another excitation source by utilizing a dryer with 2000

watt capacity. The dryer’s heater fan frequency was 50 Hz. It was positioned at

70 cm and applied for durations of 5 s, 10 s, and 20 s to the specimen surfaces.

Part 5 The purpose of the fifth investigated area was to minimize IR errors. A specially

designed configuration was built to apply IRT including sliding shutters to cut

unwanted emissions from the turned-off excitation systems. Different actions

were taken to reduce the reflection errors to the minimum. A total of 76 PTT

tests were organized with closed and opened shutters to study the thermogram

reflection errors. Pulses of 1 s and 5 s pulse’s duration were applied. The

distance between the excitation source and specimens was fixed at 50 cm for

consistency of results. Thermal image subtraction analysis was carried out to

control and check the noise in the thermogram readings.

Part 6 The capability of IRT to detect water and humidity within the defect area was

examined in the sixth part. Water with the same temperature as the specimen

was injected in several defects to check the detection of water and/or to

determine the shape of the debond or the delamination defect. The IR detector

positioned 70 cm from the scene. Both active and passive thermography

techniques were adopted in these tests. Different shapes and sizes were chosen

for the artificial defects and grooves.

Quantitative IRT experimental laboratory program

121

Part 7 Long pulse thermography was used in the seventh part to investigate the

differences in thermal imaging signals for different defects. Pulse with 10 s and

20 s heat waves were applied to the medium of interest using the halogen lamps

as excitation sources. The lamps were positioned 50 cm from the specimens’

surfaces, and a total of 20 long PTT tests were performed. In addition, lockin

thermography was used to investigate the differences in thermal image signals

for different defects. A special system was used to control the changes in the

excitation intensity and to produce a time function for the light heating.

Sinusoidal heat waves were applied to the medium of interest. Two frequencies

of 10 s and 20 s with a minimum of two cycles were set using the halogen

lamps. The lamps were positioned at 70 cm from the specimens’ surfaces.

Part 8 The final part studied crack detection and tracing using IRT. Cracked CFRP-

strengthened specimens were examined using PTT. Artificial and loading cracks

were generated in these specimens with different shapes and sizes. The ability of

IRT NDT to measure precisely crack width was examined. The detection of

grooves and spalls in concrete substrates was also investigated.

Table 4.3 details all quantitative IRT tests runs reported in this chapter. The

experimental quantitative IRT studies were performed in an extensive program. More

than 600 IRT tests were conducted on the CFRP-retrofitted concrete and steel

specimens. Each IR test included 600 IR frames, and the image save rate was 0.25 s for

the active and passive IRT. Pulsed and lockin active thermography techniques were

applied to specimens during these IRT tests. All the specimens tested in the quantitative

IRT are mentioned in Section 3.2.6 and shown in Figure 3.11. Table 4.4 summarizes the

attached CFRP materials and the defect design for each specimen tested in the

quantitative IRT program.

Chapter Four

122

Table 4.3 Quantitative IRT tests

Parts 1 5 6

Spec

imen

Emis

sivi

ty d

eter

min

atio

n

PTT

Tran

smis

sion

pul

se IR

T

Far d

ista

nce

dete

ctio

n

Exci

tatio

n in

tens

ity

Hot A

ir ex

cita

tion

sour

ce

Refle

ctio

n er

ror e

stim

atio

n te

sts

Wat

er p

rese

nce

test

s

Long

pul

se IR

T (1

0s)

Long

pul

se IR

T (2

0s)

LTT

1 12 6 3 4 1 1 42 2 12 4 4 1 43 12 4 3 4 4 1 44 2 12 4 3 4 4 15 2 12 3 4 1 26 12 3 17 12 3 18 2 12 3 19 12 110 12 3 5 111 12 4 4 112 12 113 2 12 3 114 12 115 12 4 4 116 12 117 318 2 12 4 219 12 4 420 12 4 421 12 4 3 422 12 4 423 1224 12 4 3 425 1226 12 4 427 12 4 4S1 12 1 3 1 1 4S2 12 1 3 4 1 1 1 4S3 12 4 1 1 4S4 12 1 4 1 1 4S5 12 4 4IRT

tests 12 372 3 6 44 39 76 24 20 4 34

Total 634

4 72, 3 and 8

Quantitative IRT experimental laboratory program

123

Table 4.4 Specimens CFRP designs

4.5.1 Part 1: Emissivity value validation of the FRP using IRT

A non contact method was adopted to measure emissivity following the ASTM E 1933

standard (ASTM E 1933-99a 2005). As mentioned in Section 2.2.4.2 above, the

emissivity characterizes the surface’s ability to emit radiation. It can be defined as the

ratio of the radiation emitted from a surface to the radiation that would be emitted from

Spec

imen

CFRP materials Design purpose

1 Unidirectional Fabric CF130 Unbond defect detection, defect size accuracy2 Unidirectional Fabric CF140 Unbond defect detection, defect size accuracy3 Unidirectional Fabric CF130 Debonding detection,water presence detection4 Unidirectional Fabric CF130 Water presence detection

5 CFRP laminate Unbond defect detection (single and double CFRP layers), defect size accuracy,water presence detection

6 Unidirectional Fabric CF140 Unbond defect, debonding and delamination detection (single and double CFRP layers), defect size accuracy

7 Unidirectional Fabric CF140 and bi-directional Fabric 45

Unbond defect detection (single and double CFRP layers), Bi-CF detection

8 Unidirectional Fabric CF140 Unbond defect detection (single and double CFRP layers), effect of epoxy on top specimen surface

9 Unidirectional Fabric CF140 and CFRP laminate

Unbond defect detection (combination of fabric and laminate)

10 Unidirectional Fabric CF130 Cracks detection (single and double CFRP fabrics),water presence detection11 Unidirectional Fabric CF130 Narrow loading cracks detection12 Unidirectional Fabric CF130 Very fine loading cracks detection

13 Bi-directional Fabric 45Debond and delamination defect detection (single and double CFRP layers), Bi-CF detection, ,very rough surface preparation

14 Unidirectional Fabric CF130 Narrow loading cracks detection15 Unidirectional Fabric CF140 and CFRP

laminateCracks detection (CFRP fabrics and laminate),water presence detection

16 Unidirectional Fabric CF130 and CFRP laminate

Unbond defect and delamination detection (combination of fabric and laminates), defect size accuracy

17 CFRP laminate Water presence detection18 Unidirectional Fabric CF130 Cracks detection,water presence detection19 Unidirectional Fabric CF140 Debond detection20 Unidirectional Fabric CF140 Debond detection21 Unidirectional Fabric CF140 Debond detection22 Unidirectional Fabric CF140 Spall detection (single and double CFRP layers)23 CFRP laminate and bi-directional Fabric 45 Spall detection (laminate and fabric CFRP)24 Unidirectional Fabrics CF130 and CF140 Unbond defect detection (combination of fabrics), defect size accuracy25 Unidirectional Fabric CF130 Cracks detection,very rough surface preparation26 Unidirectional Fabric CF140 Debond detection27 Unidirectional Fabrics CF130 and CF140 Unbond defect detection (combination of fabrics), defect size accuracyS1 Unidirectional Fabric CF130 Bond defect detection, defect size accuracyS2 Unidirectional Fabric CF130 Debonding detection,water presence detection

S3 Unidirectional Fabrics CF130 and CF140Unbond defect and delamination detection (single and double CFRP layers), defect size accuracy

S4 CFRP laminate Unbond defect detection, defect size accuracyS5 Unidirectional Fabric CF130 and CFRP

laminateUnbond defect detection (single and double CFRP layers), defect size accuracy

Chapter Four

124

an ideal blackbody surface at the same temperature. The surface emissivity value plays

a major part in the accuracy of the IR surface temperature reading. The more precise the

determination of emissivity, the more accurate is the surface temperature acquired by

IRT NDT.

4.5.1.1 Test set-up

Portions of concrete-FRP surfaces in Specimens 2, 4, 5, 8, 13, and 18 were painted

black to simulate a blackbody which has a known emissivity value. According to the

ASTM E 1933 standard, concrete-FRP specimens are required to have a minimum of 10 oC temperature difference, hotter or cooler, than the ambient temperature (ASTM E

1933-99a 2005). An oven was used to heat specimens and to generate the 10 oC

difference between specimens and the room temperature. Figure 4.15 shows Specimen

13 inside the oven. The oven raised specimen temperatures in a homogenous pattern

varying from 25 oC to 10 oC but remaining well below the epoxy glass transition

temperature (Tg). IR thermograms were recorded immediately after the specimen was

removed from the oven. Natural cooling was monitored to exclude the measurement of

emissivity values when the difference in temperature between the specimen’s surface

and room temperature was less than 10 oC.

Figure 4.15 Concrete-CFRP specimen inside oven

Parametric adjustments of the data processing unit were performed according to the

thermal properties of the known painted part of the specimen. IR images were recorded

Quantitative IRT experimental laboratory program

125

and monitored on both modified and original portions of the specimens’ surfaces. The

known emissivity of the painted part was input in the IR software for the modified

painted portion. Then emissivity of the original surface was then obtained by adjusting

the input value of the emissivity until the IR camera detected the same temperature as

the modified painted surface. Figure 4.16 shows the original and modified painted parts

of Specimen 2. This process was repeated five times for each specimen and the average

emissivity reading was recorded.

Figure 4.16 Thermogram of Specimen 2 shows the modified surface for emissivity test

4.5.1.2 Emissivity values

Test results were recorded for Specimens 2, 4, 5, 8, 13, and 18. The IR software Image

Processor ProII was used to adjust the emissivity values on different areas of the

surface of interest. The measured emissivity values of the tested specimens at 10 ºC

above the calculated room temperature for the unpainted parts of the specimens varied

from 0.96 to 0.98 for the carbon FRP fabric and for the laminate FRP composite the

emissivity value was around 0.92, as shown in Table 4.5. This process was repeated five

times for each of the six tested specimens. The average emissivity readings for the

CFRP were 0.97 and 0.92 for fabric and laminate system respectively.

Painted area

Chapter Four

126

Table 4.5 Emissivity values of IRT tests

Specimen IRT run #1 IRT run #2 IRT run #3 IRT run #4 IRT run #5

2 0.98 0.97 0.98 0.97 0.98

4 0.96 0.97 0.96 0.95 0.97

5 0.89 0.93 0.91 0.92 0.92

8 0.97 0.96 0.96 0.97 0.96

13 0.96 0.98 0.97 0.97 0.98

18 0.97 0.96 0.96 0.97 0.96

Areas in most of the specimens with CFRP laminates were painted with a thin matt

black coating with an emissivity value of about 0.97 before performing the

thermographic investigations in order to calibrate and record each specimen’s surface

emissivity value.

Observation angles can affect emissivity values noticeably. All the emissivity

experiments in this part followed as far as possible the same angle that was used in most

of the IR experiments conducted in this study.

4.5.1.3 Summary

Knowledge of the precise surface emissivity is required to calculate the actual surface

temperature. In applying IRT NDT for the detection of subsurface defects, knowing the

accurate value of the emissivity is not essential to detect and/or characterize the defect,

or even determine the defect size. This because detection depends on the defect’s

thermal signal and/or thermal contrast, and both of these parameters are emissivity-

independent (i.e. both temperature above the defect and background temperature in the

defect-free area have the same emissivity). Nevertheless, it was necessary to measure

the emissivity values of both CFRP fabric and laminate to compare the surface

temperatures on different defects and to compare the surface temperature according to

experimental and finite element simulation results.

Quantitative IRT experimental laboratory program

127

4.5.2 Part 2: Using PTT to detect different bond defects

During the qualitative thermography tests presented in Chapter 3, it was noticed that all

the unbonded areas and debonding defects implanted under a single CFRP fabric were

detectable. However, defects beneath multiple layers were not easily identified. In this

part of the experimental program, all specimens were investigated thoroughly. A total

of 381 IRT tests was conducted on the 32 specimens. Each test involved analyzing 600

thermogram images. For each individual defect, the surface temperature above the

defect and the defect-free areas was recorded. This stage addressed the following:

detection of unbonding areas, debond detection, far detection and transmission IRT

observation.

4.5.2.1 Unbond defect detection

The detectability of unbond defect is influenced by several factors, including the size of

the defect, the depth of the defect, the number of composite material layers and the

properties of the CFRP composites and substructure. From the thermal images of

specimens, it is possible to detect and locate the unbond areas in different CFRP

systems. However, the aim of this part of the experimental quantitative IR program was

to develop a deeper understanding of the detection procedure.

Figure 4.17a demonstrates the IR images of Specimen 1. The thermogram results show

that the bond defects were very detectable under a CF 130 CFRP fabric composite. Six

regions of interest (ROIs) were localized as measurement functions at defects UB011,

UB012 and UB013 to analyze the IR reading of Specimen 1 thermograms. Figure 4.17a

illustrates the locations of the specimens’ subsurface defects. The ability to detect

defects is represented by the value of the thermal signal (ΔT) calculated from Equation

4.1. Figure 4.17b shows defect UB011 thermal signals versus time with the excitation

source positioned at different distances. From the results in Figure 4.17b, it can noted

that the unbonded thermal signal in this specimen followed Pattern A. The maximum

thermal signal showed immediately after the excitation source was turned off and the

shutter closed. The recommended IRT site design that shows the maximum thermal

signal was when the heat source was positioned at 0.5 m from the specimen’s surface

and the input thermal interval pulse wave was 5 s. IR tests performed at less than the 0.5

Chapter Four

128

m distance or more than the 5 s pulse duration showed an increase in the maximum

temperature on the CFRP surface to over 60 oC. During the IR test, the CFRP’s surface

temperature was monitored to ensure that it did exceed the glass transition temperature

of the epoxy. The mechanical properties of the resin matrix degrade and suddenly

change when its temperature increases beyond its glass transition temperature (Tg). The

Tg of the applications used in CFRP strengthening systems are in the range of 55 to 70 oC (CEB-FIP Bulletin 14 2001).

(a) Thermal image

(b) Defect UB011 thermal responses at different distances

Figure 4.17 Defects in Specimen 1

-1.00.01.02.03.04.05.06.07.08.09.0

10.011.012.0

0 10 20 30 40

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB011-1s at 50 cm

ΔT-UB011-1s at 70 cm

ΔT-UB011-1s at 100 cm

ΔT-UB011-1s at 120 cm

Quantitative IRT experimental laboratory program

129

As mentioned in Section 4.4 above, the size of the ROI to study the surface temperature

on the thermogram can vary. The most important factor in ROI size is that it should

represent enough pixels to characterize the temperature suitably on the ROI. Figure 4.18

shows the difference in the signals with two different ROI designs adopted for defect

UB011. As illustrated in Figures 4.18a and 4.18b, the sizes of the ROI rectangles

differed considerably. However, the differences in the signals collected from these two

ROIs were negligible at less than 1 oC, due to the selection of Design 1 of the ROI that

was set exactly on the unbonding area. The average temperature was collected for most

of the ROIs in this study; however, some defects were designed not to have equal

degrees of deterioration, such as the debonding in Specimens 3, 26 and S3. These

defects were designed with ROIs that collected the maximum temperature within the

ROI rectangle. It was also found that by reducing the size of the ROI, the difference

between choosing an average or maximum ROI rectangle will be eliminated. All of the

ROIs applied to the specimens in this research were chosen very carefully to represent

the artificial defect type. The sizes of these ROIs differed from flaw to flaw. Small

defects were designed with ROIs that covered most of the defect to supply enough

pixels in the ROI area. Larger defects were set with ROIs not covering the entire defect,

and only a reasonable ROI within the defect area was selected. However, the most

critical issue was to select the area of ROI that showed the defect clearly.

(a) ROI1 design (b) ROI2 design

Chapter Four

130

(c) Signals of ROI1 and ROI2 designs of UB011

Figure 4.18 Defect UB011 thermal responses at different ROI sizes

Figure 4.19 reveals that even with a very short pulse duration of 1 second, the IRT

detection system is still able to read differences of more than 12 oC between the defect

area and the surrounding defect-free area for the single CF130 fabric layer. Further

analysis shows that by increasing the input heat flux, the maximum thermal signal rises

lineally, as shown in Figure 4.20. The rate of (ΔTmax / input heat flux) increases with the

increase in heating pulse interval (Tashan and Al-Mahaidi 2012). The results in Figure

4.20 show the input heat flux required to attain the desired thermal signal in the IR tests.

The maximum thermal signal of 5 s pulse interval is described by Equation 4.3 where q

is the input heat flux in watts per square metre.

-2.0

2.0

6.0

10.0

14.0

18.0

22.0

0 10 20 30 40 50 60

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB011-5s at 50 cmΔT-UB011-1s at 50 cmΔT-UB011-1s at 50 cm-ROI2ΔT-UB011-5s at 50 cm-ROI2

Quantitative IRT experimental laboratory program

131

ΔT(q)max = 0.032 q – 5.746 Equation 4.3

Figure 4.19 Defect UB011 thermal responses at different pulse intervals

Figure 4.20 Heat flux versus maximum thermal signal in Specimen 1 for different pulse

intervals

-2.0

2.0

6.0

10.0

14.0

18.0

22.0

0 10 20 30 40 50 60

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB011-1s at 50 cmΔT-UB011-3s at 50 cmΔT-UB011-5s at 50 cm

0

100

200

300

400

500

600

700

800

900

1000

0 5 10 15 20 25

Hea

t Flu

x (w

/m2 )

∆Tmax (oC)

1 s

3 s

5 s

Chapter Four

132

Similar equations connecting the output thermal responses with the input applied heat

flux intensity can assist the thermographer to design appropriate IRT test configurations

in terms of detectability level.

The detection of unbond defect under different kinds of carbon fabrics was investigated

with Specimens 24 and 27. Both specimens were strengthened with unidirectional

CF130 and CF140 CFRP MBrace fabrics as shown in Figure 3.11. Active IRT PTT was

performed on these specimens to examine the effect of changing CFRP physical

properties (i.e. fabric thickness, fabric directions) on the thermal detection of the same

defects.

Four ROIs where analyzed thermally in Specimen 24’s defects. The first two regions

were to study defect UB241 which was embedded under CF130 CFRP type, as shown

in Figure 4.21, while the other ROIs were assigned to record the thermal response of

defect UB242 implanted in the CF140 CFRP fabric-concrete bond zone.

Figure 4.21 Defects in Specimen 24 thermogram

The results in Figure 4.22 show that for the same pulse duration time, the thermal signal

detection is enhanced by increasing the input heat flux. The thermal signals of Specimen

Quantitative IRT experimental laboratory program

133

24 defects follow Pattern A with very high values for both defects. The UB241 defect

under the CF130 fabric shows a considerably higher ΔT (about 25% more) compared to

the UB242 signal when the heat source was applied at 50 cm with 3 s heating interval.

The difference between the CF130 and CF140 defects was reduced to less than 10%

when different heating intervals were applied, as shown in Figure 4.22b for heating at

50 cm. Both defects had almost the same behaviour after the heat source was turned off.

The thermal signal faded 20 s from the beginning of the IR test when the heating was

applied for 3 s. However, this fading duration is related to different parameters involved

pulse duration and substructure material. Figure 4.22b shows that signals for both

UB241 and UB242 faded after 10 s when the pulse was at 1 s. When the pulse was

longer, at 5 s, the signals recorded zero.

The results of Specimens 24 and 27 for the detection of the same unbonded area under

different CFRP fabric types confirm that the detection of defects is enhanced by the

reduced CFRP composite thickness. The detection of both UB241 and UB271 detection

was better than UB242 and UB272, because the CFRP fabric above the first two faults

was CF130 which is 33 % less thick than the CF140 on UB242 and UB272.

(a) 3 seconds pulse duration, heat source at 50 and 70 cm

-2

2

6

10

14

18

0 5 10 15 20

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

UB242- 3s at 50cmUB241- 3s at 50cmUB242- 3s at 70cmUB241- 3s at 70cm

Chapter Four

134

(b) 1 and 5 seconds pulse durations

Figure 4.22 Infra-red signals of Specimen 24 defects

The results from the IR analysis of Specimen 24 confirm that, by increasing the input

heat flux, the maximum thermal signal rises lineally, as shown in Figure 4.23. For the

CFRP CF130 used in UB241, similarly to Specimen 1, the rate of (ΔTmax / Input heat

flux) increases with the increase in heating pulse interval. However, for pulses of 1 s the

rate was not perfectly linear, due to the short time available to capture the IR image and

the few IR frames recorded during the 1 s pulse length. Figure 4.23a shows these

increasing. The results in Figure 4.23b present the input heat flux versus maximum

thermal signal for defect UB242. The slopes of the linear relationships between the heat

and the maximum signals do not change for this defect and follow the same increase

rate. That could be due to the CFRP type of CF140 which have thicker section compare

to the CF130, and have different fabrics waving pattern. However, maximum signal

during the 1 s pulse duration shows also a non perfect linear behaviour that was pointed

up in Figure 4.23a. Figure 4.23 shows that the maximum signals in CF140 defects are

lower than defects under CF130 CFRP fabric. CFRP CF140 is thicker than CF130,

which allow the layer to transfer the heat slightly faster and then register lower signals.

This lower signals result might be also due to the different waving CFRP patterns and

-2

2

6

10

14

18

22

0 5 10 15 20

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

UB242- 5 s at 50 cmUB241- 5 s at 50 cmUB242- 1s at 50cmUB241- 1s at 50cm

Quantitative IRT experimental laboratory program

135

the choosing of the ROI that can effect on the IR image analysis. This can highlight the

task’s hardness of making comparing between different CFRP materials.

From Figure 4.23 it can be noted that for CF140 type pulses with heat flux less than 450

W/m2 are produce ΔTmax less than 2.5 oC, which is very small temperature to well

recognition of a defect. While for the CF130 the minimum input heat that can provide

more than 2.5 oC as thermal signal is 300 W/m2. The relation between the input heat

flux and the pulse interval are affecting by different parameters involve the angle of the

lamp, and the ambient temperature. For that reason, in the concrete -CFRP fabric

system, to provide a well observed detection, heat wave injection with less than 500

W/m2 is not recommended. Usually this 500 W/m2 wave is generated when the

excitation lamp located at 1.2 m from the test object.

(a) Defect UB241

0

300

600

900

1200

1500

1800

0 5 10 15 20

Hea

t flu

x (w

/m2 )

∆Tmax (oC)

UB241-1sUB241-3sUB241-5s

Chapter Four

136

(b) Defect UB242

Figure 4.23 Heat flux versus maximum thermal signal in Specimen 24 for different pulse intervals

Unbonded area defects under multiple CFRP fabric layers were examined by PTT IRT

on Specimen 6. Defects UB063 and UB064 were identified clearly. Defect UB064

(under double CF140 sheets) had a smaller thermal signal compared with UB063.

Figure 4.24 indicates that, by increasing the distance between the heat source and the

investigated surface, the ΔTmax ratio of a defect under a single CFRP layer to a defect

under a double layer increases. The maximum thermal signal detection under a single

CFRP layer is just above double that of the of ΔTmax UB064 beneath double CFRP

layers when the heat source is positioned at 50 cm. By increasing the heat excitation

source distance to 1.2 m, the ratio of ΔTmax between single and multi layer rises to 400

%, as shown in Figure 4.24.

0

300

600

900

1200

1500

1800

0 5 10 15 20

Hea

t flu

x (w

/m2 )

∆Tmax (oC)

UB242-1s

UB242-3s

UB242-5s

Quantitative IRT experimental laboratory program

137

(a)

(b)

Figure 4.24 Thermal signals of defects in Specimen 6: (a) UB063, (b) UB064

Equation 4.2 was used to calculate the thermal contrast of Specimen 6 defects. Figure

4.25 shows the IR contrast results with the heat source located at 50 cm and pulses of 5

s were injected. As shown in the figure, the noise level in the contrast values is low until

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

0 20 40 60 80

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB063-5s at 50cm

ΔT-UB063-5s at 70cm

ΔT-UB063-5s at 120cm

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0 20 40 60 80

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB064-5s at 50cmΔT-UB064-5s at 70cmΔT-UB064-5s at 120cm

Chapter Four

138

it reaches the maximum contrast Cmax level when the excitation heat lamps are turned

on. Immediately after the lamps are turned off, the level of noise increases gradually

until the test ends. Figures 4.25a and 4.25b demonstrate the difference between C values

at different excitation distances with the same pulse interval. The figure show that, the

noise level is decreased by increasing the distance between the lamps and the

investigated surface. To determine the maximum contrast and its corresponding time,

the contrast smooth curves were calculated as shown in Figure 4.25.

(a)

(b)

Figure 4.25 Thermal contrast of Specimen 6 with 5 s pulse: (a) excitation at 50 cm, (b) excitation at 120 cm

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

6.00

0 50 100 150

Con

trast

Time (s)

UB063-5s at 50cm

UB064-5s at 50cm

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 50 100 150

Con

trast

Time (s)

UB063-5s at 120cm

UB064-5s at 120cm

Quantitative IRT experimental laboratory program

139

Defect UB063 contrast signals are shown in Figure 4.26 for 5 s PTT applied from

different distances. The maximum contrast values are very high for these heating waves.

Maximum thermal contrast reaches a value of 5.71 when the excitation source is

mounted 50 m from the tested specimen. The behaviour of the contrast responses

follows the same pattern for the same pulse period with different lamp distances. When

the lamps’ location is fixed, the pattern of contrast responses at different pulse durations

shows high noise when the pulse duration is short, as demonstrated in Figure 4.27. The

contrast wave time decay is increased by the increase pulse length. Figure 4.26

demonstrates the value of C reaches 1.5 for defect UB063 after 29 s, 31 s, 38 s, and 59 s

from the IR test commencement when the lamps are positioned at 50 cm, 70 cm, 100

cm, and 120 cm respectively.

Figure 4.26 Contrast of UB063 with 5 s pulses at different distances

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

6.00

0 50 100 150

Con

trast

Time (s)

UB063-5s at 50cm

UB063-5s at 70cm

UB063-5s at 100cm

UB063-5s at 120cm

Chapter Four

140

Figure 4.27 Contrast of UB063 with 1 m distance at different pulses

Unbonding artificial defects under CFRP laminates composite systems were

investigated in Specimen 5. Figure 4.28 illustrates these defects. As shown in the figure,

unbonding defect UB051 covered by a single layer of the laminate is easily detected.

UB052 with two CFRP laminates is a little harder to detect compared with UB051.

Figure 4.28 Specimen 5 unbonding artificial defects

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

0 50 100 150

Con

trast

Time (s)

UB063-5s at 100cm

UB063-3s at 100cm

UB063-1s at 100cm

Quantitative IRT experimental laboratory program

141

By increasing the distance of the heat source, the IR reading are weakened. However,

the technique shows very good capability in the detection of CFRP laminate defects.

The differences between the readings in single and double FRP laminate layers are

illustrated in Figure 4.29. The thermal signals of Specimen 5 shown in Figure 4.29a

illustrate Pattern A for defect UB051 under a single layer of CFRP laminate. However,

the maximum signal time is not exactly after the end of the pulse. From the figure it can

be seen that the tmax is located 3 to 5 seconds from the end of the pulse (when the lamp

was turned off). This relates to the speed of the heat wave transfer within the laminate.

The conductivity factor of the laminate allows the heat wave to move more slowly than

in the fabric which makes the maximum ΔT record a short time after the pulse ends. By

increasing the number of attached CFRP layers and increasing the distance of the

excitation system to more than 1 m, the signal drops and the thermal response pattern

converts from Type A of Figure 4.14, to Type B in Figure 4.29b. This may be due to the

heat wave transmission time, as in the double CFRP layers time is needed for the heat

wave to cross the top CFRP layer and reach the defect under the next CFRP laminate.

(a)

0.0

2.0

4.0

6.0

8.0

10.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB051-5s at 50cmΔT-UB051-5s at 70cmΔT-UB051-5s at 100cmΔT-UB051-5s at 120cm

Chapter Four

142

(b)

Figure 4.29 Thermal signal of Specimen 5 at 5 s pulse interval: (a) defect under a single CFRP laminate, (b) defect under double CFRP laminates

Figure 4.30 indicates the maximum thermal signals recorded during the IR tests on

Specimen 5 unbond defects (UB051 and UB052) from different distances and for a

series of pulse durations. The maximum thermal signal for each defect shown in Figure

4.30 was observed 3 s to 5.3 s after the end of the pulse heat wave injection for the

single layer defect (UB051). The maximum response time of the second defect (UB052)

varied considerably. It reached a local maximum at the same time as UB051, and then

reached a local minimum value of the thermal signal and then attained a maximum

thermal signal after more than 50 s from the end of the pulse. It was noticed that this

behaviour was most common when the excitation lamps were positioned more than 1 m

from the specimen, as shown in Figure 4.31. The variation between these thermal

signals is due to two reasons: (i) the implanted defect’s depth. Decreasing the defect’s

depth raises the thermal signal. (ii) the non-homogenous behaviour of the injected heat

wave (Tashan and Al-Mahaidi 2012). The heat wave was designed to hit the centre of

the specimen. The figure highlights the enhancement in the thermal maximum reading

between these two artificial defects. However, the thermal signals shown in Figure 4.31

are undesirable values to identify and confirm defect detection. Thermal signal values of

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB052-5s at 50cmΔT-UB052-5s at 70cmΔT-UB052-5s at 100cmΔT-UB052-5s at 120cm

Quantitative IRT experimental laboratory program

143

less than 1 oC can easily mislead the location of the defect. Changing the position of the

ROI to determine the thermal response with the same defect area can lead to a different

thermal reading of more than 1 oC. For that reason, signals with values of 1 oC and less

are not considered good identifications defects.

For that reason, thermal signals are not reliable for defects under CFRP double

laminates when the excitation positioned at 1 m and more, as shown in Figure 4.30.

Figure 4.30 Specimen 5 unbonded areas maximum thermal signals recorded at different

distances

0

2

4

6

8

10

12

5070

100120

ΔTmax (oC)

Excitation distance (cm)

UB051-5s UB051-3sUB051-1s UB052-5s UB052-3s UB052-1s

Chapter Four

144

(a)

(b)

Figure 4.31 UB052 signals at 1 and 1.2 m with different pulses

A ROI line was considered across Specimen 9 unbonded defects, as shown in Figure

4.32. The UB091 and UB092 faults were inserted in the specimen as demonstrated in

Figure 3.11-9. The line profile thermal response is presented in Figure 4.33, which

shows how big the difference is in the acquired surface temperatures between the single

layer defect UB091 and UB092 that is covered by two different CFRP layers (fabric and

laminate). As shown in Figure 4.33b, UB092 continues to record higher temperature

compared to the defect- free area over that laminate.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB052-5s at 100cmΔT-UB052-3s at 100cmΔT-UB052-1s at 100cm

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB052-5s at 120cmΔT-UB052-3s at 120cmΔT-UB052-1s at 120cm

Quantitative IRT experimental laboratory program

145

The UB091 defect recorded the maximum temperature immediately after the end of the

pulse of one second. The response of the UB092 defect was different in terms of the

timing. The UB092 registered its maximum thermal signal 8.5 s from the pulse

injection. Figure 4.34 highlights the differences in the thermal signals of Specimen 9

defects. The detectability under a single CFRP fabric layer was 130 % greater than for

the two different layers for different pulse durations, as shown in Figure 4.34. The

signals for the UB091 defect faded faster than those for UB092. The rates of signal

fading are much smaller in defects with multi-layers than a single layer. The UB092

thermal signal still reads about 2 oC after 90 s, while the UB091 signal minimized to

zero after 30 s from the start of the IR test, as shown in Figure 4.34.

Figure 4.32 Line ROI of Specimen 9

Chapter Four

146

(a) Defects of Specimen 9 surface temperatures

(b) Three-dimensional profile of ROI line

Figure 4.33 Line temperature profile of Specimen 9

19.0

24.0

29.0

34.0

39.0

44.0

130 180 230 280

Tem

pera

ture

(o C

)

Pixles

6 s8.5 s10.25 s13.5 s26.75 s

UB091 UB092

0510

1520

2530

3540

20.0

30.0

40.0

50.0

151

101Time (s)

Surface Temperature (oC)

ROI 1-pixels

UB092

UB091

Quantitative IRT experimental laboratory program

147

Figure 4.34 Specimen 9 defect signals

Figures 4.35 to 4.37 illustrate the IR information on the unbonded defect in Specimen

16. From the thermogram analysis all the thermal signal pulses and contrasts are of

Type B. Figure 4.35 shows the differences between thermal signals at 1 s and 5 s

durations for the UB161 unbonded area. Generally, the signals under two different

CFRP layers are small, and the maximum ΔT recorded for UB161 is 3 oC. By

increasing the excitation source distance and decreasing the pulse duration, the signal is

around 1 oC, which is a weak distinguishing value. The tmax which corresponds to ΔTmax

in this defect was recorded again not directly after the pulse ended (when the lamps

were turned off). This is due to the laminate’s thermal properties which allow it to delay

the heat wave movement inside the laminate. The values of the contrast for this defect in

this specimen show a noticeably high noise level, as shown in Figures 4.36 and 4.37,

possibly due to the top CFRP fabric layer reflection error, since the top fabric layer was

installed over two laminates and created sharp edges on the surface. Reflections on

these edges were very hard to eliminate during the setting of the IR test. However, the

contrasts in the long pulse duration still have larger values.

0

5

10

15

20

25

0 30 60 90

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

UB091-1s at 50cmUB092-1s at 50cmUB091-5s at 50cmUB092-5s at 50cm

Chapter Four

148

Figure 4.35 Specimen 16 thermal signals

Figure 4.36 Specimen 16 thermal contrasts at 5 s pulse

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 20 40 60 80 100 120

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB161-5s at 50cmΔT-UB161-5s at 100cmΔT-UB161-1s at 50cmΔT-UB161-1s at 100cm

-0.50

1.50

3.50

5.50

7.50

9.50

11.50

0 20 40 60 80 100 120

Con

trast

Time (s)

C -UB161-5s at 50cm

C -UB161-5s at 100cm

Quantitative IRT experimental laboratory program

149

Figure 4.37 Specimen 16 thermal contrasts at 1 s pulse

One of the major parameters that influence the IR response is the substructure material.

Similar defects were implanted with steel and concrete substrates strengthened with

CFRP laminate and fabric and tested with IRT NDT (Tashan and Al-Mahaidi 2012).

Figure 4.38 indicates the differences in the values and shapes of the thermal signals for

the same bond defects and sizes on two different materials. Specimen 1 and S1 were

implanted with the same UB011 and UBS11 defects. The figure below shows the

thermal results of these two defects at 50 and 100 cm and for 5 s intervals. In general,

the steel substrate shows lower signals compared to the concrete host structure for the

same pulses. The concrete material also shows better detection with low heating when

the excitation system is 1m from the investigated surface. This is because the thermal

conductivity factor of the concrete is relatively low with respect to the steel conductivity

factor, which causes the heat to be trapped more in the concrete than the steel. However,

because of capturng more heat with extensive pulse duration (pulse with 5 s injection)

the steel defect recorded higher signals than the CFRP-concrete defect, as shown in

Figure 4.38a.

By decreasing the pulse interval of the applied heat wave to 1 s, the difference between

the concrete and steel subsurface defects becomes greater, as shown in Figure 4.38b.

The detectability in concrete is one third greater than the signal in steel for the same

heating participation at 50 cm and for short 1 s pulse injection. It is understandable why

-0.50

0.50

1.50

2.50

3.50

4.50

0 20 40 60 80 100 120

Con

trast

Time (s)

C -UB161-1s at 50cm

C -UB161-1s at 100cm

Chapter Four

150

the defect in the steel-CFRP bond zone has a thermal signal that fades earlier than to the

concrete-CFRP system, because steel’s conductivity is higher than that of concrete.

(a) Pulse duration of 5 s

(b) Pulse duration of 1 s

Figure 4.38 Defects: UB011 and UBS11 signals

-1.0

4.0

9.0

14.0

19.0

24.0

0 5 10 15 20 25

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB011-5s at 50cmΔT-UBS11-5s at 50cmΔT-UB011-5s at 100cmΔT-UBS11-5s at 100cm

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

0 5 10 15 20 25 30

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB011-1s at 50cmΔT-UBS11-1s at 50cmΔT-UB011-1s at 100cmΔT-UBS11-1s at 100cm

Quantitative IRT experimental laboratory program

151

The same analyses were conducted on Specimens 5 and S4 unbonded defects under

CFRP single laminates, as shown in Figure 4.39. For 5 s pulse duration the detection of

the thermal response for bond defect in the CFRP fabric bond surface is better than the

flaw covered by the CFRP laminate for both concrete and steel subsurface materials.

The differences between the concrete and steel substrates in Figure 4.39a are greater

than the differences in Figure 4.38a, because of the low rate of heat wave decay in the

laminate-concrete system. Similar to the signal behaviour in Figure 4.38b, the results

shown in Figure 4.39b imply that by shortening the pulse duration the gap between two

systems is bridged.

The IR results in Figures 4.38 and 4.39 confirm that laminate-CFRP system signals are

detectable for longer compared to CFRP fabric sheets. For example, laminate system

signals for 5 s pulse duration are extended to about 140 s, while the CFRP fabric signals

evanesce after less than 30 s. The results also show higher signals for concrete substrate

than steel.

Chapter Four

152

(a) Pulse duration of 5 s

(b) Pulse duration of 1 s

Figure 4.39 Defects: UB051 and UBS41 signals

4.5.2.2 Debonding and delamination detectability

The ability of IRT to detect debond areas was investigated in Specimens 3, 26, S2, 19,

20 and 21. Specimen 3 was constructed with an artificial debond defect as shown in

Figure 3.11-3. The debonding defect was very detectable for all applied heating

intensities and durations. The thermal image in Figure 4.40 exhibits the defect shape

and the severity of the debonding within the defect zone. In addition, it shows the heat

flux sensor location on the surface to record the heat intensity from the excitation lamp.

-1.0

1.0

3.0

5.0

7.0

9.0

11.0

0 20 40 60 80 100 120 140

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB051-5s at 50cmΔT-UBS41-5s at 50cmΔT-UB051-5s at 100cmΔT-UBS41-5s at 100cm

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 20 40 60 80 100 120

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB051-1s at 50cmΔT-UBS41-1s at 50cmΔT-UB051-1s at 100cmΔT-UBS41-1s at 100cm

Quantitative IRT experimental laboratory program

153

Figure 4.40 Thermogram of Specimen 3

The results of the PTT tests of Specimen 3 are shown in Figure 4.41. The thermal

signals of the debonding area in this figure are similar to the thermal signals in the most

unbonded area, where the signal follows Pattern A shown in Figure 4.14. When the

excitation system was located 50 cm from the specimen’s surface, the maximum

thermal responses were the same for both pulses of 3 s and 5 s (see Figures 4.41a and

4.41b). The signal patterns after the peak point (when the lamps were turned off) have

less negative slopes as the lamps are positioned further away. That is due to the heat

distribution on the explored surface which becomes more homogeneous when the lamps

are mounted further away and the signal raises are smaller. Shorter pulses with 1 s show

the same pattern for the signals but with smaller ΔTmax as shown in Figure 4.41c. The

difference in ΔTmax of 1 s pulse recorded when the lamps were positioned at 1 and 1.2 m

was less than 0.6 oC. Thermal IR configuration with the heat lamps positioned at 1 m

and more and subjected to 1 s pulse shows very small thermal signals which are not

sufficient to be used in debonding detection.

Chapter Four

154

(a)

(b)

(c)

Figure 4.41 Specimen 3 debonding area signals: (a) Pulse is 5 s, (b) pulse is 3 s, (c) pulse is 1 s

0

5

10

15

20

25

30

0 20 40 60 80 100 120 140

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

DB031-5s-50cmDB031-5s-70cmDB031-5s-100cmDB031-5s-120cm

0

5

10

15

20

25

30

0 20 40 60 80 100 120 140

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

DB031-3s-50cmDB031-3s-70cmDB031-3s-100cmDB031-3s-120cm

0

1

2

3

4

5

6

7

8

9

10

0 20 40 60 80 100 120 140

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

DB031-1s-50cmDB031-1s-70cmDB031-1s-100cmDB031-1s-120cm

Quantitative IRT experimental laboratory program

155

Figure 4.42 presents the three-dimensional profile of the debonding fault in Specimen 3.

The hot spot appears with temperatures increasing gradually towards the middle of the

debonding area where the trapped heat reaches its peak (Tashan and Al-Mahaidi 2009).

This is a clear indication of the absence of bonding at this implanted deficiency. The 3-

D profile of the temperature variation gives an indication of the severity of debonds

within defect zones. The reflections on the CFRP fabric surface can mislead the reading

of the thermograms, but software filters can be used to reduce these reading errors. A

Gaussian filter (5×5) shows good results in eliminating the spiky errors when applied to

the 3D IR shown in Figure 4.42a. As shown in Figure 4.42b, the Gaussian filter alters

slightly the maximum temperature of the IR image. As shown in Figure 4.42b, the peak

temperature in the debond area was shifted by 0.8 oC.

(a)

Chapter Four

156

(b)

Figure 4.42 Three dimensional profile of DB031: (a) before applying Gaussian filter, (b) after applying 5 ×5 Gaussian filter

Specimen 26 was fitted with a fabricated debonding area similar to Specimen 3’s

artificial fault. However, the CFRP fabric used in Specimen 26 was Type CF140, while

Specimen 3 was strengthened with CF130. The differences in the CFRP fabric

properties of these two specimens and in the debonding area sizes that were generated in

a random way lead to different IR results for these two specimens. The maximum

thermal signal for DB031 is three times that for DB241, as shown in Figure 4.43.

Moreover, they follow different curve patterns, as DB261 shows Pattern B, whilst

DB031’s defect signal shows Pattern A.

For different pulse durations with different excitation source distances, Specimen 26

shows the same Pattern B signals. Figure 4.44 illustrates these signals. The gap between

the maximum ΔT is bridged by decreasing the input heating and shortening the duration

of the heating pulses. The pulse of 5 s from 50 cm in Figure 4.44 was noticed to have a

signal of 2.5 oC even after the end of the thermal test at 100 s.

Figure 4.45 confirms that the contrasts are noisier than the signals. For that reason, the

contrast responses required more smoothing in the construction of Figure 4.45. From

Quantitative IRT experimental laboratory program

157

the results, it is observed that the noise level is high when the surface receives more heat

from the near lamps, as shown in the difference between the contrasts after the end of

the pulse in Figure 4.45a. At 50 cm excitation distance, the smoothed maximum contrast

Cmax decreases from 8.7 when the pulse is applied for 5 s to 7.2 for 1 s pulse interval.

The C values shown in Figure 4.45b for 50 cm and 1 s pulse durations display more

noise compared to the 5 s pulse length shown in Figure 4.45a.

Figure 4.43 Specimens 3 and 26 debonding responses

Figure 4.44 Debond DB261 signals

-2.0

3.0

8.0

13.0

18.0

23.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-DB261-5s at 50cm

ΔT-DB031-5s at 50cm

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-DB261-5s at 50cmΔT-DB261-5s at 70cmΔT-DB261-1s at 50cmΔT-DB261-1s at 70cm

Chapter Four

158

(a)

(b)

Figure 4.45 Contrast of DB261: (a) at 5 s pulse, (b) at1 s pulse

Debonding in steel was investigated by testing Specimen S2. Figure 4.46 describes the

DBS21 thermal signals captured at 5 s pulse phase. All thermal responses in steel show

a Type A thermal signal pattern. The ΔTmax is affected considerably by heat flux

-1.00

1.00

3.00

5.00

7.00

9.00

11.00

13.00

15.00

0 50 100 150

Con

trast

Time (s)

C -DB261-5s at 50cm

C -DB261-5s at 70cm

-1.00

1.00

3.00

5.00

7.00

9.00

11.00

0 50 100 150

Con

trast

Time (s)

C -DB261-1s at 50cm

C -DB261-1s at 70cm

Quantitative IRT experimental laboratory program

159

intensity level. By changing the location of the heat source from 50 cm to 70 cm, the

maximum thermal signals drop by half approximately, as shown in Figure 4.46. The

debond defect inserted in the steel-CFRP system fabric has higher ΔTmax compared with

the corresponding defect in the concrete-CFRP system. However, after reaching the

peak point at ΔTmax the signal of the debond defect attached to steel reduces sharply

compared to the defect in concrete-based structure.

Figure 4.46 Steel Specimen 2 thermal signals

Figure 4.47 offers the comparison between DB031 and DBS21 defect signals. From this

figure, it can be seen that the difference between thermal signals fading in concrete and

steel is dependent on the pulse duration.

-2.0

3.0

8.0

13.0

18.0

23.0

28.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-DBS21-5s at 50cmΔT-DBS21-5s at 70cmΔT-DBS21-5s at 100cmΔT-DBS21-5s at 120cm

Chapter Four

160

Figure 4.47 Comparison of Specimens’ 3 and S2 debonding signals

The polynomial smoothing contrasts of DBS21 are shown in Figure 4.48. The Cmax is

higher compared to DB031 and DB261, due to the larger size of the air pocket within

the Specimen S2 defect zone. The contrasts for different pulses show similar behaviour

with different intensities. The time when Ctmax reaches the peak of the contrast was

found to be immediately after the end of the pulse when the lamps were turned off. The

noise level increased gradually towards the end of the IR test.

-2

3

8

13

18

23

28

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-DB031-5s at 50cmΔT -DB031-5s-100cmΔT-DBS21-5s at 50cmΔT-DBS21-5s at 100cm

Quantitative IRT experimental laboratory program

161

Figure 4.48 Thermal contrast for Specimen S2

Defects inserted in bi-directional CFRP fabric show similar thermal signals to defects in

uni-directional fabrics. Figure 4.49a shows the thermal signals for the debonding defect

in Specimen 13 at pulse intervals of 1 s, 3 s, and 5 s recorded when the lamps were at

distances of 0.5 m, 0.7 m, 1 m, and 1.2 m. From the figure it can be concluded that even

with the greater thickness of the TYFO BCC (± 45o) fabric at 0.55 mm, the technique

still provides good thermal signals. As shown in Figure 4.49b, the linear relationship

between input heat flux and maximum signal is confirmed for this type of bi-directional

fabric.

-6.00

-4.00

-2.00

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0 50 100 150

Con

trast

Time (s)

Poly. (C -DBS21-5s at 70cm)

Poly. (C -DBS21-3s at 70cm)

Poly. (C -DBS21-1s at 70cm)

Chapter Four

162

(a)

(b)

Figure 4.49 Defect DB131 (a) thermal signals at different pulse and distances, (b) heat flux versus maximum thermal signal for DB131 at different pulse intervals

Debonding with different defect thicknesses was investigated in Specimens 19, 20 and

21. Table 4.6 summarizes the maximum signal detection for all debonding artificial

0

2

4

6

8

10

12

14

16

18

20

0 30 60 90 120 150

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

DB131-1s at 50

DB131-1s at 70

DB131-1s at 100

DB131-1s at 120

DB131-3s at 50

DB131-3s at 70

DB131-3s at 100

DB131-3s at 120

DB131-5s at 50

DB131-5s at 70

DB131-5s at 100

DB131-5s at 120

0

200

400

600

800

1000

1200

1400

0 5 10 15 20 25

Inpu

t Hea

t Flu

x (W

/m2 )

∆Tmax (oC)

DB131- 1 sDB131- 3 sDB131- 5 s

Quantitative IRT experimental laboratory program

163

defects that were inserted with different thicknesses in these specimens. Due to the

small thickness of air pockets in defects DB191 and DB192, which were less than 0.25

mm, it was impractical to remove the epoxy material totally from the debond zone and

no air pocket were generated within the debonding surface. The epoxy works as a

bridge in these two defects which transfers the heat from the CFRP fabric to the

concrete subsurface. For this reason, the signals in these defects have higher values

compared to other corresponding debond defect signal values in Table 4.6. From the

analysis of Specimen 19, it can be seen that debonding with less than 0.25 mm thickness

works in an exceptional way. Because of the narrow debonding, there is no lack of

epoxy within the debonding. This means that the epoxy layer thickness was increased in

these defects which produced higher ΔT within the debonding regions. This kind of

debonding defect which arises with no air pocket within the areas does not act in a

similar way to fully debonded or fully unbonded defects.

Debond defect DB201 has a thickness close to that of DB211, and both defects show

similar maximum signal values, as shown in Table 4.5. However, DB211 with a

thickness 0.1 mm larger than DB201, shows as expected, a slightly larger signals of the

ΔTmax. The thickness of DB212 defect is double that of DB211, and a difference in

maximum limit signals between these two defects was noticeable. The average

enhancement in detection between Specimen 21 debond areas was about 285% at 1 s

pulses, 180% at 3 s pulses and 159% at 5 s pulses. Although the detection improvement

at 1 s was high, the values of maximum thermal signals were very low.

Chapter Four

164

Table 4.6 Debonding defects summary

Debonding ID

defects and

thickness

(mm)

ΔTmax (oC)

at 50 cm 70 cm 100

cm

120

cm

DB191(0.1)

1 s 9.4 7.1 4 2.7

3 s 16.4 12.5 6.9 4.8

5 s 19.4 16 8 5.6

DB192(0.25)

1 s 12.7 6.7 3.1 1.9

3 s 20.9 11.3 4.9 3.3

5 s 24.5 12.2 5.6 3.7

DB201(0.4)

1 s 3.2 1.1 0.8 0.5

3 s 7 4 2 1.1

5 s 10.5 7 3.9 1.9

DB211(0.5)

1 s 3.2 1.9 1 0.7

3 s 7.9 4.6 2.6 1.8

5 s 11.9 7.2 4.3 2.7

DB212(1)

1 s 9.2 5.7 2.9 1.9

3 s 16.1 8.8 4.6 2.9

5 s 21.4 12.2 6.3 3.8

The ability of the IRT to identify delamination defects was studied by testing Specimens

16, 6, 7, and 13. Specimen 16 was constructed with an artificial delamination defect, as

shown in Figure 3.11-16. In spite of the three CFRP composite layers on the surface of

this concrete specimen, the delamination defect between the double FRP laminates was

very detectable for applied heating intensities imposed for different pulse durations. The

thermal image in Figure 4.50a exhibits defect DL162’s shape and location in Specimen

16. Figure 4.50b show that the signal was more than 2.5 oC, even for short pulses at 1 s

from half a metre. The ΔTmax with exposure of the CFRP surface for 5 s was just below

5 oC, which is a good signal for the location of potential flaws in the bonding zone. It

was noticed that, by reducing the input heat wave when the lamps are positioned around

Quantitative IRT experimental laboratory program

165

1 m, the signals are weak to unacceptable. The signals for pulse intervals from 1 s to 5 s

at 1 m show very low values at less than 0.5 oC, due to the effect of installing multi-

CFRP layers above the delamination DL162 which hinder heat wave transmission and

produce shallow thermal responses.

The thermal contrasts calculated during the IR analyses of delamination under multi-

layers of CFRP composites follow Pattern B as shown in Figure 4.14. Figures 4.50c and

4.50d highlight contrast registers its maximum values almost at the end of the IR test.

This makes the value of the contrast unreliable, especially with the amount of noise that

increases towards the end of the IR test. As shown in Figure 4.50c, the maximum

contrast captured for this defect was 3.6. However, due to the unacceptable noise level

this C value is inappropriate.

(a)

Chapter Four

166

(b)

(c)

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

0 50 100 150

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-DL162-5s at 50cmΔT-DL162-5s at 100cmΔT-DL162-1s at 50cmΔT-DL162-1s at 100cm

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

0 50 100 150

Con

trast

Time (s)

C -DL162-5s at 50cm

C -DL162-5s at 100cm

Quantitative IRT experimental laboratory program

167

(d)

Figure 4.50 Defect DL162: (a) location of DL162, (b) thermal signals, (c) contrast at 5 s, (d) contrast at 1 s

The maximum signals of the artificial delamination defects in Specimens 6, 7 and 13 are

shown Table 4.7. By studying the two delamination areas of Specimen 6, it can be noted

how the size of the delamination area can influence the surface temperature distribution,

when the larger DL061 defect area records higher signals than the DL062 delamination

for all lamp distances and pulse intervals. The average improvement for the detected

ΔTmax of DL061 and DL062 was between 222%, and 207 % for intervals from 1 s to 5

s.

Delaminations in bi-directional CFRP fabrics were investigated with defects DL072 and

DL132. Specimen 7’s defect DL072 thermal results are shown in Table 4.7. The data

show a higher thermal maximum signal than the delamination underlying a uni-

directional fabric in Specimen 16, possibly due to the increase in the delamination

thickness of DL072. The delamination in Specimen 13 shows very similar values of

ΔTmax to Specimen 7. The only small alteration of the values between these specimens’

defects was due to the fabric design, as DL132 is between two TYFO BCC (± 45o)

sheets, while DL072 is between uni-directional CF140 and bi-directional CFRP fabric

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

0 50 100 150

Con

trast

Time (s)

C -DL162-1s at 50cm

C -DL162-1s at 100cm

Chapter Four

168

layers. However, this difference between the values of DL132 and DL072 was expected

to be the opposite, with DL072 being expected to have the high pattern of ΔTmax. This

small increase in DL132 thermal signals might be related to different parameters

including the rough surface preparation of Specimen 13, which created a pointy

concrete surface that contacted the CFRP with less epoxy and helped heat to transfer

faster to the substrate structure.

Table 4.7 Summary of maximum thermal signals for delamination defects

Defect ID

ΔTmax (oC)

at 50 cm 70 cm 100

cm

120

cm

DL061

1 s 7 6.6 2.6 1.8

3 s 13 9.2 4.9 3.3

5 s 15.7 11.4 6.5 4.5

DL062

1 s 6.1 4.3 1 0.5

3 s 11.7 5.5 1.6 1

5 s 14 6.9 2.4 1.6

DL072

1 s 7.1 3.5 1.3 0.9

3 s 13.8 7.1 3.6 2.5

5 s 18.3 9.6 5.3 3.5

DL132

1 s 8.4 3.6 1.6 0.8

3 s 14.7 7.7 3.5 3.2

5 s 22.8 11.7 5.3 4

4.5.2.3 Far distance IR detection

Tests were conducted at distances to explore the opportunity of carrying out these IR

tests from far distances. The same active IR tests were applied to Specimen 1 at

different pulse intervals. The IR camera was mounted at 5 m and 10 m from the

specimen while the heating lamp was positioned at 70 cm. According to the IR camera

features, the view of field can detect an area of 6 mm2 from 10 metres, as shown in

Quantitative IRT experimental laboratory program

169

Figure 4.1b. For that reason, the maximum distance at which the IR camera can detect

the defect and read size correctly is 10 m.

The results reveal that even though that the distance between the specimen surface and

the IR camera was increased up to 10 m, the location, shape and size of the fabricated

defects under the CFRP fabric were still observed and identified with proportional

defects’ sizes. The IRT NDTs thermograms achieved from far distances are shown in

Figure 4.51.

(a) Image captured from 5 m distance

(b) Image captured from 10 m distance

Figure 4.51 Thermal image of Specimen 1

Chapter Four

170

Far distance detection was investigated in Specimen 1 in 6 IRT tests. Both tests were

performed with active PTT. Heat load pulses with intervals of 1 s, 3 s, and 5 s were

applied. Figure 4.52 shows the thermal responses of these six IRT tests. Results of both

camera distance locations follow the same pattern for each pulse interval. All IR images

show encouraging results in terms of accuracy of defect size measurement and detection

with a minimum of 5 oC difference between the defect and its surrounding area at a

minimum pulse interval of 1 s. However, the thermograms captured 10 m from the

object show higher ΔTmax compared to IR images recorded at 5 m. This may due to the

increase of the transmission line between the IR and the investigated surface which

leads to increased errors in the emissions readings.

Figure 4.53 reveals the three thermal responses of defect UB011 captured from 0.7 m, 5

m and 10 m from the specimen’s surface. The 4 oC difference between the readings at

0.7 m was because of a different IR analysis at the pixel level and different camera

angle.

(a) Captured from 5 m distance

0.0

5.0

10.0

15.0

0 10 20 30 40

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

UB011 at 5 sUB011 at 3 sUB011 at 1 s

Quantitative IRT experimental laboratory program

171

(b) Captured from 10 m distance

Figure 4.52 Thermal responses of Defect UB011

Figure 4.53 UB011 signals captured from different distances

Verification of the ability to conduct the IRT NDT from far distances can help in

applying IRT tests in the field. It is obvious that IR detector cannot be located close to

all structures on sites. The distances that allow reliable results in this section are

0.0

5.0

10.0

15.0

0 10 20 30 40

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

UB011 at 5 sUB011 at 3 sUB011 at 1 s

-2.0

2.0

6.0

10.0

14.0

18.0

22.0

0 10 20 30 40

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB011-5 s at 10 mΔT-UB011-5 s at 5 mΔT-UB011-5s at 70 cm

Chapter Four

172

reasonable distances that offer the possibility of testing most structures that needs to be

tested thermographically in the field. However, unwanted emittance which affects

thermograms that captured from far distances may be a problem that will need to be

solved. Usually a filter that attached to the IR cameras can help overcome unwanted

emittance.

The passive approach is most appropriate technique for IRT from far distances in site

conditions. It is recommended to carry out far passive IRT just after the sun-rise or after

the sun-set, when temperature has the maximum chance.

4.5.2.4 Transmission observation IRT

Cold spots can form, as indicated in Figure 2.23 when transmission observation method

is applied in PTT IRT. Concrete specimens are too thick to capture any signals by

means of transmission IRT, and the results of IR tests using this technique show no

thermal responses when applied to selected concrete specimens. For that reason, it is not

feasible to inspect defects inserted in concrete specimens with the transmission

observation method Specimens with steel substrate are more appropriate for the

employment of transmission PTT. Three steel specimens were tested using this

technique to explore PTT with transmission observation technique. However, unbonded

defects with a single sheet of CFRP fabric in Specimen S1 were not identified using this

method. Unbonding defects on the CFRP laminate-steel zone in Specimen S4 were

localized and detected with very small thermal responses. Figure 4.54 illustrates defect

UBS41’s thermal responses. The IR results show that the unbonded area beneath FRP

laminate is noticeable; however, the values of the maximum thermal signal and contrast

are small compared to the signals and contrasts obtained by applying the reflection

observation method. The negative IR values in the figures below reveal the principal

cold spots generated by applying this transmission detection method.

Figure 4.54a presents the thermal signal response with a pulse period of 10 s and the

lamp mounted at 0.7 m from the surface of Specimen S4. The ratio of the pulse interval

to thermal signals is very high when the specimen is observed by the transmission

scheme, being only 4 oC when recorded as ΔTmax with 10 s pulses. The steel specimen

Quantitative IRT experimental laboratory program

173

thickness is 3 mm. For steel sections strengthened with CFRP laminate and more than 3

mm thick more time is required for the injection of the heat pulse. The contrast value is

small, being less than 0.75 at Cmax, as shown in Figure 4.54b. The results show that the

noise level in the transmission observation method is at minimum. The contrast appears

as a smoothed curve in the figure below, even after the pulse of 10 s end, due to the

stability of the temperature distribution in the specimen using this transmission method.

The noise level was slightly high at the beginning of the test when the pulse was

applied.

(a) Thermal signal

(b) Thermal contrast

Figure 4.54 UBS41 transmission observation method thermal responses

-5.0

-4.0

-3.0

-2.0

-1.0

0.0

1.0

0 20 40 60 80 100 120 140

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UBS41-Transmission

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

0 20 40 60 80 100 120 140

Con

trast

Time (s)

C -UBS41-Transmission

Chapter Four

174

4.5.2.5 Summary of Part 2 experimental program

The experiments that conducted in this part involved the study of defect detection using

PTT. Artificial defects of unbonded areas, debonding, and delamination were examined

using PTT using the reflection observation technique. The transmission IR observation

method was also chosen for selected specimens. Thermal responses of defects

underlying single and/or multiple-CFRP fabric and laminate composites were evaluated

at different pulse durations and different lamp distances. The first set of IR experiments

focused on unbonded defects. Unbonded defects covered with different types and layers

CFRP fabric were investigated and the effect of increasing the fabric thickness was

examined. Thermal response curves of unbonding defects under single and double

CFRP laminate were also constructed. The experimental runs also included unbond

flaws under an arrangement of CFRP fabrics and laminates. Finally assessments of

defects inserted in CFRP- concrete and CFRP-steel systems were carried out.

The second experimental set performed emphasised debonding and delamination

detection by using PTT IRT. Irregular artificial debonding defects under different CFRP

fabrics and different substrate structures were evaluated. Three dimensional profiles of

the debond areas were constructed to study the severity of debonding within the flaw.

Delamination between CFRP systems was inspected in fabrics, laminates and

combination of both.

Applying the IRT from far distances was also studied. IR runs were conducted to study

the ability to capture consistent thermograms from different distances and up to 10 m

from the tested objects. Far distance detection reliability was analyzed for unbond

defects.

Finally, IRT NDTs adopting the transmission observation method were applied in this

part of the quantitative experimental program. Steel specimens only were chosen to be

tested using this observation method.

The quantitative experiments reported in this part present several interesting

conclusions, of which the following is a summary:

Quantitative IRT experimental laboratory program

175

For unbond, debond and delamination, the thermal signals decrease with

increasing thickness of CFRP composites.

The noise level in the thermal contrast is higher than the thermal signals. A

smoothing process is required to find the C versus time relationship using a

moving average and polynomial algorithm. The noise level is low until Cmax.

The level of noise then increases gradually towards the end of the test. The noise

level is decreased by increasing the distance between the lamps and the

investigated surface.

Most bond defect thermal signals follow Pattern A when the defect is located

under CFRP fabric. Defects underlying laminates Perform with A or B.

The maximum thermal signal is captured immediately after the excitation source

is turned off and the shutter closed for all defects in the CFRP fabric systems.

Flaws in the laminate-CFRP composite show their ΔTmax not immediately at the

end of the pulse, but after a short time, was due to the different thermal

properties of the CFRP fabric and laminates. The time range of this period was

different from defect to defect, according to the design, the specimen and/or IR

test setting.

The IRT PTT test proves that detection of different bond defects can be

achieved even with pulse intervals of 1 s. However, other fast PTTs with higher

pulse lengths at 3 s and 5 s show higher signals and contrasts in the thermal

analyses.

For unbond defects under different CFRP fabric, the maximum thermal signal

increases lineally with increasing input heat flux.

For different CFRP fabrics the maximum thermal signals decrease with the

increase of the fibre thickness.

To generate well-recognized detection for bond defect the input heat flux is

recommended to be greater than 500 W/m2 and the pulse length more than 1 s.

The maximum thermal signal is proportional to the number of CFRP layers. It

decreases to about half with the increase of CFRP fabric sheets to 2 layers.

Chapter Four

176

The rate of thermal signal fading is greater in defects under a single CFRP layer

than multi-layers and the fading rate for fabrics is higher than for CFRP

laminates.

Bond defect detection does not depend only on the CFRP composite design and

system, but also on the substrate material. For identical pulse lengths, defects

with concrete substrate show greater thermal responses than those with steel.

However, due to extensive heat capture when IR is conducted with more than 5 s

pulse intervals and with very high injected heat waves (when the lamp is close,

up to 0.5 m), defects in steel systems reveal higher signals than in concrete.

The 3-D profile constructed for debonding defects is a very efficient tool to

determine the severity of the unbonding within the debonding zone.

The size of debonding air pockets effect the thermal response.

The maximum thermal signal increase nonlinearly with increasing debonding

region thickness.

By increasing the number of CFRP layers, the contrast of a delamination will

produce unacceptable noise levels and provide irrelevant C values.

The maximum thermal signal increases by increasing the delamination area.

Rough surface specimen preparation alters the IR reading, and may present

irrelevant spots due to spiky point formation in the bonding zone.

The technique shows an excellent ability to detect defects from 10 m accurately.

However, IR thermograms from far distances contain a high level of unwanted

emittance due to the long transmission line between the IR detector and the

object.

In the transmission observation method, specimens need more time to generate

well-identified thermal signals. Cold spots appear with negative signals. The

noise in the thermal contrast appears at the commencement of the test and

decreases towards the end.

4.5.3 Part 3: Defect size measurement

Knowledge of the precise size of unbond, debond areas and delaminations helps the

assessment and evaluation of the integrity of the entire structure that has been retrofitted

with CFRP systems. This assessment and monitoring can lead to reduced stress from

Quantitative IRT experimental laboratory program

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over-loading and keep the structure well beyond the serviceability limit. At the same

time, reading the size of defects accurately can help radically with repair and

maintenance. This section investigates the ability of IRT to determine subsurface defect

sizes with high accuracy. Defects in Specimens 1, 2, 4 - 9, 16, 17, 24, 27, S1, and S3 -

S5 were measured using active PTT IRT. These defects were located under different

CFRP materials. Halogen lamps were used as the excitation system during the tests. The

IR detector was positioned 70 cm from the investigated objects.

The defect size is determined by analysis of the thermal image at pixel level.

Measurement area functions provide excellent defect size measurement, by drawing an

ROI around the defect boundaries and calculating the number of pixels inside the ROI.

The size of a defect can then be calculated by translating the pixels to their

corresponding equivalent size and / or area. Figure 4.55 demonstrates the pixels

calculation analysis for the measurement of defect UB011 in Specimen 1. The lengths

of the lines in this IR image were as follows: Line 1 145 pixels, Line 2 68 pixels, and

Line 3 440 pixels. To find the equivalent length ratio for each pixel, the specimen’s

know distance was used. Line 3 of 440 pixels was equal to 300 mm. Then each pixel in

this thermogram is equal to 1.467 mm. By converting the size of defect UB011 of this

specimen in lines 1 and 2, the calculated defect size is 98.86 × 46.36 mm, representing

with great accuracy the actual size of 100 × 50 mm.

Figure 4.55 Defect sizes measurement in Specimen 1

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178

The defect size and area can also be established and verified using the boundary outline

method. In this method, an area measurement function is used to draw round the

boundaries of the defect. The number of pixels is then calculated and converted to the

corresponding area. The boundary outline method is very useful to calculate defects that

have irregular shapes. Figure 4.56 shows the calculation of the size of defect DB031.

The reference size of the specimen’s 300 mm dimension was taken to determine the

image length/pixel ratio. By converting the 505 pixel length of Line 1, it was found that

each pixel equals 0.59406 mm. That means each 1 pixel square will identify 0.353 mm2.

ROI 2 in Figure 4.56a was set to the debonding defect DB031 via the boundary outline

method. The area of this defect was analyzed at pixel level. The measurement of the

pixel number was 30651 pixels, which is calculated to be 108.17 cm2.

(a) (b)

Figure 4.56 Boundary outline method for defect area measurement- Specimen 3

The defect size measures were exactly the actual size, however, these measurements can

vary for many reasons. The most important factor that affects the defect size

measurement is the selection of the defect boundaries, which depend completely on the

thermographer’s judgment. Figure 4.56b shows the selected boundary in Specimen 3’s

debond defect. As shown in the figure, the decision as to the edge where the analyst can

consider the defect boundary to be located is not an easy task. The other major factor is

the time of the thermogram frame that the analyst selects to calculate the size of the

defect. To have an accurate defect size there is a need to analyse the specific IR image

captured at tmax or immediately after it. Factors include the colour scale of the

Quantitative IRT experimental laboratory program

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thermogram and the angle between the surface and the IR camera view line can also

play a role. To obtain a very accurate defect shape and size using this method of pixel

area calculation, it is recommended to have an IR test design where the IR detector is

perpendicular to the tested surface. In this way, the error of the angle of view will be

eliminated. However, this option was not always available during the entire IR test

programs

The thermograms of Specimens 1 and 2 illustrate that the sizes of the unbonded defects

under a single CF130 and CF140 layer matching exactly the actual embedded defects’

sizes, as shown in Figures 4.54 and 4.58. As shown in the latter figure, it is very clear

that the resin crosses the designed boundaries of unbonded defect UB021. For that

reason, the size of this defect width was measured precisely at the desired position.

Figure 4.57 Measuring defects in Specimen 1 in mm

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50

50

50 100

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Figure 4.58 defect size of UB021 in mm

Opposite fibres setting is usually used when the structure is strengthened with more than

one layer of CFRP composites. This may lead to reduced ability to read accurately the

defects’ sizes due to heat diffusion caused by the fibres’ opposite alignment. However,

the pixels size readings matched the real defect sizes with good accuracy, even when

double sheets of CFRP were used and attached in opposite fabric directions. Figure 4.59

exhibits the dimensions of the UB081 defect that was retrofitted with double CF140

sheet with opposite fibres direction alignments. In this defect size reading, the

boundaries of the defect were not easy to determine clearly, possibly due to the

difference in the CFRP fabric direction of the two layers in this specimen. Furthermore,

the detection of the size measurements of UB071 and DL072 which were constructed

by attaching 0.55 mm CFRP bi-directional fabric to the top of CF140 fabric was very

accurate, as shown in Figure 4.60.

100 70

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Figure 4.59 Specimen 8 defect sizes in mm

Figure 4.60 Specimen 7 defect measurements in mm

Defect size determination in steel specimens was also precise. Nevertheless, selecting

the best IR image needs a punctual frame analysis to decide the frame with maximum

thermal signal and clear surface temperature distribution. Figure 4.61a illustrates the

five defects in steel Specimen S1. The size pixel reading shows the accurate defect size.

However, the angle of the IR with respect to the surface altered the sizes slightly. For

very accurate size reading of defects, thermograms should be captured perpendicularly.

Defect sizes are influenced significantly by the capture time of thermograms. For steel

specimens, the signal fading rate was high compared to concrete, which allowed a short

time for the IR analyst to read the defect size precisely. Figure 4.61b shows an ROI that

was drawn to collect thermal information on defects UBS11 and UBS14 in Specimen

100

180220

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182

S1. Several 3-dimensional profiles of this region of interest were constructed at different

times after the end of the 1 s pulse from 50 cm distance. Both defects read 8 oC thermal

signals immediately after the end of the pulse, as shown in Figure 4.61c, however, the

shapes of the defects were not clear, due to the increase in the defect-free area

neighbouring the defect. After 3.25 s from the pulse end, the signal reduced but the

shape detection increased, as shown in Figure 4.61d. Figure 4.61e shows that when the

ΔT reaches to 4 oC at 4.25 s from pulse end, defect shapes become easier to determine.

After 7 s the signals become around 2 oC, but with clear defect size dimensions for

UBS11 and UBS14.

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(a) Specimen S1 defects (b) ROI of defects UBS11 and UBS14

(c) 3-D profile at t = 0 s after pulse end (d) 3D-profile at t = 3.25 s after pulse end

(e) 3D- profile at t = 4.5 s after pulse end (f) 3-D profile at t = 7 s after pulse end

Figure 4.61 Steel Specimen S1surface temperature profiles at different times

20.0

24.0

28.0

32.0

36.0

40.0

Surface Temperature (oC)

UBS11

UBS14

20.022.024.026.028.030.032.034.036.038.040.0

Surface Temperature (oC)

UBS11

UBS14

20.022.024.026.028.030.032.034.036.038.040.0

Surface Temperature (oC)

UBS11

UBS14

20.021.022.023.024.025.026.027.028.029.030.0

Surface Temperature (oC)

UBS11

UBS14

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184

The measurement of defect and anomaly sizes beneath CFRP laminate is a major

challenge. The 1.4 mm thickness of the CFRP laminate is one of the main reasons why

it is hard to observe these defects. The IRT tests performed on Specimens 5, 9, 16, 17

and S4 prove that the technique is able to measure with high accuracy the different

defects in the CFRP laminate concrete and steel bond zones. Figures 4.62 to 4.65

illustrate these measurements. Defects UB051 and UB052 were calculated with

acceptable accuracy. Figure 4.62 illustrates these two defect sizes and highlights that the

actual defect areas does not match exactly the rectangular areas shown in Figure 3.11-5.

Again, that is due to crossing the epoxy during the application of the CFRP laminate.

Unbonded area UB091 size measurement is shown in Figure 4.63. The size of this

defect was very small and it was located close to the CFRP laminate edge where

excessive epoxy used to attach the laminate can mislead the interpretation of the size

defect reading in the thermogram. However, the reading of the defect dimension was

very accurate.

Figure 4.62 Specimen 5 thermogram measurements in mm

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80

Quantitative IRT experimental laboratory program

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Figure 4.63 Specimen 9 defect size in mm

The artificial defect UB161 was not able to be measured precisely, as shown in Figure

4.64, mainly due to the three layers of the CFRP on top of the defects. The resolution of

the defect boundaries was not as good as the defect size reading under a single CFRP

layer. Defect DL162 in the same specimen was determined with good accuracy

compared to the unbond defect of UB161. This may be attributed to the different

number of layers above each of Specimen 16’s defects.

The defect size under CFRP laminate can be easily misanalysed due to the laminate’s

properties. The size of groove defect GR171 was detected with the wrong

corresponding area. Figure 4.65 shows how the IR image size reading is not identical to

the actual size of the embedded GR171 defect. The groove was guaranteed to be empty

from excessive epoxy. The only interpretation for this wrong size reading at the bottom

of the groove under the CFRP laminate is the groove end in the concrete, which was not

a sharp edge. Figure 4.65c shows the smooth edge at the end of the groove cut in the

concrete surface. This might make the heat transfer faster in this area and lead to the

misreading of the groove size shown in Figure 4.65b.

50

25

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Figure 4.64 Specimen 16 defects measurement

(a) (b)

(c)

Figure 4.65 Groove size detection in GR171: (a) the actual size of the groove under the CFRP laminate, (b) the measured detected defect, (c) groove end details at the concrete

surface

Quantitative IRT experimental laboratory program

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4.5.3.1 Summary of Part 3 experimental program

This part of the quantitative experimental program was designed to answer whether IRT

can determine the precise shape and size of the detected defect. The tests studied

various kinds of artificial implanted defects including unbond, debond, grooves in

concrete surface and delamination. After full IR analysis several conclusions were

reached as follows:

The thermographer’s judgment in the selection of defect boundaries can play a

major role in the defect’s calculated area and shape.

The accurate area and shape of the defect depend considerably on the IR image

capture time, i.e. how many seconds after the end of the pulse the IR image was

captured.

Having the IR detector positioned at a perpendicular angle with respect to the

investigated surface is preferable to help to calculate the size and shape of the

nominated defect very accurately. However, border dimensions of defects can

still be read precisely by means of the proportional method when a perpendicular

IR imager position cannot be achieved.

Defects with ΔTmax values less than 2 oC do not generate well-defined

boundaries. Shape and size cannot be determined accurately in this case.

Increasing the number of the CFRP layers over the defect reduces the ability to

calculate the defect area accurately.

Setting the multi-CFRP fabrics in different fibre directions reduces the ability to

calculate the defect area.

The defect size calculation in CFRP-steel system needs higher IR frame rate

analysis due to the high speed of heat wave fading in steel substrate.

Defect shape and size under laminate CFRP system are harder to calculate than

under the fabric systems.

The technique shows that defect sizes of unbond under multi-CFRP fabric layers

cannot be measured precisely.

The exact size of the groove in the concrete-CFRP laminate bond surface is

undetermined.

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4.5.4 Part 4: Excitation system design

The main aim of this experimental program was to investigate the efficiency of using

different excitation systems. Heating tungsten halogen lamps in spot and flood modes

were compared. In addition, an air blower excitation system was investigated. Different

kinds of implanted artificial defects were subjected to these excitation schemes and

observed thermographically using quantitative IR testing. The experimental program in

this part was conducted through 44 IR tests for lamps with different heating shape

functions. The second heating scheme was achieved by applying a total of 39 PTT IRT

runs using an air blower excitation system.

4.5.4.1 Lamps heating modes

The heating tungsten halogen light lamps used in the design as an excitation source to

generate heat waves in the active thermography had maximum capacity of 2000 watts

with varibeam capability. The light beam can vary from spot to flood mode. The spot

mode was utilized for most of the IR tests to generate the surface detection shown in

Figure 2.22c with high thermal responses. However, studies were performed using both

spot and flood modes in this part of the quantitative active thermography program.

As shown in Figure 4.66, the injected heat waves struck the surface with non-

homogenous behaviour. The heat wave was designed to hit the centre of the specimen,

and for that reason the UB051 and UB052 artificial defects in the centre of that

specimen have higher thermal signals compared to the off-centre defects GR053 and

GR054. Moreover, within the same UB051 defect, the area close to the centre of the

specimen (the epicentre of the heat wave) has a higher temperature than the unbonded

areas far from this point, as shown in Figure 4.66c.

Quantitative IRT experimental laboratory program

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(a) (b)

(c)

Figure 4.66 Thermograms of Specimen 5 (a) before the test, (b) during the heat pulse, and (c) 1s after the heat pulse

The spot mode highlights the maximum response causing it to generate a larger heat

wave within the defect zone, while the flood lighting mode helps the thermographer to

draw the boundaries of the defect clearly. Figure 4.67 illustrates the two types of heating

light modes generated by means of tungsten halogen lamps on Specimen 24. As shown

in Figure 4.67a, the maximum temperature was recorded in the centre of the specimen

surface where the heat wave was designed to strike. This was an advantage for

enhancing the detectability of the unbonding defect. At the same time, it could mislead

the thermographer’s analysis, especially during the location of the ROIs. Choosing a

large ROI with the ability to record the maximum temperature during the IR sequence

run can cause misinterpretation of the location of a defect, particularly with the presence

of small hot spots unrelated to the subsurface defects. However, this challenge

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190

commonly faces the thermographer. For that reason, special care needs to be taken in

the selection and design of the ROI in IR analysis. One of the methods adopted in this

research to overcome this problem was to select a small rectangular ROI in the

investigated unbonded area and to record the average temperature within this small

ROI. The locations of these ROIs were usually selected to be not within the area in the

centre of the specimen where the heat wave can register a very high temperature.

However, this was not always possible, especially when the artificial defect was inserted

in the middle of the specimen.

Heat waves applied in flood distribution documented the defect boundaries clearly. No

obvious nonrelated hot spots misled the detection of the unbonding fault. However, the

thermal signals captured in this mode were much lower than in the spot mode. The flood

distribution of the light beam works perfectly if the investigated area is large, but

examining large areas needs more uniform heat waves.

(a) (b)

Figure 4.67 Specimen 24 after 1 s of pulse (a) using the spot light mode, (b) using the flood light mode

For the unbond defect in Specimen 2 the differences in thermal responses between the

two excitation light modes are marked, as shown in Figure 4.68. The flood mode

maximum signals reduce by 40% over the spot phase at different pulse lengths, mainly

due to the difference in heat intensities and heat distribution of each light mode. The tmax

of both modes for the same pulse duration was the same as shown in Figure 4.68.

Quantitative IRT experimental laboratory program

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Moreover, the fading time for both mode signals where the signals record around zero

values was very similar.

Figure 4.68 Thermal responses of UB021 in spot- and flood-lighting modes

In the debonding area the difference between these two light-distribution modes

increases. Figures 4.69a and 4.69b reveal the homogeneity of the temperature surface

distribution of defect DB031. As shown, the spot mode concentrates all heat in the

middle of the specimen, while the flood mode distributes the heat uniformly over the

entire surface. The detection for DB031 in Figure 4.69a was easier to determine the

boundaries of the debonding zone than boundary of the same defect that shown in

Figure 4.69b. To find the edges of the defect precisely by means of flood-distributed

heat wave, it is necessary to apply the wave for a medium to long duration.

-2.0

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Ther

mal

sig

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T (o C

)

Time (s)

ΔT-UB021-5s at 50cm-spot modeΔT-UB021-5s at 50cm-flood modeΔT-UB021-1s at 50cm-spot modeΔT-UB021-1s at 50cm-flood mode

Chapter Four

192

(a) (b)

Figure 4.69 Specimen 3 during pulse time (a) using the spot-light mode, (b) using the flood-light mode

The difference in the thermal signals recorded for Specimen 3 is shown in Figure 4.70a.

From this figure it can be seen that both light modes have the same thermal signal

pattern (Type A). However, there was a great difference in the detectability. The

enhancement of the maximum signals was more than 160% for different setting of the

IR configuration at 1 s and 5 s from 50 cm. The thermal contrast difference again was

smaller than the differences in the thermal signals. In debonding detection it takes more

time to create higher recognition. Figures 4.70b and 4.70c show the smoothed contrast

behaviour in debonding defect DB031 in spot and flood modes at 1 s and 5 s pulse

durations. The improvement in the detectability of the maximum contrast was 50% by

using the spot mode introduced at 1 s and 5 s durations.

Quantitative IRT experimental laboratory program

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(a)

(b)

0

5

10

15

20

25

30

0 50 100 150

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

DB031-1s-50cm-Spot mode

DB031-1s-50cm-Flood mode

DB031-5s-50cm-Spot mode

DB031-5s-50cm-Flood mode

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9

14

19

24

0 50 100 150

Con

trast

Time (s)

C-DB031-5s-50cm-spot modeC-DB031-5s-50cm-flood modePoly. (C-DB031-5s-50cm-spot mode)Poly. (C-DB031-5s-50cm-flood mode)

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194

(c)

Figure 4.70 Thermal results of DB031 with different light modes (a) thermal signals, (b) contrast at 5 s, (c) contrast at 1 s

In summary, flood mode can achieve a more homogenous and uniformly-distributed

heat wave over the investigated surface; however, the identification of the defects is not

easy with this mode for medium and small defects, especially with its modest heat

intensity values compared to the spot mode. The flood mode is recommended when

large area is under evaluation, or as a first IR test in advance of a second detailed test to

nominate the area that needs more investigation with spot mode injection excitation.

4.5.4.2 Air blower excitation system

A 2000 watt hot air blower was employed to generate a linear air beam applied to the

investigated area within the specimens’ surfaces. The intensity of the air beam was

different from test to test because it is dependent on different parameters including the

distance from the surface, the angle with the surface, and the room temperature.

However, room temperature was controlled at 20 oC for most of the laboratory tests.

The other parameters were designed to be fixed but they were very hard to control.

Figure 4.71 illustrates the thermal responses for defect UB011 using the air excitation

system. The maximum signal obtained by this system was significantly lower than the

lamp excitation system. However, the signal value can still lead to the recognition of the

-1

4

9

14

19

24

0 50 100 150

Con

trast

Time (s)

C-DB031-1s-50cm-spot modeC-DB031-1s-50cm-flood modePoly. (C-DB031-1s-50cm-spot mode)Poly. (C-DB031-1s-50cm-flood mode)

Quantitative IRT experimental laboratory program

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defect. The temperature reached just above 2 oC when the system introduced air for 10

s, as shown in Figure 4.71a. The difference between lamps and air excitation systems

was broad. For example, for the same 70 cm distance of excitation source from the

surface, the maximum signal traced when using the lamp for only 1 s was 5.7 oC (see

Figure 4.18), more than double the signal collected after using the air blower for 10 s.

The test of the air blower on Specimen 1 experienced some reflection error at the

surface during the IR experimental run. The reflection altered the thermal signal with

0.4 oC by about 10 s half a minute after the start of the test. The error area with the

signal curve is highlighted with a yellow rectangle in Figure 4.71a. The computed

thermal contrast date for this defect with air excitation has some noise that makes the

categorization of the contract behaviour very difficult, as shown in Figure 4.71b. The

characterized maximum thermal contrast was around 2.5. It is certain that the error

noticed in the thermal signal affected the computing of the contrast. Moreover, the IRT

tests of Specimen 1 highlight the high probability of introducing different kinds of

errors in the IR results.

(a)

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sig

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)

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ΔT-UB011-10s at 70cm

Reflection error

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196

(b)

Figure 4.71 UB011 thermal response by using air blower excitation system for 10 s (a) thermal signal, (b) thermal contrast

The detection ability for debonding defects was similar to that of unbonded defects.

Tests on Specimen 3 using air excitation show that the maximum thermal signal and

contrast was modest but comprehensible and contained a high level of noise. Figure

4.72a provides the IR image of defect DB031 collected by applying an air blower to

Specimen 3’s surface. The data presented in Figures 4.72b and 4.72c confirm the

limited detectability of debonding defects by this excitation technique compared to the

lamp heating technique. From Figures 4.41a and 4.72b, the maximum thermal signals

captured for DB031 with 5 s pulse with lamps were 10 times greater than those recorded

by applying the air beam for 20 s.

Exposure to air for 5 s and 10 s produced small thermal responses in terms of signals or

contrast. Signals with less than 10 s of air blowing show responses below 1 oC, as

shown in Figure 4.72b. The 1 oC value reflects an undesirable limit for identifying the

defect or the anomaly clearly in a composite non-homogenous structure like the

concrete-CFRP system. The IR readings of these surfaces contain some marginal

differences in the surface temperature that are not related to any defect or abnormality.

-0.50

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1.50

2.50

3.50

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5.50

6.50

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0 20 40 60

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Time (s)

C -UB011-Air Blower at 70cm

Quantitative IRT experimental laboratory program

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(a)

(b)

-0.5

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0 20 40 60

Ther

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sig

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T (o C

)

Time (s)

ΔT-DB031-5 s at 70cmΔT-DB031-10 s at 70cmΔT-DB031-20 s at 70cm

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198

(c)

Figure 4.72 Specimen 3 with air excitation (a) IR image, (b) thermal signal, (c) thermal

contrast

Using the air blower system with 20 s exposure to generate a heat wave in the

unbonding defect underlying the CFRP laminate, the IR technique was unable to detect

a legible thermal signal. The thermal signal computed from that test was very low at less

than 1.3 oC. Figure 4.73a shows the thermal signal for a Specimen 5 unbonded defect

with 20 s excitation. The figure clearly shows the non-homogenous ΔT pattern. The

thermal contrast shown in Figure 4.73b has a high noise level, especially after the end of

the pulse. Values of Cmax and its corresponding tmax are very hard to determine from the

figure, possibly due to the air effect on the background temperature in the thermograms.

The lamp and air excitation systems show very different thermal responses in CFRP

laminate composites. The ratio of the maximum signal that achieved by introduce a hot

air beam to 5 s lamp pulse was 1:6 and 1:3 when the pulse length was 1 s. The clear

difference in detectability makes the lamps more appropriate than the air blower in

CFRP laminate applications.

The low values of the thermal responses acquired by applying air blowers in the CFRP

laminate system are related to the thermal properties of the laminate that needs a high

-1.00

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Con

trast

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C -DB031-5 s at 70cmC -DB031-10 s at 70cmC -DB031-20 s at 70cm

Quantitative IRT experimental laboratory program

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intensity heat source to generate internal heat waves sufficient to be recognized using

the IRT system. The air blower system used in this part of the study was found to be

inadequate to provide enough heating with homogenous distribution to generate easily

recognizable thermal responses defect in laminate system subsurface defects.

(a) Thermal signal

(b) Thermal contrast

Figure 4.73 Thermal results of UB052 using air excitation of 20 s

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sig

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ΔT-UB052-20 s at 70cm

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0 20 40 60

Con

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Time (s)

C -UB052-20 s at 70cm

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Increase the number of layers in the CFRP fabric systems decreases the thermal

responses significantly. Figure 4.74 illustrates the thermal response of UB081 after it

was subjected to air blowing for 20 s. The signal shown in Figure 4.74a considers small

to distinguish the defect properly. Detection of a defect through two layers of CF140

fabric by means of an air blower is not practical with the limited capacity of the air

blower and the temperature of the hot air. Detection could be enhanced if an air blower

of more than 2000 W was used during the IRT test or the temperature of the input air

was higher and better controlled. However, increasing the amount and capacity of the

air may affect the accuracy of the IR image. An air blower with the ability to produce a

controlled temperature air beam is recommended to produce hot spots with higher

thermal responses with the same input volume of air.

The contrast in the multi-CFRP fabric sheets revealed irrelevant values and behaviour,

as illustrated in Figure 4.74b. This may be attributed mainly to two reasons: (i) by

increasing the number of CFRP layers, the thermal contrast in the thermograms contains

more noise and misleads the C values; (ii) the air blowing process influences the

temperature at the surface. From all data collected in the air blowing excitation

program, it was found that the thermal contrast showed in general non-relevant

behaviour and it did not follow a specific pattern. Most of the maximum thermal

contrast values were not able to be calculated.

Quantitative IRT experimental laboratory program

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(a) Thermal signal for 20 s exposure time

(b) Thermal contrast for 20 s exposure time

Figure 4.74 Specimen 8 thermal responses via air blower excitation system

The final experiments were conducted on steel specimens 1 and 2. The unbonded area

inserted in the steel CFRP bond zone shows smaller ΔT compared to the same area in

the concrete system. Figure 4.75a demonstrates the thermal signals for UB011 and

UBS11. Both defects show comparable signal behaviour. The difference in the detection

-0.5

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sig

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)

Time (s)

ΔT-UB081-20 s at 70cm

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values of ΔTmax was small at 0.7 oC. Both defects recorded similar timing for the

maximum signal at tmax to those observed exactly at the end of the excitation pulse. By

comparing Figures 4.38 and 4.75a, it can be seen that defects in CFRP concrete and

steel systems follow the same behaviours following lamp and air excitation. Both follow

Pattern A. However, the signals of the subsurface defect achieved with air excitation in

both systems with concrete and steel substrates are much smaller than the signals

acquired with lamp heating systems. As illustrated in Figure 4.75a, the ΔTmax of both

steel and concrete produced from applying a 2000 W hot air blower for 10 s is

approximately equal to the corresponding values shown in Figure 4.38b from applying

lamp pulses for 1 s from 1 m. Again, the air blower excitation system shows modest

capabilities for clear detection compared to the halogen lamp excitation system.

Debonding in steel and concrete CFRP composites is exhibited in Figure 4.75b. The

difference in the maximum thermal signals recorded from defects DB031 and DBS21 is

smaller than 0.3 oC. Figure 4.47 and 4.75b compare Specimens 3 and S2 debonding

with the two different heating systems. When comparing the signals from the air and

heating lamp systems, it can be seen that signals in both systems follow the same

pattern. However, the debonded area in CFRP-steel zone provided a higher ΔTmax than

the same area in the concrete system.

The signals captured in both unbonding and debonding areas were very low. IRT testing

of structures expected to have either unbonded or debonded areas is recommended to be

conducted with an air blower that has the capability to provide a controlled air

temperature. However, the air beam must be designed to generate sufficient heat

without disturbing the thermograms by increasing the amount of the air applied.

Quantitative IRT experimental laboratory program

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(a) Thermal signals of defects UB011 and UBS11

(b) Thermal contrasts of defects DB031 and DBS21

Figure 4.75 Thermal responses in concrete and steel- CFRP systems

By comparing the IR data collected from heating lamp and air blower excitation

systems, it can be noted that by using the heating air blower the detectability of unbond,

debonding and delamination defects is greatly reduced. Using the hot air system, it was

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noticed that due to the air’s high speed the IR images experienced a large amount of

noise. It is true that the speed of the air did not exceed 50 kph (the maximum limit for

conducting an IR test (ASTM D 4788 1997)), but the noise level was noticeably high.

The probability of reflection error was also increased by using the hand air blower.

4.5.4.3 Summary of Part 4 experimental program

The fourth stage of the experimental quantitative study focused on defect detectability

using different designs and modes of excitation systems. The study used halogen lamps

and air blower systems. Unbond, debond, delamination and grooves were investigated

in CFRP laminates and fabric attached externally to both concrete and steel substrates.

IR analyses were performed on the data collected from about 80 IR tests of both

excitation systems.

A number of conclusions can be drawn, based on the results of IR analysis:

Spot heating mode provides higher signals for defects located under the centre of

the injected heat wave, which makes the thermal signals of defects located far

from the centre not comparable.

Due to the intense heating wave that can be generated, the spot mode is

recommended when the study of defects within the bond zone is required.

Non-related hot spots in the thermograms decrease significantly when flood-

light mode is used.

Thermal signals are clearer when spot heating is used than flood mode for all the

different defects studied.

Flood mode is not recommended for defect with small area, as clear detection

may be not achieved with the low heat intensity applied in this mode.

Capture time of the maximum thermal signals is not affected by mode heating

change.

Differences between spot and flood modes in debonds are higher than in

unbonded areas.

Excitation with air supply systems produces very small signals and high noise

levels in the thermal contrasts for different types of defects.

Quantitative IRT experimental laboratory program

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The air excitation system is highly likely to produce errors in the recording of

thermograms. This may be caused by the air blower system or the reflection on

the CFRP surface from the hand movement.

The accuracy of thermal signals when hot air beams are applied with pulse

lengths less than 20 s is not acceptable.

In general, the maximum contrast from the air heating system cannot be

determined from the analysis of the IR images.

Thermal signals of defect underlying multi-CFRP layers are irrelevant when

using an air blower as excitation source.

In spite of the small thermal signals collected using the air excitation system, the

signals follow the same behaviour as signals from the lamp system in both

concrete and steel and for unbonding and debonding defects.

Air blower devices with the ability to provide high temperature air at acceptable

pumping speed may be more useful to produce higher thermal responses.

4.5.5 Part 5: Infra-red errors and noise

IRT has many convenient features that make it applicable in many fields and in superior

to other nondestructive tests in many fields. However, similarly to other NDT methods,

it is common for the captured thermograms to contain errors. This part of the

quantitative program studied the confidence level of the acquired thermograms.

4.5.5.1 Errors in IRT

The errors that contribute seriously to IR misreading can be classified into three main

groups: transmission path errors which involve absorption, scattering, size of object

effects and vignetting; errors that can occur during signal processing and finally,

process of characterization that involves surface emissivity and reflections. Emissivity

has already been identified for specimen testing as shown in Part 1 of this quantitative

program.

While the radiation is passing the medium between the IR detector and the target

surface, transmission path errors can occur. IR transmitted energy that crosses the air

medium may be subject to absorption or scattering at various levels which leads to

errors in the IR reading. The severity of these errors is dependent on the gases in the

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medium. Air transparency is not absolute, part of the IR radiation will be absorbed

during its crossing in the air. Water vapour (H2O), carbon dioxide (CO2) and ozone (O3)

are the gases that cause most absorption in air. However, IR transmittance is heavily

dependent on the IR radiation wavelength, reading distance, and meteorological

conditions. Each IR detector has specific band infra-red wavelengths with which it can

work with. The efficient IR spectrum range that has the minimum effect of the

atmosphere and gases is positioned in the window of LWIR between 8 to 13 µm. To

minimize the transmission path errors in the IR result both of the IR detectors’ radiation

wavelength used in this study were located in this LWIR band.

In addition, a clear and clean test environment was ensured to minimize the effect of

suspended solid particles in the medium like dust and smoke. All laboratory tests were

conducted in controlled humidity, and ventilation was maintained during the tests. The

IR sight-line was always clear of any object that might cause a vignetting effect and

reduce the amount of radiation received.

Some errors in thermal signal processing were noticed which had very minor effects.

Some points produced irrelevant temperatures during the capture of several

thermograms, mainly due to the IR decoder reset time during testing, when the decoder

reset the temperature mapping every time the detector functioned. However, these errors

appear could be detected easily and their effect eliminated.

Reflection is the most frequent error that influences temperature accuracy in the thermal

image data. To minimize this kind of error it is essential to recognize and avoid

undesired background atmosphere reflections on the investigated surface from all

external sources. It is true that background reflections are normally due to external

objects being warmer than the investigated specimen, but error reflection from colder

sources should also be taken into consideration. However, if the investigated

specimen’s surface is heated well above the external objects, background radiation from

external sources will be hardly noticeable in the thermal images. The elimination of

these background reflections depends on their nature. Point source reflection, for

example, can be solved by relocating the IR detector until its best position is identified

Quantitative IRT experimental laboratory program

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where no error is noticed. It strongly recommended to block the line of sight between

any unwanted emittance source and the tested surface. Due to the IR detector’s limited

capabilities in distinguishing these background radiations that reflect on the specimen’s

surface, shielding the detector from these external radiation sources is a solution to

minimize undesired reflection. A special design was adopted during the performance of

all IR tests. To prevent all unwanted radiation from objects in the laboratory that could

affect the thermograms, a dark curtain was used to cover the entire test equipment, as

shown in Figure 4.76a. Moreover, a rigid steel frame was built with sliding shutters

coated with matt black paint, to simulate black body emissivity and reduce the reflected

radiation of the steel.

In spite of all these actions to reduce the reflection from outside objects, the

thermograms were still able to receive reflections from open windows that allowed heat

to come through or from the thermographer’s body if he moved during the test. Figure

4.76b shows reflection on the CFRP fabric coming from the open window. This is an

indication that reflection error needs to be minimized from all directions including the

test’s camera line. The thermographer needs to trial IRT in advance of the main test to

set the position of the IR detector to have the minimum reflection on the investigated

surface. This can be achieved when IR testing on site is supported by with the ability to

analyses the captured thermogram sequences instantaneously.

Chapter Four

208

(a) View of the covered site location

(b) Reflection on the CFRP fabric surface

Figure 4.76 Views of the covered site location

The dark curtain helped to prevent all the unwanted radiation from laboratory

background objects. It was found that the excitation lamps also emitted undesirable

radiation after it being turned off. For that reason, a special IR test rig was built to

reduce errors from the turned off excitation sources. A 1.8 m × 3 m steel rigid frame

was constructed with two sliding shutters to reduce the emission from the turned off

lamp. The sliding shutters were designed to prevent the unwanted emitted radiation after

the end of the thermal injection. Styrofoam insulation material was used to make the

sliding shutter body. Figures 4.5 and 4.6 illustrate the schematic of the constructed

frame. To evaluate IR error from the excitation system after it was turned off, one

sliding shutter was moved and the window between the heat source and the specimen

closed to stop the specimen’s surface from receiving any extra radiation from the

Quantitative IRT experimental laboratory program

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turned-off lamps. Figure 4.77 illustrates the thermograms for the IRT site when it was

not covered with the curtain and when the lamp was turned off. As shown in the figure,

even with turned off lamps, there is still radiation being emitted from the excitation

lamp and many objects in the laboratory. This lamp’s emittance caused an error in the

surface temperature recorded on Specimen 1 in Figure 4.77. To study the effect of this

unwanted emittance from the turned-off excitation lamps, many IR tests were carried

out to compare the IR readings when the shutter was closed and when it was open. Tests

were performed on different specimens to cover different defect types. Two pulse

lengths at 1 s and 5 s were chosen for CFRP applications with closed and opened

shutter. The lamp was positioned at 0.5 m.

Figure 4.77 Thermogram of the uncovered site with no shutter in use

A comparison of thermal signals recorded with closed and opened shutter revealed that

unwanted radiations were emitted from the excitation lamp after it was turned off.

Figure 4.78 illustrates the difference in UB021 signals when shielding was used. As

expected, the difference in temperature starts to appear after the thermal signal peak.

From the results in Figure 4.78 it can be seen that the pulse length influences the

amount of error coming from the lamp. For short pulses of 1 s, the IR reading had an

error of 0.6 oC in the thermogram sequence recorded when no shutter was used. For 5 s

pulse duration the surface was heated well with more than 20 oC increase, which means

Chapter Four

210

it decreases the effect of unwanted lamp emittance. However, it is still an error of 0.6 oC

as shown in Figure 4.78b. This could be due to different reasons, including the location

of the defect with respect to the centre of the heating wave and the design of the defect

itself in term of the CFRP thickness and type over the defect. UB021 was designed with

a single CF140 layer. The small thickness of the CFRP composite above this artificial

defect makes the influence of the turned-off lamp error greater than for a defect

underlying a thick laminate CFRP system. As can be seen from Figures 4.78, 4.79a and

4.79b, the unbonded area beneath laminate (defect UB051) is less shaped by not using

the shutter than the defect in the concrete-CFRP fabric bonding zone. Laminate defect

UB051 showed 0.3 oC and 0.1 oC temperature differences when pulses were applied

with 1 s and 5 s respectively. However, these differences were not constant and altered

towards the end of the IR test. Errors of defects under double CFRP laminates show

similar ranges with corresponding thermal signals patterns.

(a) Pulse length of 1 s

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Quantitative IRT experimental laboratory program

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(b) Pulse length of 5 s

Figure 4.78 Thermal signals of defect UB021

(a) UB051 at 1 s pulse length

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(b) UB051 at 5 s pulse length

(c) UB052 at 1 s pulse length

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ΔT-UB051-5s at 50cm-shutter closed

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ΔT-UB052-1s at 50cm-shutter closed

Quantitative IRT experimental laboratory program

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(d) UB052 at 5 s pulse length

Figure 4.79 Error in thermal signals of Specimen 5 defects

A comparison of Figures 4.78 and 4.80 shows that unwanted radiation from turned-off

excitation lamps cause almost the same amount of error in thermograms as debonded

and unbonded areas. Defect DB031 was covered with the same CFRP fabric as defect

UB021, however, for the same pulse duration, the error in the debonding flaw was

around 0.65 oC. The errors were taken as an average, due to the high alteration rate in

the temperatures.

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ΔT-UB052-5s at 50cm-shutter opened

ΔT-UB052-5s at 50cm-shutter closed

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Figure 4.80 Specimen 3 defect signals

Defects in steel-CFRP specimens showed similar behaviour to concrete-CFRP defects

but with smaller error. However, the recognized temperature error when pulses were

applied at 1 s was negligible, mainly due to the thermal properties of steel, which allow

the heat wave to fade rapidly. The 5 s heat pulse injections again showed small errors in

both unbonded and debonded areas, as shown in Figure 4.81 for defects UBS32 and

DBS31. However, the debond defect in this steel specimen shows the maximum error at

10 s from the starting time of the pulse injection, then the error rate reduce to almost

zero toward the end. This may be attributed to the air pocket in this defect that can

change the surface temperature with different rates.

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Quantitative IRT experimental laboratory program

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(a) UBS32 at 5 s pulse length

(b) DBS31 at 5 s pulse length

Figure 4.81 Specimen S3 defect signals

The error in the thermal signal of a laminate CFRP-steel system defect is shown in

Figure 4.82. The errors are again small and are at their maximum after the pulse peak

point. Errors in this system have slightly higher values than the concrete system,

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ΔT-DBS31-5s at 50cm-shutter closed

Chapter Four

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possibly due to the thermal properties of the steel substrate. The figure shows a similar

alteration rate in the two thermal signals.

Figure 4.82 DBS31 errors in signal of 5 s pulse length

In summary, the results presented in this part show the need to cut off the radiation from

turned-off excitation systems by using a shutter. Moreover, the results highlight the

need to eliminate unwanted radiation from objects surrounding the surface of interest.

4.5.5.2 Noise in the IRT

Noise in thermograms can be evaluated by constructing noise population histogram,

which are usually calculated to predict the probability density function. This histogram

usually follows normal distribution, which is often assumed in noise distribution

processes in IRT analysis. However, there is still a chance of non-normal noise

occurring.

To identify the noise content in IR images, it is necessary to analyze two images at pixel

level. If the two thermal images show the same scene under the same condition, noise

will appear as the differences between the two images. The subtraction process was

followed during the IR analysis of several specimens to study the noise level of their

thermograms. To fulfill the constant scene conditions, thermogram frames were

recorded before the heating application. Figure 4.83 displays Specimen 5 noise analysis

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sig

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Quantitative IRT experimental laboratory program

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and evaluation. As mentioned, two frames at different times were captured in a static

scene before the IR testing of this specimen. Frame number two was recorded 2 s after

frame 1. Figures 4.83a and 4.83b show these thermograms. Figure 4.83c shows the

subtraction thermogram produced by subtracting frame 2 from frame 1 IR images.

Figure 4.83d illustrates the histogram of the noise evaluation after the subtraction of the

two thermal images captured of Specimen 5 in the static scene. From the results of the

histogram shown in Figure 4.83d it can be seen the bell shape has normal distribution

which means that random noise content is slight.

(a) Thermogram frame number 1

(b) Thermogram frame number 8

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218

(c) Subtraction IR image of frame 1 and 8

(d) Histogram of subtraction IR image

Figure 4.83 Noise evaluation of Specimen 5

Noise cannot be controlled in terms of the scene field and the gases and wind can

change the temperature on the investigated surface or increase the noise and error in the

thermograms. However, filters can be attached externally to the IR camera lens to

minimize such effects. Filter technology is developing swiftly in terms of capabilities

and prices.

Apart from the external filters, different built-in software filters can be used to reduce

noise effects or to enhance the detection of the defect boundaries and/or area. The IR

software Image Processor ProII that was used with a Thermo Tracer TH9260 IR imager

has the most common filters utilized in image processing, includes Gaussian,

neighbourhood averaging, focus, Laplacian and Prewitt filters. However, software like

Quantitative IRT experimental laboratory program

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MATLAB has more sophisticated facilities and greater capabilities. Figure 4.84 shows

examples of filters employed with IR images and 3-dimensional profiles of defect

UB081. It was found that the most efficient filters that can reduce the sharp noise within

the construction of the 3-D profiling are Gaussian 5×5, and neighbourhood averaging

5×5. It was noticed that sharp points were eliminated with these two filters in the

thermograms. However, the thermal signal of this defect did not show significant

change when these two filters were applied, mainly because of the size of ROI that was

designed to measure the IR data from the thermograms and the method of recording the

temperature within the ROI area of that defect. Different filters can be applied to

increase some feature of the data. However, using different filters to enhance the quality

of images during thermogram processing was not one of the aims of this study.

(a) Normal image (b) Averaging 5× 5 filter 5 times

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220

(c) Gaussian 5× 5 filter 5 times (d) Laplacian 3× 3 filter

(e) Prewitt (horizontal) filter (f) Focus (+) filter

Figure 4.84 Specimen 26 IR images and 3D profile processing with different filters

Quantitative IRT experimental laboratory program

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4.5.6 Part 6: IR detection of the presence of water

The ability of the IRT testing to detect moisture at debond areas was investigated in this

part of the research. During the quantitative thermography tests, several defects were

filled with water to investigate water detectability using this technique. Only concrete

specimens were investigated with this defect.

The water was inserted using a 60 ml syringe into the defect area. The temperature of

the injected water was the same as that of the surrounding environment before

conducting the thermography test for most tests. Active PTT tests were applied

following the injection of the water. PTT was adopted when the temperature of the

injected water was the same as the investigated object in a static scene.

Grooves in Specimen 4 were filled with water to investigate the detection of water

under CFRP fabric using IRT. During the IR test, one groove was filled with water and

the other remained without water. The thermal result shows that the water in the groove

can be detected, but not easily as shown in Figure 4.85. The water acts as a good

medium to transfer and alter the heat wave so that the detection will be low. For that

reason, it was found that to provide a good detection of water it is necessary to supply a

high pulse for a long time. This intensive heat will increase temperature of the entire

investigated surface by several degrees and in this case the defect saturated with water

will appear as a cold spot. Generating the 3-dimensional profiles in this investigation

aids detection markedly. Figure 4.85b exhibits the cold spot clearly in defect GR042.

Nevertheless, Figure 4.85 illustrates some imperfection on the surface during the

making of this specimen when excessive epoxy bled on the surface and caused the

irrelevant hotspot shown on the surface.

Chapter Four

222

(a) IR image of groove filled with water

(b) Three-dimensions profile

Figure 4.85 Water investigation in Specimen 4

The debonding defect in Specimen 3 was filled at the water with same temperature as

the specimen and left for half an hour to ensure that the water and the specimen reached

the same temperature. Pulses with 5 s lengths were then applied on the entire surface.

Figure 4.86 illustrates the signals of DB031 when it was filled with water and when it

Quantitative IRT experimental laboratory program

223

was empty. Water will change the debond detection from a hot spot to appear as a cold

spot in the thermograms. It can be seen from the results in the figure that the presence of

water reduces the signal greatly, as for the same pulse length and lamp distance the

maximum signal dropped to slightly more than one fifth. However, the debond area

with water still has enough temperature signals to detect the presence of water within

the defect area.

Figure 4.86 DB031 signal with water presence

According to the requirement of the ASTM standard D4788, surfaces to be investigated

with IRT should be dried for at least 24 hours before the test (ASTM D 4788 1997).

This condition was hard to apply when water was inserted into the CFRP fabric system,

mainly because of the fabric weave design that allowed water to escape to the surface

during the injection. Figure 4.87 demonstrates water escaping from DB031 which led to

the cancellation the IR test. IRT testing was postponed 1 day in all cases of water

escaping.

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Chapter Four

224

Figure 4.87 Water escaping from the defect

Due to the physical properties of CFRP laminate, water escape from defects underlying

a CFRP laminate did not happen frequently. Figure 4.88 shows the water injection

process in the IRT images of Specimen 17 groove defect GR171 captured 30 minutes

before conducting active 5 s PTT testing. As it was hard to provide an air pocket under

the laminate, the groove was prepared in the concrete surface and it was open to the air

from one side to facilitate the insertion of water inside the groove. The temperature of

the injected water in this defect was around 20 oC, the same as that of the surrounding

environment before conducting the thermography test. However, the water was left for

about 30 minutes inside the groove before performing the IR test to harmonize the

temperatures.

Defects underlying the CFRP laminate show different detection spots. The Specimen 17

defect showed a hot spot when the water was in the defect area, due to the open defect

area and the difference in the laminate thermal properties that allowed the CFRP

composite to keep the heat for longer before it transfered it to the underlying material.

The thermal records of defect GR171 are shown in Figure 4.89. The results of this

defect show that the IRT can detect the presence of water at the defect. However, the

comparison of thermal signals or contrast values of the same defect with and without

water show that the presence of water greatly reduces the thermal response. In addition,

when the water filled this groove the signal followed a sharper pattern with respect to

Quantitative IRT experimental laboratory program

225

time after the end of the pulse interval. The pulse duration of this IR test shown in

Figure 4.89 was 5 s. As can be noticed from the figure, the signal of the defect with air

recorded 2.4 oC after 30 s from the test start. However, when it was filled with water for

the same capture time it was just 1.2 oC. The contrast also shows the same diversity of

values for the case with the defect containing water, shown in Figure 4.89b. Both ΔTmax

and Cmax when water is present within the defect area are relatively detectable with

reasonable values; however, the detection time after reaching these maximum values

may be very short when the signals fade swiftly. In spite of the low values of the

thermal responses to water presence in defects beneath laminate systems, the

homogenous temperature distribution in the neighbouring defect-free area will enhance

detection in the IR image and profile. Figure 4.90 shows the IR image and 3-D profile

of GR171 when it was filled with water. From the temperature scale it can be noticed

that the ΔT of that defect is about 2 oC, but due to the laminate’s homogenous

distribution on the defect-free area surrounding the defect, the defect is detected clearly.

Chapter Four

226

(a) Water filling the groove (b) Quarter of groove filled

(c) Filled with 60%

Figure 4.88 Water injection process of GR171 before the pulse injection

Quantitative IRT experimental laboratory program

227

(a) Thermal signals

(b) Contrast

Figure 4.89 Specimen 17 IR results

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GR171

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Chapter Four

228

(a) IR image

(b) 3D profile

Figure 4.90 Defect GR171 thermal result

4.5.6.1 Summary of Part 5

In summary, the quantitative thermography tests conducted show that the technique is

able to detect water presence. Similar to bond defects, the signals of pockets filled with

water beneath CFRP fabric were higher than the same defect underlying laminate

composites. Water in the fabric system produces cold spots in the thermogram. A

thermal signal shows a significant reduction when water is present in the defect area.

Applying intensive pulses to raise the tested surface temperature well above its static

scene temperature is recommended to detect areas with water presence.

Thermal responses in laminate CFRP-concrete systems show hot spots with very small

values. Defect signals fade more rapidly in the presence of water in the defect area,

Quantitative IRT experimental laboratory program

229

which makes the detection of defects that have water more challenging task for the

thermographer. Generating a 3-D profile of the captured thermogram greatly aids the

visualization of water-filled defects.

4.5.7 Part 7: Long-Pulsed IRT and Lockin thermography approaches

4.5.7.1 Long-Pulsed heating scheme

Reports of experiments on long pulse IRT tests are provided in this part. In general, the

results of applying 10 s and 20 s pulses to unbond and debond defect show an

improvement in general detectability.

Figure 4.91 compares the signals recorded in UB011 when the lamp was placed at 0.5 m

for different pulse lengths. Specimen 1 defect number UB011 showed more than a 3 oC

increase in the maximum thermal signal when 10 s time length pulse was applied

compared to 5 s. From the figure, it can be seen that not only the maximum ΔT is

enhanced but the signal fading rate also improves. Imposing the pulse for 5 s will faded

after 14.5 s from the end of the pulse, while this fading time increased to 20 s when the

pulse length extended to be 10 s. This fading rate increase gives the theromgrapher

more time to analyze the captured IR frames after the end of the pulse. However, the

increase in pulse duration is limited by the Tg temperature of the epoxy, where the

temperature of the surface should not exceed the epoxy glass transition limit

temperature. In concrete specimens the maximum pulse length time that was applied

was 10 s. It was found from the results that applying pulses from 50 cm for slightly

more than 10 s raises the CFRP fabric surface temperature to more than the 60 oC limit.

This limit is the recommended Tg (CEB-FIP Bulletin 14 2001) that should not be

exceeded according to the epoxy manufacturer’s specifications. From the result of

Specimen 1 that was strengthened with CF130 fabric, it was found that the enhancement

in the detectability was 13% when the pulse interval time was doubled from 5 s to 10 s.

This enrichment in the signal was good but not advisable due to the high surface

temperature, especially when the pulse of 5 s provides a very good signal with more

than 22 oC.

Chapter Four

230

Figure 4.91 UB011 thermal signals

Different CFRP types were investigated using the long PTT heating method. Figure

4.92 compares the thermal signals of unbonded defects in Specimen 6 at 5 s and 10 s

pulses. These tests were conducted with the lamp positioned at 70 cm to reduce the risk

of the surface temperature reaching the limit. The signals detected when pulses were

applied for 10 s increased by 13% compared with 5 s intervals. The IR results of defects

UB011 and UB063 indicate that by applying a 10 s long pulse heating, the detection

improvements in defect covered with CF130 and CF140 are the same. For defects under

double CFRP fabric layers, the use of long PTT showed interesting results. The thermal

signal in UB064 experienced a substantial increase of more than 50% compared to 5 s

pulses. This is significant, particularly given the small scale of the signal detection for

this defect type.

-2

2

6

10

14

18

22

26

0 10 20 30 40 50 60

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB011-1s at 50 cm

ΔT-UB011-3s at 50 cm

ΔT-UB011-5s at 50 cm

ΔT-UB011-10s at 50 cm

Quantitative IRT experimental laboratory program

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Figure 4.92 Defects UB063 and UB064 thermal signals at 5 s and 10 s

The study of defects in the concrete-CFRP laminate bond zone showed similar signal

observations to concrete-CFRP fabric defects. However, the growth in the maximum

value of the thermal signal was smaller compared to the increase in the fabric CFRP

system. The signal presented in Figure 4.93 reveals around 6% rise to ΔTmax of defect

UB051 when long PTT was applied from 70 cm. The pulses of 10 s show similar

behaviour to the 5 s pulses length. In contrast, the maximum thermal signal values of 5 s

and 10 s levelled off for defect UB052 under two layers of CFRP laminates. However,

after reaching the peak of the thermal signal, defection under multiple laminates showed

slight enhancement with 0.5 oC difference in ΔT, as illustrated in Figure 4.93.

Long PTT in laminate CFRP concrete shows a good improvement in the thermal signals

detected for both defects under single- and multi-laminate layers. The results show that

long PTT, even with more than 10 s pulse lengths, can be recommended when concrete-

multi CFRP laminate is under IRT investigation. This heating approach can improve the

thermal response of any expected defect under laminates, especially if the laminate’s

surface temperature increase does not exceed the limit. However, if a combination of

laminate and CFRP fabric is used, the fabric’s surface temperature can be critical with

more than 10 s heating.

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Ther

mal

sig

nal

ΔT

(oC

)

Time (s)

ΔT-UB063-5s at 70cm

ΔT-UB064-5s at 70cm

ΔT-UB063-10s at 70cm

ΔT-UB064-10s at 70cm

Chapter Four

232

Figure 4.93 Defects UB051 and UB052 thermal signals at 5 s and 10 s

Applying long pulse heating to debonding defects displays a large increase in the

thermal response collected. Conducting the pulse for 10 s 50 cm from the lamp cause an

unacceptable increase in the CFRP fabric surface. For that reason, the test was

performed from 70 cm. Results shown in Figure 4.94 shown the difference between

signals when applied for 5 s and 10 s. Specimen 3's debond flaw signals collected from

10 s pulses show an increase of 50 % more than the 5 s pulse. This increase is not

desirable due to the high increase in the surface temperature.

0.0

1.0

2.0

3.0

4.0

5.0

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7.0

8.0

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Ther

mal

sig

nal Δ

T (o C

)

Time (s)

ΔT-UB051-10s at 70cmΔT-UB052-10s at 70cmΔT-UB051-5s at 70cmΔT-UB052-5s at 70cm

Quantitative IRT experimental laboratory program

233

Figure 4.94 Defect DB031 thermal signals at 5 s and 10 s

Steel specimens were tested with long PTT heating in two 10 s and 20 s pulse designs.

Figure 4.95 compares the thermal signals versus time for different pulse lengths for

defect UBS11. The results indicate there is a great advantage in using longer pulse

intervals. Pulse heating in steel-CFRP fabric for 20 s shows that the system reaches a

steady-state, defined as when the maximum thermal signal reaches a specific value,

even by increasing the injected pulse heat duration to infinity. The maximum signals at

pulse lengths of 10 s and 20 s show the same values. It was not clear from the collected

data at what point the system reached steady-state condition. However, it was between 5

s and 10 s pulse durations.

0

5

10

15

20

25

0 50 100

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

DB031-5s-70cm

DB031-10s-70cm

Chapter Four

234

Figure 4.95 Defect UBS11 thermal signals at 5 s and 10 s

4.5.7.2 Lockin thermography approach

The general principle of lockin IRT is to investigate and indicate the depth of the defect

from the surface (deeper defects will be detectable by low frequency while high

frequency pulses will help to detect defects closer to the surface). However, the bond

defect is usually located at the bonding surface between the CFRP and the substrate

structure and the depth of this surface can be calculated when the thickness of the CFRP

and epoxy layers is known. Multi-layer CFRP composites can have different locations

of defect. All tested specimens had a known defect depth, and for that reason the testing

of this heating scheme was not intended to determine defect depth. Different

researchers have highlighted this issue in different material. A detailed study of defect

depths in concrete-CFRP systems using LTT is presented by Brown (2005).

The LTT tests concentrated on studying the detection abilities and signal trends using

this excitation method for unbonding and debonding defects in both concrete and steel-

CFRP fabric.

Two frequencies were investigated using the lockin thermography technique. Sinusoidal

waves mentioned in Section 4.3.5.2 were applied to the specimens in this heating

-1.0

4.0

9.0

14.0

19.0

24.0

0 10 20 30 40

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

UBS11-5s at 70cm

UBS11-10s at 70cm

UBS11-20s at 70cm

Quantitative IRT experimental laboratory program

235

scheme. Specimens 1, 2, 3, S1, S2 and S3 were observed in the LTT. A summary of the

LTT frequencies, pulse lengths and IR images collected are presented in Table 4.8. Both

frequencies used in the LTT were generally low. For each tested specimen there was a

cooling time varying from 5 to 10 minutes between the LTT test runs.

Table 4.8 LTT frequencies applied

Frequency (Hz) Pulse duration (s) Number of analyzed thermograms per pulse

0.05 20 80

0.25 40 160

Comparisons of thermal signals collected by applying sinusoidal waves for 20 s and 40

s to the Specimen 1 defect are shown in Figure 4.96. The lockin technique shows high

detectability. The results the thermal maximum thermal signal increases with each

following cycle, and the amount of that increase is around 2oC in both trends of the

frequencies used, basically as a result of accumulating the heat on the defect area after

each cycle. For 20 s pulse duration cycles the temperature captured on the defect area

was 4 oC greater than the defect-free area at the end of the first cycle, as shown in

Figure 4.96a. This trapped heat in the unbonding defect was owing to insufficient

cooling time, which allows the surface to cool down and thus the ΔT value to reach

minimum value. In Figure 4.96b as a result of increasing the pulse time, the value of the

thermal signal at the end of the first cycle is just 2 oC, half of its corresponding signal at

0.05 Hz.

By decreasing the frequency from 0.05 Hz to 0.025 Hz, the maximum thermal signal

values of the same defect depth were increased by 40% and 25% for the first and second

cycle respectively. This indicates that, by lowering the frequency rate, detectability will

increase for a specific defect at a specific depth, which confirms the guideline of using a

low frequency to detect a deeper defect.

Unbonding defects with steel substrate show very similar thermal signal trends. Figure

4.97 reveals the ΔT values as a function of time. These signals were calculated from the

IR images captured during the two frequencies LTT. The increase in the maximum

Chapter Four

236

signals over the cycle was negligible and both signal cycle peaks show almost the same

value. That is different from the results of UB011 due to the different materials in the

substrate. Steel has thermal properties that help the heat to transfer faster than concrete.

For that reason the trapped heat was less than 2 oC after the cycle when 0.05 Hz

sinusoidal wave applied, as revealed in Figure 4.97a. Similar to the concrete unbond

defect, UBS11 shows less trapped heat after the end of the cycle when the frequency

increased. Moreover, an increase in detectability was still observed when the applied

sinusoidal wave frequency rate was reduced.

(a) Frequency of 0.05 Hz (b) Frequency of 0.025 Hz

Figure 4.96 Specimen 1 thermal signals by applying LTT

(a) Frequency of 0.05 Hz (b) Frequency of 0.025 Hz

Figure 4.97 Defect UBS11 thermal signals by applying LTT

-2.0

0.0

2.0

4.0

6.0

8.0

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Ther

mal

sig

nal Δ

T (o C

)

Time (s)

UB011-0.05Hz

-2.0

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Ther

mal

sig

nal Δ

T (o C

)

Time (s)

UB011-0.025Hz

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

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9.0

10.0

0 10 20 30 40

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

UBS11-0.05Hz

0

2

4

6

8

10

12

0 20 40 60 80

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

UBS11-0.025Hz

Quantitative IRT experimental laboratory program

237

Debonding defects show different thermal signal patterns compared to unbond areas.

The debonding defect fabricated in Specimen 3 shows a very high detectability value as

shown in Figure 4.98. The air pocket in debonding defect DB031 helped to generate the

high signals when the LTT sinusoidal waves were applied. The signals do not

experience a serious drop after reaching the peak, possibly because of the air between

the CFRP and the concrete which will not allow the heat to transfer swiftly. Figures

4.98a and 4.98b show that, by reducing the frequency by half, the debonded defect

thermal signals in Specimen 3 increased dramatically by more than 60 % and 101% for

the 1st and 2nd cycles respectively. Defects of debond type in steel specimens show a

parallel trend to debonding areas in concrete specimens. Figure 4.99 illustrates the

thermal data of DBS21. The increase in the signals with respect to frequencies and

cycles is almost the same. However, the debonding defect in steel registers lower

thermal signals at the end of cycle one compared to the concrete DB031 defect. The

debonding areas in both concrete and steel specimens tested with 0.025 Hz LTT waves

experienced large rise in the surface temperature, which reached 55 oC in the 2nd cycle

of that test. This could raise the temperature to an unacceptable level at which where the

epoxy under the CFRP fabric may be affected.

(a) Frequency of 0.05 Hz (b) Frequency of 0.025 Hz

Figure 4.98 Defect DB031 thermal signals by applying LTT

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

0 10 20 30 40

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

DB031-0.05Hz

0.0

5.0

10.0

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25.0

30.0

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40.0

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Ther

mal

sig

nal Δ

T (o C

)

Time (s)

DB031-0.025Hz

Chapter Four

238

(a) Frequency of 0.05 Hz (b) Frequency of 0.025 Hz

Figure 4.99 Specimen S2 debonding defect thermal signals by applying LTT

4.5.7.3 Summary and findings

From the comparison of heating schemes, the results show that for concrete

strengthened with CFRP composites, long PTT enhances the detection of defects

generally. The improvement in the thermal signal reading and the analysis of defects in

the concrete-laminate bond surface is appropriate in terms of the total temperature on

the surface. This detection enhancement suggests that long PTT should be utilized in

IRT assessment of concrete structures strengthened with CFRP laminate. Artificial bond

defects in CFRP fabric-concrete composites show high increases in the thermal signals

captured when long PTT is adopted. However, this increase raises the surface

temperature to more than the epoxy glass transition limit. The increase in pulse duration

was found to be more efficient and to assist in the detection process when the long

pulses are applied from far distances. An excitation system tested at 0.5 m showed a

high increase in ΔTmax values for both unbond and debond defects covered with a single

CFRP fabric. This increase in the signals is inappropriate because of the unacceptable

rise in the investigated surface’s temperature. For artificial bond defects in the concrete-

multi CFRP fabric layers, the PTT with long pulses enhances detectability substantially

with an adequate increase in the surface temperature which does not reached Tg limit of

the epoxy.

0.0

5.0

10.0

15.0

20.0

0 10 20 30 40

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

DBS21-0.05Hz

0

5

10

15

20

25

30

35

40

0 20 40 60 80

Ther

mal

sig

nal Δ

T (o C

)

Time (s)

DBS21-0.025Hz

Quantitative IRT experimental laboratory program

239

One of the main advantages of using the long pulse duration heating scheme is that the

increase in the thermal signal of the defect means that the size and shape can be

established easily. The higher signals lead to better defect size and shape determination.

Using the lockin thermography technique, the results show that the ΔTmax in concrete

unbonding defects is raised by increasing the sinusoidal wave cycles. Steel unbond

defects show no evidence of this rise in the thermal signal peak points. In general, at the

end of the cycles the value of signals does not normalize and level off totally. This ΔT

value is decreased by reducing the frequency rate and it is higher in concrete than steel

substrate. Low frequency provides better detection for defect at the same depth.

Debonding defects in both concrete and CFRP fabric systems show very high signals

with the LTT heating scheme. However, is not recommended to apply LTT for

debonding surface defects with air pockets due to the high rise in the surface

temperature over the defect area.

4.5.8 Part 8: Detection of cracks

The final investigation in the quantitative experimental program was to detect cracks in

the concrete surface beneath CFRP applications. Deep spalling was also under

examined in several specimens. Active PTT was used in this study. Figure 4.100 shows

the schematic of the IRT set-up applied to the specimens. The crack defect area in the

concrete surface will appear with different temperatures relative to the defect-free areas

at the surface in the thermal image. However, due to the small sizes of the cracks,

detection was expected to be difficult.

Chapter Four

240

Figure 4.100 Schematic of IRT for crack detection

Cracks of three types were manufactured in concrete specimen surfaces using three

methods: wide straight grooves, fine curved grooves and loading cracks. Wide straight

grooves 3.6 mm wide and 13.2 mm deep were designed in Specimens 10 and 15 to

investigate the ability of IRT to detect cracks under thick multi-CFRP fabrics and

laminates. Figure 4.101a shows Specimen 10's artificial grooves constructed to study

the identification of wide cracks through multi-CF 130 fabric sheets. Fine curved

grooves were produced during the construction of the concrete specimen. During the

making of the concrete specimens, fine plastic sheets were inserted in the mould with

controlled thickness and depth. After the initial concrete setting, the plastic sheets were

removed carefully to prevent any changes in the artificial crack widths. However, all

crack sizes were checked before the application of CFRP. Loading cracks were

generated in specimens 11, 12, and 14 by three points loading. Loading cracks were

closer to the crack sizes that can occur in real life situations. Figure 4.101b reveals

CR141 and CR142 loading cracks generated in Specimen 14 before attaching the CFRP

sheet.

Quantitative IRT experimental laboratory program

241

(a) Specimen 10

(b) Specimen 14 before CF130 fabric application

Figure 4.101 Artificial crack generation

Two lines were chosen as ROI to reveal the thermal results of IR analysis of Specimen

10's artificial cracks. Figure 4.102a shows the location of these ROIs. They were chosen

to be away from the specimen’s centre to avoid the irrelevant increase in the

temperature within the ROI line profile caused by the pulse hitting the centre of the

specimen. CR101 and CR102 were covered with a single sheet of CF130 fabric, while

double CF130 sheets were attached to cracks CR103 and CR104. The cracks under a

single fabric sheet were very detectable from 50 cm and 70 cm and for all pulse

durations, as shown in Figures 4.102b to 4.102g. As expected, by increasing the

distance and reducing the pulse duration, crack detection was weakened. IR analysis of

Chapter Four

242

pulses applied from 1 m and 1.2 m are present in Appendix B. Figures 4.102b and

4.102e highlight the extent to which surface temperature can be affected by changing

the lamp position by 20 cm. The temperature detected on cracks dropped more than 10 oC when the lamp location moved from 50 cm to 70 cm. The lamp distance or the input

heat flux were expected to be more crucial parameters when using IRT to investigate

finer cracks. For 5 s pulse intervals, theCR102 crack shows a slightly higher

temperature compared to CR101. It is true that both cracks have exactly the same

dimensions and their width is identical, but CR102 was designed to be 20 mm closer to

the centre of the specimen where the pulse heat was planned to strike, as shown in

Figure 3.11-10. That made the received heat at CR102 greater than at CR101 and

caused the difference in surface temperature shown in Figure 4.102b. For pulses with 3

s and 1 s periods the effect of non-identical alignment for these two cracks was

negligible. This provides an interesting guideline for thermographers, they cannot

compare two defect areas (even if both have the same dimensions) unless many

conditions apply including the location of the target of the pulse wave.

(a) ROIs in IR image

CR101 CR102

CR103 CR104

Quantitative IRT experimental laboratory program

243

(b) At 5 s from 50cm (c) At 3 s from 50cm

(d) At 1 s from 50cm (e) At 5 s from 70cm

(f) At 3 s from 70cm (g) At 1 s from 70cm

Figure 4.102 Cracks CR101 and CR102 profile trends

Cracks CR103 and CR104 were covered with two CF130 fabric layers. Pulses with 5 s

and 3 s from 50 cm and 70 cm were able to generate identifiable temperatures

differences on these cracks, as demonstrated in Figure 4.103. However, these

temperature differences were small and faded faster compared to CR101 and CR102.

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

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50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

Chapter Four

244

IRT analysis of pulses from 1 m and 1.2 m are present in Appendix B. Thermal signals

were not reliable for pulses from 1 m and 1.2 m distances.

(a) At 5 s from 50cm (b) At 3 s from 50cm

(c) At 1 s from 50cm (d) At 5 s from 70cm

(e) At 3 s from 70cm (f) At 1 s from 70cm

Figure 4.103 Cracks CR103 and CR104 profile trends

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels 0

510

1520

25

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

05

1015

2025

20.0

30.0

40.0

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1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

05

1015

2025

20.0

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50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

Quantitative IRT experimental laboratory program

245

Cracks under CFRP laminates, even wide cracks of 3.6 mm, were unable to provide

acceptable thermal signals. Figure 4.104a reveals the thermal signals of artificial cracks

CR153 and CR155 under laminate composite in Specimen 15. The results of this figure

illustrate that the maximum crack thermal signal that can be detected in CR153 is about

1.8 oC for the FRP combination of CF140 and laminate when the lamp is mounted at 0.5

m. CR155 IRT with 5 s pulse and from 50 cm provides a maximum thermal signal just

above 2 oC. Both of these values are considered too small to recognize defects. From the

results, it can be concluded that fine cracks under laminate CFRP are hard to detect.

Due to the good length of cracks in general, the thermographer can sometimes evaluate

potential cracks visually from IR images even with small thermal signals. For example,

CR155 can be seen in the thermogram in Figure 4.104b. However, this identification is

dependent on the colour temperature scale used in the IRT analysis.

(a) Thermal signals

0.0

0.5

1.0

1.5

2.0

2.5

0 10 20 30 40 50 60

Ther

mal

Sig

nal Δ

T (o C

)

Time (s)

CR153 at 5s from 50 cm

CR155 at 5s from 50 cm

Chapter Four

246

(b) Thermal image

Figure 4.104 Cracks in Specimen 15

The IR results of Specimen 25 reveal a number of imperfections in the bonding that can

be read from the temperature distribution on the surface of interest. The irregularity of

the hotspot areas in the thermogram shown in Figure 4.105, may be due to the rough

surface preparation and imperfections in the CFRP installation. Detection was unrelated

to crack location and size. The results of Specimen 25 do not show the real values of

thermal signals. The rough surface preparation of the concrete before the application of

CFRP sheet can cause many small point hotspots in the thermograms and lead to

misinterpretation of the defect's location and size.

Figure 4.105 Specimen 25 IR image

CR155

CR153

Quantitative IRT experimental laboratory program

247

Figure 4.106 shows the surface temperature 3-D profile of the ROI line designed to

investigate cracks in Specimen 12. The ROI in the specimen thermograms is shown in

Figure 4.106a. The measured width of the loading CR121 crack was 0.4 mm in its

narrowest part; however, it did not have the same width over the entire length of the

crack. The IR image in this figure shows that the crack size was wider than 0.4 in the

middle of the specimen, although the ROI was chosen to be in an area were the crack

has the minimum width of 0.4 mm. Figures 4.106b to 4.106g demonstrate the ROI

temperature profile for different pulse length durations and from different lamp

locations. From the IR results in Figure 4.106b to 4.106d, the differences between

detected temperatures over ROI1 for pulses of 5 s , 3 s, and 1 s lengths and from half a

metre distance can be seen. From this lamp distance pulses of 3 s and more can provide

good detectability of this size crack for about 5 s after the end of the pulse. Pulses of 1 s

show poor capability to identify the CR121 defect.

The good detectability when applying the 5 s pulse from 50 cm is reduced when the

lamp is positioned further away. The difference in temperature of CR121 and the

surrounding defect- free area reduces considerably by more than 10 oC when the lamp

location is shifted from 50 cm to 70 cm. This shows that the recognition of fine cracks is

very much dependent on the pulse amount and duration. Pulses with 3 s and less could

not reveal the crack clearly when the lamps were mounted more than 50 cm away,

while pulses of 5 s can cause recognizable differences in over crack temperatures from

1.2 m. The signal is extended differently for each different pulse length. In general,

longer pulse length generates a longer thermal signal. All pulse ranges create short

detection times in IRT investigation, when none of the pulses and/or lamp distance

designs experience signals readable for more than 10 s, as illustrated in Figure 4.106b to

4.106g. The crack size detected in thermograms was 0.8 mm. However, the thermal

signal responses were extended for no longer than 5 s after the pulse end. The short

period of the signal might force the analyst to minimize the time for frame analysis.

Figure 4.106d shows that even for 1 s pulse duration and 50 cm lamp position, the

technique is able to detect this fine crack, but with a very small thermal signal value.

Pulses from that distance with longer time periods show higher signal values, as shown

in Figures 4.106b and 4.106c. As revealed in Figures 4.106f and 4.106g, for this crack

size 5 s pulses provide inappropriate thermal signals when the lamp is placed further

Chapter Four

248

than 1 m. Pulses of less than 3 s and applied from further than 70 cm show no good

thermal responses for this crack.

(a) Location of ROI 1 in the Specimen 12

(b) At 5 s from 50cm (c) At 3 s from 50cm

(d) At 1 s from 50cm (e) At 5 s from 70cm

CR121

0 5 10 15 20 25

20.0

30.0

40.0

50.0

151

101151

201251

301

351

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR121

0 5 10 15 20 25

20.0

30.0

40.0

50.0

151

101151

201251

301

351

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR121

0 5 10 15 20 25

20.0

30.0

40.0

50.0

151

101151

201251

301

351

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR121

0 5 10 15 20 25

20.0

30.0

40.0

50.0

151

101151

201251

301

351

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR121

Quantitative IRT experimental laboratory program

249

(f) At 5 s from 100cm (g) At 5 s from 120cm

Figure 4.106 ROI thermal data in CR121 crack

Crack CR141 in Specimen 14 shows a similar surface temperature response to CR121,

because the ROI were positioned on crack CR141 where it was 0.8 mm wide, and

CFR121 was generated with the same width size. The comparison of the surface

temperature behaviours of these two cracks, as can be seen from Figures 4.106 and

4.107, in terms of maximum temperature and length of the signal lead to the conclusion

that they also have the same depth besides their identical width. The CR142 crack with

width of 0.4 in this specimen was undetectable in all pulse designs, as shown in Figure

4.107.

(a) At 5 s from 50cm (b) At 5 s from 70cm

0 5 10 15 20 25

20.0

30.0

40.0

50.0

151

101151

201251

301

351

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR121

0 5 10 15 20 25

20.0

30.0

40.0

50.0

151

101151

201251

301

351

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR121

05

1015

2025

20.0

30.0

40.0

50.0

60.0

1

51

101

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR142

CR141

05

1015

2025

20.0

30.0

40.0

1

51

101

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR142CR141

Chapter Four

250

(c) At 5 s from 100cm (d) At 5 s from 120cm

(e) At 3 s from 50cm (f) At 1 s from 50cm

Figure 4.107 ROI thermal data of Specimen 14

Generally the heat wave should be designed to strike perpendicularly the centre of the

surface of interest to provide as homogenous a temperature distribution as possible.

However, different angles of heat waves were tested to study if they can improve crack

detection. The best IR recognition in terms of crack patterns and sizes was when the

heat wave hit the surface of interest off-centre and at a 60o angle to the specimen's

surface. Figure 4.108 shows the schematic of the IRT configuration to enhance crack

identification.

05

1015

2025

20.0

30.0

40.0

1

51

101

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR142CR141

05

1015

2025

20.0

30.0

40.0

1

51

101

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR142CR141

05

1015

2025

20.0

30.0

40.0

50.0

60.0

1

51

101

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR142

CR141

05

1015

2025

20.0

30.0

40.0

50.0

60.0

1

51

101

Time (s)

Surface Temperature (oC)

ROI 1-pixels

CR142

CR141

Quantitative IRT experimental laboratory program

251

Figure 4.108 IRT configuration to improve crack detection

An IRT inspection was conducted of cracked reinforced concrete Specimen 11

strengthened with two strips of single CFRP MBrace CF130. Concrete cracks were

observed in the IR images recorded. The thermogram in Figure 4.109 shows the cracks

in concrete that divided the specimens into three slices with different temperatures. A

hot strip was observed at the middle between the two major cracks in the

CFRP/concrete specimen. This may be related to the crack depth which met the

reinforcement mesh and caused spalling in the concrete middle strip. As shown in

Figure 4.109, if the crack is moderately deep, it may act as an obstacle to the heat flow

reaching the areas far from the external heat source. In Specimen 11 the heating sources

were directed towards the specimen’s surface at an angle of 60 degrees to the horizontal

level at the top and the bottom edge of the specimen. Figure 4.109a shows that the

cracks generated from loading were deep enough to form spalls in the concrete and to

put a stop to the heat transfer in this specimen. The thermogram shows that the middle

slice had a 2.7 oC temperature difference from the neighbouring areas. A 3-D surface

temperature profile was produced to enhance the cracked area in this specimen, as

shown in Figure 4.109b. The spike in the temperature profile at one edge of the

specimen is due to the angled position of the heating source. Spall in concrete was easy

to detect due to the hot spot area formed in the entire concrete segment that fractured

from the concrete surface. The IRT was unable to evaluate the severity of the spall in

general. The middle spall between CR111 and CR112 was fixed within the concrete

specimen. Spalls Specimens 22 and 23 were unidentifiable by IRT techniques. PTT and

long PTT were applied to these specimens to investigate the capability of IRT to locate

Chapter Four

252

spalling in deep concrete. However, none of these techniques was suitable to produce a

recognizable thermal response, possible because concrete's thermal properties can easily

dampen the heat wave.

(a) Thermogram (b) 3D profile

Figure 4.109 Specimen 11 thermal results

Measurement of the cracks was also conducted in this part of study. Major cracks like

CR102 were detected and measured with very high accuracy. However, to measure that

crack it was essential to position the IR detector perpendicular to the investigated

crack's surface, as shown in Figure 4.110a. The line ROI above the crack shows a value

of 3.7 after pixels conversion. The error measurement reading was less than 0.1 mm

which is very good. The crack size in Specimen 12 was too fine to be measured with

this thermogram pixel resolution. Fine cracks of 1 mm and less can show inaccurate size

readings. The crack in Figure 4.110b was 0.8 mm wide; however, the IR image size

reading showed that the crack width was 0.9 mm. This error in measurement may be

due to different reasons, but mainly to the pixel resolution which was not sufficient to

represent this small size. Crack CR111was also too small to be measured accurately.

The cracks in Specimen 11 generated a spall in the concrete. In such cases the crack will

usually be very hard to measure. The location of the crack in this instance is very

detectable, but the measurement of its size is not possible.

Quantitative IRT experimental laboratory program

253

(a) CR102

(b) CR121

(c) CR111

Figure 4.110 Crack measurement from thermograms

4.5.8.1 Summary and findings

The results of an experimental study have been presented in this section to investigate

the ability of IRT NDT to detect and measure cracks between CFRP fabrics and

Chapter Four

254

concrete specimens. PTT was adopted. The experiments show that the technique is

capable of detecting the locations and sizes of major cracks quite adequately, and the

sizes and shapes of cracks up to 0.8 mm can be identified with high accuracy. The

detection and measurement of cracks in the CFRP concrete bond zone are significantly

dependent on the pulse interval and the distance between the external heat source and

the surface of interest.

4.6 Guidelines for quantitative IRT NDT

The data collected from the results are not sufficient for the development of a

mathematical relationship for thermal signal maximum values as a function of pulse

interval, CFRP material type (laminate or fabric, or type of fabric weave), and CFRP

layers for the different defects investigated. However, the data provide information

about the input pulse durations that need to allocated for each defect type and for

different CFRP composites. The following points are guidelines to help thermographers

to perform IRT PTT.

It is essential for theromgraphers to avoid performing IRT NDT in dusty

environments, as the solid particles suspended in the medium have grey body

performance.

Thermographers should mover the IR imager device until they obtain the best IR

view and angle that show the minimum reflection on the investigated surface.

It is recommended to conduct PTT IRT with short pulse lengths (1 s) for general

scanning and once the discontinuity regions are detected, a full PTT IRT with

appropriate pulse intensity and duration is recommended for deep inspection.

The flood mode of heating is recommended when a large area is under

evaluation, or it can be used as a first IR test in advance of a second detailed test

with spot mode to indicate the areas that need more investigation.

The pulse duration length and lamp distance should be designed according to the

type of CFRP application. For example, for single-layer CFRP fabric, even 1 s

can detect unbonding or debonding in the concrete or steel bonding zone. Table

4.9 shows proposed guidelines for minimum pulse durations for each lamp

Quantitative IRT experimental laboratory program

255

distance for all CFRP applications and combinations tested in this quantitative

research.

The experimental results show that the minimum heat flux intensity that should

be provided to generate the minimum thermal signal when the excitation lamp is

located at 1.2 m from the test object is 500 W/m2.

The IR detector should be positioned at a fixed distance during the test. This

distance should be designed with respect to the potential defect size. Small sizes

need closer IR images to determine the actual size of the defect with respect to

the field of view of the IR camera.

Isolating shutters should be used during IR testing to eliminate undesirable

radiation from the excitation source after it is turned off.

The probability of background radiation reflection is increased for low

emissivity materials and if the test surface is not a plane. The thermographer

needs to take these factors into account in field tests.

From the IR results, a 2 oC minimum is a reasonable value for a thermal signal

to detect an anomaly or defect. With this value of the signal, the size and the

shape of the defect can be characterized adequately.

It is recommended to apply pulses with an intensity that ensures a rise in the

investigated surface’s temperature compared to the background to alleviate the

effects of undesired reflection from objects surrounding the IRT test scene.

The results of the IR quantitative tests can help to provide pulses designs for

different substrates and different CFRP composites. The pulse design guidelines,

shown in Table 4.9, are proposed thermal pulse inputs that can be considered

when conducting a quantitative PTT IRT NDT.

To minimize the influences of unwanted emission from surrounding objects, it is

recommended to heat the investigated surface to a temperature 10 oC higher than

the objects in the background.

To provide good detection of water it is necessary to supply a high pulse for a

good length of time. Long PTT is recommended.

The guidelines categorize pulses mainly according to defect type, CFRP system under

test and substrate material. The 4th column in the table represents the excitation lamp’s

distance from the surface investigated. The recommended pulse interval range is

Chapter Four

256

provided in the last column. These proposed pulse duration ranges offer an upper and

lower boundary of pulse duration for each distance of the lamp to detect all bond defects

in the CFRP-structures investigated in this study.

Table 4.9 IR recommended thermal inputs for different CFRP composites

Defect type CFRP system Substrate

material

Lamp distance

(cm)

Recommended

range pulse length

(s)

Unbonding Single fabric CF130 Concrete

50 1 – 3

70 1 – 3

100 1 – 3

120 1 – 3

Unbonding Single fabric CF140 Concrete

50 1 – 3

70 1 – 3

100 1 – 3

120 3 – 5

Unbonding Double fabric CF140 Concrete

50 3 – 5

70 3 – 5

100 3 – 5

120 >5

Unbonding Single laminate Concrete

50 1 – 3

70 3 – 5

100 >5

120 >5

Unbonding Double laminate Concrete

50 3 – 5

70 3 – 5

100 >5

120 >5

Unbonding Single fabric and single

laminate combination Concrete

50 1 – 3

70 3 – 5

100 3 – 5

120 >5

Unbonding Single fabric and double

laminate combination Concrete

50 3 – 5

70 >5

100 >5

120 >5

Quantitative IRT experimental laboratory program

257

Unbonding Single fabric CF130 Steel

50 1 – 3

70 1 – 3

100 1 – 3

120 3 – 5

Unbonding Single laminate Steel

50 3 – 5

70 3 – 5

100 >5

120 >5

Debonding Single fabric CF130 Concrete

50 1 – 3

70 1 – 3

100 3 – 5

120 3 – 5

Debonding Single fabric CF140 Concrete

50 1 – 3

70 1 – 3

100 3 – 5

120 3 – 5

Debonding Single fabric CF130 Steel

50 1 – 3

70 1 – 3

100 3 – 5

120 3 – 5

Debonding Single fabric 45 bi-

directional Concrete

50 1 – 3

70 1 – 3

100 1 – 3

120 3 – 5

Delamination laminate Concrete

50 1 – 3

70 3 – 5

100 >5

120 >5

Delamination Fabric CF140 Concrete

50 1 – 3

70 1 – 3

100 3 – 5

120 >5

Delamination Fabric 45 bi-directional Concrete

50 1 – 3

70 1 – 3

100 3 – 5

120 >5

Chapter Four

258

Night-time is the best time to conduct an IR test in the field, because unwanted

reflection radiation that might come from objects surrounding the investigated surface

will be minimized. However, it is sometimes very difficult to eliminate the radiations

from surrounding objects in the field. In this case, the effect of the surrounding objects

should be taken into consideration during the IR analysis of the recorded images. There

is no signal standard that can be applied, and normally it depends on the object's

temperature and emissivity.

With all the above guidelines there still remain limited specifications and studies for the

applications of IRT in the field conditions, and site conditions play a pivot role in IR

readings. It is obvious that the temperature at the time of IR testing affects the

temperatures of surfaces under test. Cloudy skies, high winds and surface moisture also

affect the radiation recorded by the IR decoder.

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259

5 CHAPTER FIVE: NUMERICAL ANALYSIS

5.1 Introduction

The numerical analysis of IRT NDT for testing concrete specimens strengthened

externally with CFRP fabric and laminates was the second component of the research

program. This chapter presents the outputs of using the finite element method (FEM) as

an analytical tool to simulate, investigate and study different parameters that affect the

thermal detection of different defects. The numerical modeling and parametric studies

were used to predict IR results and evaluate potential IR test procedures. Different

laboratory circumstances and testing scenarios were applied in the FEM analysis.

Numerical analyses were used to study the influence of several different factors. Single

parameter studies were conducted using FEM. Models of bond defects were mimicked

in the simulation FEM analyses for defects covered with single and double CFRP

fabrics. Different parameters, including the thermal properties of different materials,

layer thicknesses and thermal input loads, were investigated.

5.2 FEM studies of bond defects in single CFRP fabric

5.2.1 Modeling

5.2.1.1 Geometry

Extensive parametric studies involving FEM analyses were conducted. The modeling

involved a study of different parameters that affect the detection of bond defect in

concrete-CFRP system. All the analytical simulations presented in this study were

executed using FE software ANSYS 13.

Concrete Specimen 2 with a single CF140 fabric sheet was used. The artificial defect in

this specimen was in the form of an unbonded strip at the middle of the bond zone

between the substrate structure and the CFRP composite 70 mm wide along the

specimen length, as shown in Figure 3.11-2. A full 3-D model was constructed to

simulate this specimen. The concrete dimensions were 300 mm wide, 300 mm length,

Chapter Five

260

and 50 mm depth. The single carbon fibre sheet was CF140 0.25 mm thick. The epoxy

resin layer was MBrace saturant 0.9 mm thick. The thermal properties and materials

densities used in the modeling are shown in Table 5.1. The concrete material properties

assigned to model the FE simulation substrate structure were the same properties used

to construct this specimen in the laboratory. The carbon fabric thermal properties were

as shown in Table 5.1, were estimated from data sheets provide by the CFRP

manufacturer (MBrace). The thermal properties of air were assigned to model the

unbond defect, adopted from the ANSYS materials library. The air void was presented

at the defect location between the concrete and the CFRP fabric.

Table 5.1 Materials properties (MBrace 2011; MBrace 2012)

Properties Concrete

MBrace

saturant

epoxy

resin

CFRP

fabric

CF140

Air

Density (kg/m3) 2400 983 1700 1.2

Specific Heat (J/kg. oC) 800 1700 800 700

Thermal conductivity (W/m. oC) 1.5 0.19 9.38 0.024

5.2.1.2 Meshing

Different methods were used in the FE meshing. Multi-zone mesh was applied to the

contact surfaces of simulated concrete, epoxy and CFRP layers to enhance the heat

transfer between these layers. The mapped-face meshing method was employed for the

external surface of CF140 where the temperature was recorded. This method of meshing

allows the adjustment and control of the type and size of elements. Figure 5.1 shows the

using meshing of Specimen 2 mapped-face meshing.

To provide more information about the heat transfer within the thin layers of CFRP and

epoxy, the sweep meshing method was applied to these layers as shown in Figure 5.2.

The epoxy layer is subdivided into 3 element layers and the CFRP is also subdivided by

the sweep method into 3 elements. The sweep method of meshing improves the

Numerical analysis

261

representation of thin layers. As shown Figure 5.2, the thickness of the CFRP and resin

matrix layers is very small compared to the concrete substrate structure. If a mesh was

generated with the same size for all materials of this model of the same size, then

misreading may be expected and unnecessary time would be consumed to achieve the

runs of the simulation.

To refine the result of the analytical FE runs and to study the effect of the mesh process

on the data, different meshing methods were applied to the specimen surface. Figure

5.3 shows the mapped facing and the refined surface meshing schemes applied to the

CFRP surface of the first parametric study.

Figure 5.1 Mesh of Specimen 2

Figure 5.2 CFRP and epoxy layers mesh details

CFRP fabric layer subdivded into three elements

Epoxy layer subdivded into three elements

Chapter Five

262

(a) Mapped-face meshing (b) Refined surface meshing

Figure 5.3 Faced meshing of Specimen 2

5.2.1.3 Thermal boundary conditions

Experimental laboratory IRT quantitative results showed that the applied heat wave on

the CFRP surface did not reach the other edge of the concrete from the opposite side.

For that reason, thermal waves were assumed to vanish inside the thick concrete layer of

the strengthened specimen during the IRT, and no heat waves crossed to the other side

of the concrete. Thus, adiabatic boundaries were applied during the FE studies for all

surfaces not receiving the pulse heat wave (where ΔT in both x and y directions was

assumed to be zero). Figure 5.4 shows the model and adiabatic boundaries of the

simulated specimen.

(a) Specimen 2 model

Artificial defect- UB021

CFRP-CF140MBrace epoxy

Concrete Specimen 2

300 mm

300 mm

y

x

z

110 70mm

Numerical analysis

263

(b) Adiabatic boundary conditions

Figure 5.4 Model of Specimen 2 simulation

The CFRP surface experienced free cooling after being heated by the inserted heat

wave. A convection cooling method was used to simulate the effect of this free cooling

on the CFRP surface during the IR test. Convection is defined as the heat transfer that

arises between any surface and fluid in contact due to the temperature difference.

Ideally, this process happens naturally and continues until the temperature reaches

equilibrium. The free convection of the air has a heat transfer coefficient varying from 5

W/m2 .oC to 25 W/m2 .oC. However, this factor is related to the surface temperature of

the object that under goes convection cooling. In all parametric studies presented in this

chapter, a cooling function of the convection type was applied to the top CFRP surface

after receiving the heat pulse waves. Air cooling convection factors of (20-25) W/m2

.oC, (20-40) W/m2 oC and 80 W/m2 oC were used for pulses with 1 s, 3 s and 5 s

respectively.

5.2.1.4 Thermal results

Surface temperatures were recorded at different points to cover hot spots in the IR

thermal experimental results. Four coordination systems were assigned to record the

surface temperature of the specimen. Figure 5.5 shows the coordination points of

Specimen 2. Thermal signals were computed from these coordination points by

applying the thermal signal equation shown in Equation 4.1. Thermal signals as a

function of time were constructed for all simulated runs. The time of the maximum

Heat flux (W/m2)

Epoxy (0.9mm)

Concrete (50mm)

Defect

dT/dy = zero

dT/dx = zero

dT/dz = zero

CF140 (0.25mm)

Chapter Five

264

signal (tmax) was recorded to study the change in the capture-time of Δ Tmax .Surface

temperatures (as a function of time) were monitored and recorded on each node over the

entire CFRP surface to highlight any possible hot spot.

Figure 5.5 Coordination points system

Thermal ANSYS 13 runs were conducted for 120 s with step periods of 1 s, and detailed

results were collected from these runs over the 120 s period. Thermal signal-time

relationships were constructed for different thermal loads and pulse durations in the

parametric studies. The thermal loads and pulses periods were varied to FE simulations.

5.2.2 Parametric Study 1: Verification of analytical simulations

The first parametric study was planned to verify the results of the laboratory

experimental program tests and the thermal results collected from the modeling

simulation. Simulations were computed on Specimen 2 3-D modeling. The material

properties for the materials in this simulation were as the same as those shown in Table

5.1. Mapped-face meshing was used in this simulation, and a sweep mesh refiner was

used on both CFRP and bonding layers with 3 subdivision layering. The thermal

boundary conditions were assumed to be adiabatic and cooling convection modeling

was conducted on the CFRP surface elements after the heat injection. However, the free

Numerical analysis

265

air cooling convection coefficient was varied with the different thermal wave intensities

that were applied to the modeled specimen's surface in this simulation trial. Three pulse

durations were introduced in the PTT injected heating, and a uniform heating scheme

was assumed for simplification purposes. Table 5.2 summarizes the thermal input loads

applied in the laboratory IRT tests, which were the same as those used in the

verification simulations. Four points were allocated to record the surface temperature as

a function of time in this simulation. Verifications of the analytical results and the

laboratory results were conducted by compare different parameters of the thermal data

over a range of infra-red thermography tests with different pulse designs. IR

configuration test results with a lamp mounted at 50 cm were used in these

comparisons. From the experimental studies of this specimen it was found that the

excitation system setting at this distance provides the highest recognized thermal signal

and allows enough time to determine precisely the tmax. The thermal response

parameters that were used for verifying the simulations runs were: thermal signal (as a

function of time), maximum signal time (tmax), and surface temperature (as a function of

time). The ambient temperature for all simulation runs in this verification was assumed

to match the ambient of the experimental IRT test at 20 oC.

Table 5.2 Average of input heat flux waves for different pulse lengths in experimental program

Pulse length (s) Input heat flux

(W/m2)

1 977.7

3 922.22

5 1055.56

An analysis setting with 0.1 s as minimum was used to perform this simulation, and a

120 s time frame was adopted in the three analyses. The results show a high level of

agreement between the experimental laboratory results and the corresponding simulated

results, as shown in Table 5.3 and Figure 5.6. FEM simulation runs numbers 1 to 3 were

assigned to verifying and comparing the results of the experimental program. The

maximum thermal signals of Specimen 2 from the experimental laboratory programs are

Chapter Five

266

shown in Table 5.3. The maximum signals and their corresponding time were collected

for three different pulse periods at 1 s, 3 s and 5 s. The heat fluxes that Specimen 2's

surface received during the PTT IRT were documented, as shown in Table 5.2. These

heat waves were applied to the surface of the 3-D model in the simulation runs.

Simulation run number 1 shows that the maximum thermal signal of the 3-D model was

10.566 oC and this value was reached 2.42 s from the start of the run. That signal was

slightly different, being 2.48 % less than the signal obtained from the laboratory

experiment. Differences between the experimented and simulation runs were reduced

with the increase of pulse durations, as shown in Table 5.3. The 3 s and 5 s pulse

intervals exhibit very close read with less than 0.2 oC difference. The time of recording

these maximum signals also decreased with increased pulse intervals. It is important to

note that the cooling coefficients were 25 W/m2. oC for 1 s pulse length and increased to

more than double when 5 s pulse length was applied.

Figure 5.6 compares the thermal signals versus time of experimental and simulation

runs with pulses a 5 s pulse length and 1055 W/m2. It was noticed that, even with the

accepted differences of ΔTmax, the signals experienced dissimilar cooling trends. In

addition, the signal from the IR experiment faded around 20 s from the start of the test,

while the simulated run signal disappeared after double this period. These differences

between the experimental and simulation results could be reduced if higher cooling

convection factor were used, especially since the cooling factor number was increased

by the increase of the surface temperature. However, it is very hard to predict the

precise cooling temperature rate that occurred during the IRT tests. This kind of

difference may also be due to the not very accurate simulation assumption of heating

consistency over the entire surface investigated. However, these differences occur after

the maximum thermal signals have been reached. The verification of ΔTmax and tmax in

experimental and simulation finite element modeling showed high consistency for

different pulse lengths and different heat flux amounts. The simulated thermal signals

versus time of runs 1 to 3 are presented in Figure 5.7.

Numerical analysis

267

Table 5.3 Simulations thermal results

Run

#

Pulse

length

(s)

Input

heat

flux

(W/m2)

Experimental Simulation Change (%)

ΔTmax

(oC)

tmax

(s)

ΔTmax

(oC)

tmax

(s) ΔTmax

1 1 612 10.5 1.5 10.566 2.42 0.63

2 3 922.22 21.1 3.75 21.379 3.9 1.32

3 5 1055.56 28.5 5.75 28.57 5.55 0.25

Figure 5.6 Comparison of experimental and simulated thermal signals at run 3

-5

0

5

10

15

20

25

30

35

0 20 40 60 80 100 120

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

Experimental

Simulated

Chapter Five

268

Figure 5.7 Three pulses durations of runs 1 to 3

In summary, the first parametric study involved the verification of the simulation and

experimental thermal results of an unbond defect under a single CFRP CF140 fabric.

The results of the simulated model were very close to the experimental results for all

pulse duration phases.

5.2.3 Parametric Study 2: Influence of materials thermal properties on

defect detection

Many thermal properties of CFRP products and resin materials are not fully documented

in the manufacturers' data-sheets or reports. Study of the influence of the changes in

these materials’ thermal properties is required to gain a better understanding of the heat

wave movement in these products. The second FE parametric study focused on the

effect of changes in specific heat and conductivity factors on thermal responses. Table

5.1 illustrates the thermal properties of the materials used to construct the simulated

specimen. Parametric Study 2 was subdivided into three parts to address the change for

each of the three materials components of the composite structure. The first group of

runs studied the effect of CFRP thermal properties. The second and third focused on the

-5

0

5

10

15

20

25

30

35

0 20 40 60 80 100 120

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

1 s3 s5 s

Numerical analysis

269

resin and concrete substrate materials. Pulses of 1 s, 3 s and 5 s were used in Parametric

Study 2 with the average heat intensities provided in Table 5.2.

5.2.3.1 Influence of CFRP material thermal properties

CFRP material thermal properties vary widely over the broad range of CFRP products.

These variations are related to several factors including resin matrix type, carbon

volume, and direction of the fibres. Moreover, the fabric weave in the CFRP fabric

influences the thermal response. Due to all these factors that may change the thermal

properties of the CFRP material, it is necessary to study the influence on thermal

detection that can occur using a CFRP application which had different thermal

properties. The simulation studied the effect of changing CFRP heat specifications and

conductivities. The densities and thermal properties of concrete and epoxy are shown in

Table 5.1. The conductivity of CFRP was fixed at 9.38 W/m. oC when the specific heat

was under investigation, and the specific heat was fixed at 800 J/kg.oC when runs were

performed to study the change of the thermal conductivity of the CFRP.

The definition of the specific heat is the energy in J that required to raise the

temperature by 1 oC of a material with a mass of 1 kg. The unit of specific heat is

J/kg.oC or J/kg.K. However, as this project worked with degree Celsius, J/kg.oC unit

was chosen to represent the specific heat. The runs of the heat specification studies are

summarized in Table 5.4. The results show the change of the maximum thermal signal

when the specific heat varies from 700 J/kg.oC to 1200 J/kg.oC. Three pulse durations

were applied: 1 s pulse (runs 4 to 14), 3 s pulse (runs 15 to 25), and 5 s pulses the

remained. Figures 5.8a, 5.8b and 5.8C show the maximum thermal signal as a function

of the specific heat at different pulse durations. The results indicate that the signal

decreased linearly by increasing the specific heat of the CFRP. However, the linear

pattern altered when the specific heat was less than 750 J/kg.oC. The rate of ΔTmax

decrease is changed by increasing the pulse duration. Figures 5.8a, 5.8b and 5.8C

highlight this point. The rates are 0.0107, 0.0209 and 0.0162 for pulses of 1 s, 3 s and 5

s respectively. For 1 s pulse duration, the maximum thermal signal decreases by 33 %

when the specific heat increases to 1200 J/kg.oC.

Chapter Five

270

Figure 5.8d shows the percentage of maximum thermal signal change. The smallest

pulse duration experiences the highest change in the signal value. This confirms that

CFRP material composite with higher specific heat needs a higher heat wave and a

longer pulse to enhance thermal detectability. The time to the maximum thermal signal

is also raised by the increase of the specific heat value. Figure 5.9a shows the thermal

signal as a function of time for different specific heat CFRP values at a pulse duration of

5 s. It can be seen the tmax calculated for specific heat of 1200 J/kg.oC is 5.85 s while the

time is 5.4 s when the specific heat is 700 J/kg.oC. Figure 5.9b indicates the linear

increase in tmax with respect to the specific heat increase. However, this change in the

time of maximum thermal signal is insignificant compared to the differences in ΔTmax.

Table 5.4 CFRP specific heat simulations 4 to 36

Run

#

Pulse interval

(s)

Specific heat

(J/kg.oC) ΔTmax (oC) Change (%)

4 1 700 12.2 15.6

5 1 750 11.3 7.2

6 1 800 10.5 0

7 1 850 9.8 -6.42

8 1 900 9.2 -12.1

9 1 950 8.7 -17.2

10 1 1000 8.2 -21.8

11 1 1050 7.8 -25.9

12 1 1100 7.4 -29.7

13 1 1150 7.0 -33.1

14 1 1200 6.7 -36.2

15 3 700 24.5 14.6

16 3 750 22.8 6.8

17 3 800 21.3 0

18 3 850 20.0 -6.1

19 3 900 18.9 -11.5

20 3 950 17.8 -16.4

Numerical analysis

271

21 3 1000 16.9 -20.9

22 3 1050 16.0 -24.9

23 3 1100 15.2 -28.6

24 3 1150 14.5 -31.9

25 3 1200 13.8 -35.0

26 5 700 30.5 6.8

27 5 750 29.5 3.3

28 5 800 28.5 0

29 5 850 27.6 -3.1

30 5 900 26.7 -6.2

31 5 950 25.9 -9.1

32 5 1000 25.1 -11.8

33 5 1050 24.4 -14.4

34 5 1100 23.7 -16.9

35 5 1150 23.0 -19.3

36 5 1200 22.3 -21.6

(a) At 1 s pulse (b) At 3 s pulse

y = -0.0107x + 19.237R² = 0.9771

6

7

8

9

10

11

12

600 700 800 900 1000 1100 1200 1300

ΔT m

ax(o C

)

CFRP specific heat (J/(kg.oC))

y = -0.0197x + 36.942R² = 0.984

15

16

17

18

19

20

21

22

23

24

600 700 800 900 1000 1100 1200 1300

ΔT m

ax(o C

)

CFRP specific heat (J/(kg.oC))

Chapter Five

272

(c) At 5 s pulse (d) Changing of different pulses

Figure 5.8 Maximum thermal signal versus different specific heat of CFRP fabric

(a) (b)

Figure 5.9 Pulses of 5 s for different CFRP specific heat factors (a) Thermal signals versus time; (b) Time of maximum thermal signals

The second set of FE simulations examined the effect of changing the CFRP

conductivity. Thermal conductivity is defined as the measure of the ability of a material

to conduct heat and is determined by the rate of heat flow through a unit area in the

material influenced by temperature gradient in the direction of flow. It is measured in

watts per metre per degree Celsius or degree Kelvin. Simulation runs from 37 to 69

analyzed the conductivity variation from 6 W/m.oC to 16 W/m.oC over 3 pulse

y = -0.0162x + 41.581R² = 0.9955

21

22

23

24

25

26

27

28

29

30

31

32

33

600 700 800 900 1000 1100 1200 1300

ΔT m

ax(o C

)

CFRP specific heat (J/(kg.oC))

-35

-30

-25

-20

-15

-10

-5

0

5

10

15

20

600 700 800 900 1000 1100 1200 1300

Cha

nge

in Δ

T max

(%)

CFRP specific heat (J/(kg.oC))

5 s3 s1 s

-5

0

5

10

15

20

25

30

35

0 1 2 3 4 5 6 7 8 9 10 11

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

1200J/kg.oC1150J/kg.oC1100J/kg.oC1050J/kg.oC1000J/kg.oC950J/kg.oC900J/kg.oC850J/kg.oC800J/kg.oC750J/kg.oC700J/kg.oC

y = 0.0009x + 4.7714R² = 0.9995

5.3

5.4

5.5

5.6

5.7

5.8

5.9

6

600 700 800 900 1000 1100 1200 1300

t max

(s)

CFRP specific heat (J/(kg.oC))

Numerical analysis

273

durations, as shown in Table 5.5. The results shown in Table 5.5 indicate that the

maximum thermal signals on the CFRP surface are decreased by the increase in the

thermal CFRP conductivity factor in nonlinear trends for pulses of 1 s and 3 s and

present a more linear trend with 5 s pulses. The percentage changes are minor for all

pulse intervals. However, there are still differences between the thermal signals of the

different pulse lengths. The longer pulse duration shows the higher change. The changes

in time for the maximum thermal signals are very small at a scale of milliseconds. That

small influence on CFRP thermal conductivity of the thermal signal was due to the

small thickness of the CFRP layer.

Table 5.5 CFRP conductivity simulations 37 to 69

Run

#

Pulse interval

(s)

Conductivity

(W/m.oC) ΔTmax (oC)

37 1 6 10.563

38 1 7 10.565

39 1 8 10.566

40 1 9.38 10.566

41 1 10 10.565

42 1 11 10.564

43 1 12 10.562

44 1 13 10.56

45 1 14 10.557

46 1 15 10.554

47 1 16 10.551

48 3 6 21.37

49 3 7 21.379

50 3 8 21.377

51 3 9.38 21.379

52 3 10 21.381

53 3 11 21.382

54 3 12 21.382

Chapter Five

274

55 3 13 21.383

56 3 14 21.382

57 3 15 21.381

58 3 16 21.379

59 5 6 28.618

60 5 7 28.603

61 5 8 28.588

62 5 9.38 28.57

63 5 10 28.562

64 5 11 28.549

65 5 12 28.535

66 5 13 28.521

67 5 14 28.507

68 5 15 28.491

69 5 16 28.476

5.2.3.2 Influence of epoxy resin material thermal properties

The next set of analyses studied the changes in the specific heat of the epoxy layer

beneath the CFRP fabric sheet. Table 5.6 shows the results of simulations 70 to 90. The

epoxy specific heat varied in these runs from 1600 J/kg.oC to 1900 J/kg.oC. From the

results, it can be seen that the surface temperature above the defect area is not affected

by changes in the epoxy, due to the lack of epoxy layer under the bond defect. This

causes the defect to play the role of an insulator and prevent the heat from flowing

smoothly. However, the background temperature in the defect-free area is affected. The

surface temperature in this defect-free area decreases with the increase of the epoxy's

specific heat. This is because material of a higher specific heat needs a higher heat wave

and longer pulse to have an identical increase in the temperature at the surface. This

decrease in the background temperature produces an increase in the thermal signal. The

maximum thermal signal increases linearly with the increase of the epoxy's specific

Numerical analysis

275

heat. The maximum change was about 1% for epoxy specific heat of a value of greater

than 1900 J/kg.oC and subjected to pulses of 5 s duration.

Table 5.6 Epoxy specific heat simulations 70 to 90

Run Pulse interval (s) Specific heat (J/kg.oC) ΔTmax (oC)

70 1 1600 10.54

71 1 1650 10.55

72 1 1700 10.56

73 1 1750 10.57

74 1 1800 10.58

75 1 1850 10.59

76 1 1900 10.60

77 3 1600 21.30

78 3 1650 21.34

79 3 1700 21.37

80 3 1750 21.41

81 3 1800 21.45

82 3 1850 21.48

83 3 1900 21.524

84 5 1600 28.459

85 5 1650 28.515

86 5 1700 28.57

87 5 1750 28.624

88 5 1800 28.678

89 5 1850 28.73

90 5 1900 28.782

Similarly to the CFRP conductivity study, FE simulations 91 to 108 were conducted to

examine the effects of changing the conductivity of the epoxy over the range from 0.17

Chapter Five

276

W/m.oC to 0.22 W/m.oC. The same three pulse intervals were applied during these

simulations, as shown in Table 5.7. The results show that the maximum change in ΔTmax

is 1.76 %. Again, the maximum temperature on the surface above the defect was not

influenced by the alteration in the epoxy conductivity due to the presence of the bond

defect. The change in the epoxy conductivity leads the surface temperature to rise in the

defect-free area which causes an increase in the thermal signal. Compare the changes in

the ΔTmax of CFRP and epoxy conductivities; it can be seen that the effect of modifying

epoxy conductivity is higher than the change in CFRP conductivity, possibly due to the

thickness of the CFRP and epoxy layer. The epoxy has a thickness 3 times that of the

CFRP slim fabric sheet. The time for the maximum thermal signal is not affected by the

change of the epoxy conductivity values. Figure 5.10 shows the ΔTmax peak point versus

time for pulses with different epoxy thermal conductivities at 5 s pulses.

Numerical analysis

277

Table 5.7 Epoxy conductivity simulations 91 to 108

Run

#

Pulse interval

(s)

Conductivity

(W/m.oC) ΔTmax (oC)

91 1 0.17 10.661

92 1 0.18 10.631

93 1 0.19 10.599

94 1 0.2 10.566

95 1 0.21 10.53

96 1 0.22 10.491

97 3 0.17 21.616

98 3 0.18 21.541

99 3 0.19 21.463

100 3 0.2 21.379

101 3 0.21 21.292

102 3 0.22 21.199

103 5 0.17 29.074

104 5 0.18 28.916

105 5 0.19 28.748

106 5 0.2 28.57

107 5 0.21 28.38

108 5 0.22 28.179

Chapter Five

278

Figure 5.10 Time for maximum thermal signal of different epoxy conductivities

5.2.3.3 Influence of concrete substrate material thermal properties

A study of the influence of substrate concrete specific heat change on the thermal

signals on the specimen's surface was performed in runs 109 to 130. The concrete

specific heat varied from concrete stone specific heat at 76 J/kg.oC to light concrete

thermal properties at 1000 J/kg.oC. Table 5.8 shows the thermal results for the concrete

specific heat change for pulses of 1 s, 3 s and 5 s. The results show that the change of

concrete specific heat had a slight influence on the thermal responses detected. It can be

seen that the surface temperature above the defect area is not changed by the

modification of specific heat value. The slight change in the thermal signal was due to

the change in the surface temperature above the defect-free area. These changes in the

maximum thermal signal show a linear trend. The rate of thermal responses increases

with increasing heat pulse duration.

The time for the maximum thermal signal also increases linearly with increasing

concrete specific heat, as shown in Figure 5.11. Pulses with longer intervals show

higher changes in tmax. However, the change in tmax was small when it was increased for

0.01 s with each 80 J/kg.oC lift in concrete specific heat at pulses of 5 s.

25

26

26

27

27

28

28

29

29

30

30

4.50 4.85 5.20 5.55 5.90 6.25

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

0.22W/m.oC

0.21W/m.oC

0.2W/m.oC

0.19W/m.oC

0.18W/m.oC

0.17W/m.oC

Numerical analysis

279

Table 5.8 Concrete specific heat simulations 109 to 130

Run

#

Pulse interval

(s)

Specific heat

(J/kg.oC) ΔTmax (oC)

109 1 760 10.564

110 1 800 10.566

111 1 840 10.567

112 1 880 10.568

113 1 920 10.569

114 1 960 10.57

115 1 1000 10.571

116 3 760 21.378

117 3 800 21.379

118 3 840 21.381

119 3 880 21.382

120 3 920 21.383

121 3 960 21.383

122 3 1000 21.384

123 5 760 28.557

124 5 800 28.57

126 5 840 28.582

127 5 880 28.593

128 5 920 28.603

129 5 960 28.613

130 5 1000 28.623

Chapter Five

280

Figure 5.11 Pulse of 5 s for different concrete specific heat factors: Time of maximum

thermal signals

Simulation runs 131 to 148 were performed to investigate the effect of changing the

concrete conductivity factor. The conductivity of concrete was studied over the range

from 1.3 W/m.oC to 1.8 W/m.oC. Table 5.9 summarizes the results of these simulation

runs.

Similar to the changes of the epoxy, the thermal signal increases only slightly due to the

temperature rise at the detect-free area. However, due to the location of the concrete

layer with respect to the applied heat pulse, the effect was less than 0.01 oC for the

entire studied range of conductivities. The tmax shows no change for all different

concrete conductivities for the same heating pulse duration.

y = 0.0001x + 5.465R² = 1

5.505.515.525.535.545.555.565.575.585.595.605.615.625.635.645.65

700 800 900 1000 1100 1200

t max

(s)

Concrete specific heat (J/(kg.oC))

Numerical analysis

281

Table 5.9 Concrete conductivity simulations 131 to 148

Run

#

Pulse interval

(s)

Conductivity

(W/m.oC) ΔTmax (oC)

131 1 1.3 10.565

132 1 1.4 10.565

133 1 1.5 10.566

134 1 1.6 10.566

135 1 1.7 10.566

136 1 1.8 10.566

137 3 1.3 21.379

138 3 1.4 21.379

139 3 1.5 21.379

140 3 1.6 21.38

141 3 1.7 21.38

142 3 1.8 21.38

143 5 1.3 28.561

144 5 1.4 28.566

145 5 1.5 28.57

146 5 1.6 28.574

147 5 1.7 28.578

148 5 1.8 28.582

5.2.3.4 Summary of Parametric Study 2

A total of 148 simulations runs were conducted in Parametric Study 2 to examine the

influence of changes in the thermal properties (specific heat and conductivity) of all

materials that involved in strengthened CFRP-concrete systems. The simulated model

was subjected to three different pulse lengths. A range was chosen to study the variation

of specific heat and conductivity for CFRP, epoxy and concrete independently. The

following points represent the findings of this study:

Chapter Five

282

Maximum thermal signal reduces in a linear trend by increasing CFRP specific

heat.

Time for the maximum thermal signal increases linearly with increasing CFRP

specific heat.

The longer pulse duration shows the higher change for the same values of

specific CFRP heat and conductivity.

Maximum thermal signal reduces with increasing CFRP conductivity value.

By increasing the pulse duration, the rate of ΔTmax change decreases in both

specific heat and conductivity CFRP simulations.

The surface temperature above the defect shows no alteration with the

modification of specific heat and conductivity for both concrete and epoxy

materials.

Maximum thermal signal increases with increasing specific heat and

conductivity values for both concrete and epoxy substrate materials.

By increasing the pulse duration, the rate of ΔTmax change increases in both

specific heat and conductivity for both concrete and epoxy substrate simulations.

Time for maximum thermal signal (tmax) shows no change with increasing epoxy

and concrete conductivity values.

Moreover, by comparing the effect of epoxy and concrete specific heat alteration, it can

be seen that the thermal signal is affected more in the epoxy specific heat change than

the concrete, possibly because the epoxy layer is nearer to the surface than the concrete,

which means that the change in the thermal properties of this layer has a greater role.

However, the greatest ΔTmax and tmax changes are experienced by changing the CFRP

specific heat value.

In summary, altering the specific heat or conductivity factor for both substrate epoxy

and concrete layer has no important influence on the thermal signals or the time for

these signals. Only the change in the specific heat or conductivity of the CFRP material

properties has a greater influence on the thermal signal. Nevertheless, these changes in

signals do not cause serious issues for detectability. A bond defect still has a very

recognizable thermal signal even with short pulse duration.

Numerical analysis

283

5.2.4 Parametric Study 3: Thickness of materials

The third parametric study focused on the effect of the thickness of the CFRP fabric,

epoxy and concrete layers on the thermal responses. The same model geometry

dimensions and material types were adopted in these simulations, adiabatic boundary

conditions were assumed for all runs. The study was subdivided into three sets to collect

thermal results of changes in the thickness of CFRP, epoxy and concrete. For all sets,

the thermal input heat flux intensities were thermal loads calculated from the

experimental program, as shown in Table 5.2. Each simulation run set applied three

pulse durations of 1 s, 3 s and 5 s.

5.2.4.1 CFRP layer thickness

The first set contained 26 runs designed to simulate changes in CFRP layer thickness.

The thickness of CFRP varied from 0.175 mm to 0.55 mm during the simulations for

each of the three pulse lengths. The boundary edges of the thickness range were chosen

to meet the minimum and maximum thicknesses of the CFRP fabrics that are

commercially available. The thickness of the epoxy layer and concrete substrate were

fixed at 0.9 mm and 50 mm respectively. The data from Table 5.10 show interesting

results. The changes in CFRP thickness significantly affect the maximum thermal

signals at the defect. Maximum thermal signal detectability is enhanced by up to 50 %

when the CFRP thickness 0.175 mm. On the other hand, the recognition of the

maximum thermal signal is difficult when the value of ΔTmax reaches only 4 oC when 1

s pulse is applied to the 0.55 mm CFRP fabric layer.

Thicker fabric layers in the CFRP application show smaller ΔTmax. The decrease in

ΔTmax is non-linear by increasing CFRP thickness, as shown in Figure 5.12. From

Figure 5.12d, it can be seen that by increasing the pulse duration time, the signal change

rate decreases, mainly due to trapping more heat over the defect area, which leads to

increased signals in the defect area. Moreover, the time for the maximum thermal signal

increases linearly by increasing CFRP thickness, as revealed in Figure 5.13.

Chapter Five

284

Table 5.10 CFRP thickness simulations 149 to 175

Run

#

Pulse interval

(s)

CFRP fabric

thickness (mm) ΔTmax (oC) Change (%)

149 1 0.175 15.5 47.3

150 1 0.2 13.4 27.5

151 1 0.25 10.5 0

152 1 0.3 8.6 -18.4

153 1 0.35 7.2 -31.3

154 1 0.4 6.2 -40.9

155 1 0.45 5.4 -48.4

156 1 0.5 4.8 -54.3

157 1 0.55 4.3 -59.1

158 3 0.175 30.8 44.3

159 3 0.2 26.9 26.2

160 3 0.25 21.39 0

161 3 0.3 17.53 -17.9

162 3 0.35 14.8 -30.5

163 3 0.4 12.8 -39.9

164 3 0.45 11.2 -47.3

165 3 0.5 10.0 -53.1

166 3 0.55 8.9 -57.9

167 5 0.175 33.8 18.4

168 5 0.2 31.4 10.0

169 5 0.25 28.5 0

170 5 0.3 25.1 -11.9

171 5 0.35 22.83 -20.0

172 5 0.4 20.8 -27.0

173 5 0.45 19.1 -33.0

174 5 0.5 17.6 -38.2

175 5 0.55 16.3 -42.8

Numerical analysis

285

(a) At 1 s pulse (b) At 3 s pulse

(c) At 5 s pulse (d) Changing of different pulses

Figure 5.12 Maximum thermal signal versus CFRP thickness

y = 85.19x2 - 89.484x + 28.114R² = 0.9922

0

2

4

6

8

10

12

14

16

18

0.1 0.2 0.3 0.4 0.5 0.6

ΔT m

ax(o C

)

CFRP thickness (mm)

y = 161.63x2 - 171.4x + 55.018R² = 0.9934

0

5

10

15

20

25

30

35

0.1 0.2 0.3 0.4 0.5 0.6

ΔT m

ax(o C

)

CFRP thickness (mm)

y = 76.921x2 - 101.26x + 48.923R² = 0.9987

15

17

19

21

23

25

27

29

31

33

35

0.1 0.2 0.3 0.4 0.5 0.6

ΔT m

ax(o C

)

CFRP thickness (mm)

-60

-40

-20

0

20

40

60

0.1 0.2 0.3 0.4 0.5 0.6

Cha

nge

in Δ

T max

(%)

CFRP thickness (mm)

1 s3 s5 s

Chapter Five

286

(a) (b)

Figure 5.13 Pulses of 5 s for different CFRP thicknesses (a) Thermal signals versus time; (b) Time of maximum thermal signals

5.2.4.2 Epoxy layer thickness

Runs from 176 to 196 were designed to analyze the change in the epoxy thickness layer.

The thickness of the epoxy varies in these runs from 0.3 mm to 1.5 mm. Again three

pulse intervals of 1 s, 3 s and 5 s were applied with thermal intensities of 977.77 W/m2,

922.22 W/m2 and 1055.56 W/m2 respectively. The change in the epoxy thickness has

less thermal influence than the change in CFRP thickness. However, reducing the epoxy

layer from 0.9 mm to 0.3 mm reduces ΔTmax by more than 5 % at 1 s pulse, as shown in

the thermal results of simulation runs 176 and 179 in Table 5.11. By having a thicker

layer of epoxy, the change in ΔTmax reduces and the trend has more flat behaviour, as

shown in Figure 5.14.

Contrary to the CFRP thickness change, the signal change rate for epoxy thickness

modification increased by increasing the pulse duration time, as shown in Figure 5.14d.

This is due to the temperature decrease in the background defect-free area, which causes

the increase in ΔTmax in the defect area.

For all runs with the same pulse interval the time the maximum thermal signal showed

no significant change. The tmax values were 2.42 s, 3.9 s and 5.55 s for 1 s, 3 s and 5 s

pulses.

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6 7 8 9 10

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

0.55 mm0.5 mm0.45 mm0.4 mm0.35 mm0.3 mm0.25 mm0.2 mm0.175 mm

y = 1.7143x + 5.1571

5

5.2

5.4

5.6

5.8

6

6.2

0.1 0.2 0.3 0.4 0.5 0.6

t max

(s)

CFRP thickness (mm)

Numerical analysis

287

Table 5.11 Epoxy thickness simulations 176 to 196

Run

#

Pulse interval

(s)

Epoxy thickness

(mm) ΔTmax (oC) Change (%)

176 1 0.3 11.1 5.3

177 1 0.5 10.8 2.7

178 1 0.7 10.6 0.9

179 1 0.9 10.5 0

180 1 1.1 10.5 -0.4

181 1 1.3 10.4 -0.6

182 1 1.5 10.4 -0.7

183 3 0.3 22.4 4.9

184 3 0.5 21.7 1.9

185 3 0.7 21.5 0.5

186 3 0.9 21.3 0

187 3 1.1 21.3 -0.2

188 3 1.3 21.3 -0.3

189 3 1.5 21.3 -0.3

190 5 0.3 31.0 8.5

191 5 0.5 29.8 4.4

192 5 0.7 29.0 1.6

193 5 0.9 28.5 0

194 5 1.1 28.2 -0.9

195 5 1.3 28.1 -1.5

196 5 1.5 28.0 -1.8

Chapter Five

288

(a) At 1 s pulse (b) At 3 s pulse

(c) At 5 s pulse (d) Changing of different pulses

Figure 5.14 Maximum thermal signal versus epoxy thicknesses

5.2.4.3 Concrete layer thickness

The third run set was designed to study the influence of changing the concrete substrate

thickness. Concrete structures of thicknesses varying from 30 mm to 600 mm were

studied for the three pulses of 1 s, 3 s and 5 s. Both ΔTmax and tmax showed negligible

changes in the concrete thickness. Table 5.12 summarizes the results of runs 197 to 214

are allocated to this part of the study.

As can be seen from the results, the maximum percentage change in the maximum

detected thermal signal was around 1 %. This alteration is very minor, possibly due to

y = 0.6744x2 - 1.7111x + 11.561R² = 0.9915

10.4

10.5

10.6

10.7

10.8

10.9

11

11.1

11.2

0.2 0.5 0.8 1.1 1.4 1.7

ΔT m

ax(o C

)

Epoxy thickness (mm)

y = 1.4042x2 - 3.3343x + 23.219R² = 0.9595

21

21.2

21.4

21.6

21.8

22

22.2

22.4

22.6

0.2 0.5 0.8 1.1 1.4 1.7

ΔT m

ax(o C

)

Epoxy thickness (mm)

y = -1.8264x3 + 7.6277x2 - 11.116x + 33.719

26

27

28

29

30

31

32

0.2 0.5 0.8 1.1 1.4 1.7

ΔT m

ax(o C

)

Epoxy thickness (mm)

-2

0

2

4

6

8

10

0.2 0.5 0.8 1.1 1.4 1.7

Cha

nge

in Δ

T max

(%)

Epoxy thickness (mm)

1 s3 s5 s

Numerical analysis

289

the location of the concrete layer with respect to the heat wave application. The results

of this study highlight the minor effect of concrete thickness on the detected thermal

signal, and confirm the reliability of the adiabatic boundary conditions assumed in all

parametric studies presented in this chapter.

Table 5.12 Concrete thickness simulations 197 to 214

Run

#

Pulse interval

(s)

Concrete

thickness (mm) ΔTmax (oC)

197 1 30 10.563

198 1 50 10.566

199 1 100 10.511

200 1 200 10.454

201 1 400 10.556

202 1 600 10.548

203 3 30 21.377

204 3 50 21.379

205 3 100 21.174

206 3 200 21.041

207 3 400 21.382

208 3 600 21.314

209 5 30 28.551

210 5 50 28.57

211 5 100 28.588

212 5 200 29.041

213 5 400 28.395

214 5 600 28.259

5.2.4.4 Summary and finding of Parametric Study 3

Simulations 149 to 214 were carried out to study the effect of changing the material

thicknesses of CFRP-epoxy-concrete systems. The investigation was subdivided into

Chapter Five

290

three parts to address material thickness changes in the CFRP, epoxy and concrete

components. The following are the conclusions of this study:

The maximum thermal signal decreases significantly in a nonlinear trend by

increasing CFRP fabric thickness.

By increasing the pulse length applied to different CFRP thicknesses, the ΔTmax

change rate decreases.

By increasing CFRP thickness, tmax increases linearly.

Epoxy thickness has less influence than CFRP thickness on thermal response.

A thicker layer of epoxy shows smaller ΔTmax.

By increasing the pulse length applied to different epoxy thicknesses, the ΔTmax

change rate increases.

Times for the maximum thermal signal show no change when epoxy thickness is

modified.

ΔTmax shows negligible changes at less than 1 oC when concrete thickness is

varied, while tmax shows no change.

5.2.5 Parametric Study 4: Thermal loads and periods

The extensive experimental program presented in Chapter 4 showed that the effects of

thermal load intensity playing a major role in bond defect detectability. However, input

thermal load intensities were limited to only 4 values for each pulse duration, where the

lamp was positioned at 50 cm, 70 cm, 100 cm and 120 cm from the specimen

investigated. A study of a wider range of thermal load is required to understand to what

extend that the thermal injection may influence the thermal results, and what is the limit

causing the epoxy to rise to an undesirable temperature beyond its glass transition

temperature.

In this parametric study, simulations with different intensity pulses applied to the top

surface of the CFRP fabric were analyzed. The same concrete, epoxy and CFRP

materials thermal properties that were used in the previous parametric studies were used

in the model construction. In all simulated analytical runs in this simulation, a cooling

function of convection type was applied to the top CFRP surface after the application of

Numerical analysis

291

different heat pulse waves. Air cooling convection factors of (20-25) W/m2 oC, (20-40)

W/m2 oC and 80 W/m2 oC were used for pulses of 1 s, 3 s and 5 s respectively.

Adiabatic temperature conditions were applied to all other surfaces in the model, and

the ambient temperature was 20 oC. A total of 44 simulation runs were performed to

study the effect of changing the heat flux intensity for different pulse intervals. The heat

waves were applied to the CFRP surface with different pulse lengths and of a wide

range of thermal intensities, as shown in Table 5.13. Pulse durations were at 1 s, 3 s and

5 s, while the pulse heat flux intensity varied from 444 W/m2 to 2000 W/m2. The FE

model surface had the dimensions of Specimen 2 being 300 mm wide and 300 long. The

heat flux intensity was converted to Watts, as shown in Table 5.4. Information on the

maximum thermal signals recorded on the specimen surfaces for each run is tabulated in

the last column of Table 5.13.

ANSYS runs from 215 to 229 had the same pulse interval of 1 s with different thermal

loadings. Pulses of 3 s at different thermal input loads were studied in runs 230 to 244,

and final group of simulation runs from 245 to 259 investigated the range of 5 s pulse

intervals.

The results shown in Figure 5.15 indicate that the maximum thermal signal increases

linearly with the increasing applied to the specimen. Moreover, the changing rate of the

maximum thermal signal increases with the pulse interval increase. The ΔTmax detection

is enhanced by 1.08 oC, 2.32 oC and 2.71 oC for each 100 W/m2 increase in injected

thermal loads during pulses of 1 s, 3 s and 5 s respectively.

Figure 5.16 shows interesting results. The time for the maximum thermal signal is

independent of the injected heat wave and is not affected by changing the value of the

input heat wave intensity within the same pulse interval. For all curves of 1 s pulses and

different thermal loads in Figure 5.16a the tmax remains at 2.42 s. The same pattern

appears in Figures 5.16b and 5.16c of 3 s and 5 s pulses where tmax continues to record

the same times of 3.9 s and 5.55 s.

Chapter Five

292

Table 5.13 Thermal load studies 215 to 259

Run #

Pulse

interval

(s)

Input heat flux

(W/m2)

Input heat

flux (W)

ΔTmax

(oC)

215 1 444.44 40 4.8

216 1 555.55 50 6.0

217 1 666.66 60 7.2

218 1 777.77 70 8.4

219 1 888.88 80 9.6

220 1 1000 90 10.8

221 1 1111.11 100 12.0

222 1 1222.22 110 13.27

223 1 1333.33 120 14.4

224 1 1444.44 130 15.6

225 1 1555.55 140 16.8

226 1 1666.66 150 18.0

227 1 1777.77 160 19.2

228 1 1888.88 170 20.4

229 1 2000 180 21.6

230 3 444.44 40 10.3

231 3 555.55 50 12.8

232 3 666.66 60 15.4

233 3 777.77 70 18.0

234 3 888.88 80 20.6

235 3 1000 90 23.1

236 3 1111.11 100 25.7

237 3 1222.22 110 28.3

238 3 1333.33 120 30.9

239 3 1444.44 130 33.4

240 3 1555.55 140 36.0

241 3 1666.66 150 38.6

242 3 1777.77 160 41.2

243 3 1888.88 170 43.7

244 3 2000 180 46.3

245 5 444.44 40 12.0

246 5 555.55 50 15.0

Numerical analysis

293

247 5 666.66 60 18.0

248 5 777.77 70 21.0

249 5 888.88 80 24.0

250 5 1000 90 27.0

251 5 1111.11 100 30.0

252 5 1222.22 110 33.0

253 5 1333.33 120 36.0

254 5 1444.44 130 39.0

255 5 1555.55 140 42.1

256 5 1666.66 150 45.1

257 5 1777.77 160 48.1

258 5 1888.88 170 51.1

259 5 2000 180 54.1

Figure 5.15 Thermal signal versus input heat flux for different pulses

y = 0.0108x + 0.0009R² = 1

y = 0.0232x + 6E-05R² = 1

y = 0.0271x - 0.0002R² = 1

0

10

20

30

40

50

60

0 400 800 1200 1600 2000

Ther

mal

Sig

nal ∆

T (o C

)

Input heat flux (W/m2)

1 s

3 s

5 s

Chapter Five

294

(a) At 1 s pulse interval

(b) At 3 s pulse interval

0

5

10

15

20

25

0 20 40 60

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

455 W/m2555 W/m2666 W/m2777 W/m2888 W/m21000 W/m21111 W/m21222 W/m21333 W/m21444 W/m21555 W/m21666 W/m21777 W/m21888 W/m22000 W/m2

-5

0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20 25 30 35 40

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

455 W/m2555 W/m2666 W/m2777 W/m2888 W/m21000 W/m21111 W/m21222 W/m21333 W/m21444 W/m21555 W/m21666 W/m21777 W/m21888 W/m22000 W/m2

Numerical analysis

295

(c) At 5 s pulse interval

Figure 5.16 Thermal signals versus time at different input thermal loading

5.2.5.1 Summary of Parametric Study 4

In bond defect detection, input heat flow intensity and duration are critical parameters

which control the value of the detected signal. Different heat wave intensities were

investigated in this study with different pulse durations. The simulation runs presented

here can help the thermographer to have the best input heat wave design in terms of

intensity and pulse length. The following are some of the conclusions from this study:

The maximum thermal signal increases linearly the increasing heat.

The changing rate of maximum thermal signal increases with increasing pulse

interval.

The time for maximum thermal signal is independent of the applied heat wave.

The results of this study provide a procedure of the thermal input versus the thermal

signals expected to provide the best IRT detection for the specific bond defect.

The results presented in Table 5.13 may provide guidelines for thermographers and help

to characterize the thermal load input needed for the desired thermal signal for different

-5

5

15

25

35

45

55

0 5 10 15 20 25 30

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

444 W/m2555 W/m2666 W/m2777 W/m2888 W/m21000 W/m21111 W/m21222 W/m21333 W/m21444 W/m21555 W/m21666 W/m21777 W/m21888 W/m22000 W/m2

Chapter Five

296

types of CFRP fabric designs. The maximum thermal load intensity of the pulse can be

designed according to the minimum desired thermal signal.

5.3 Finite element studies of bonding defects under double CFRP

fabric layers

5.3.1 Modeling

5.3.1.1 Geometry

A bond defect was created in this model with two CFRP layers, and the same parametric

studies involved in the FEM analyses presented in the previous sections in this chapter

were conducted. The modeling involved a study of various parameters that might

influence the detectability of a bond defect in the concrete-CFRP bonding zone. All the

analytical simulations presented in these studies were executed using FE software

ANSYS 13.

A full 3-D model was constructed to simulate this specimen. The concrete dimensions

were 300 mm wide, 300 mm long, and 50 mm deep. Both carbon fibre sheets used in

this specimen were type CF140 with 0.25 mm thickness. The epoxy resin layers were

MBrace saturant with thickness of 0.5 mm. The thermal materials properties are

summarized in Table 5.1. The properties of air were assigned to model the unbond

defect. The air properties were adopted from the ANSYS material library. The air void

was presented at the defect location between the concrete and the first CFRP fabric

layer. The bond defect design was very similar to the defect implanted in Specimen 6.

Although, the dimensions of the defect were not exactly the same, the defect was wide

enough to make a comparison between the results of defect UB064 from the

experimental program and the FE simulation studies. The epoxy layer thickness used in

Specimen 6 was the same as the simulated epoxy layers shown in Figure 5.17.

Numerical analysis

297

Figure 5.17 Model for bond defect with double CFRP fabric simulation

5.3.1.2 Meshing

Different meshing methods were used to model the different layers of simulations in the

double CFRP system. To improve the heat transfer between the simulated layers, multi-

zone meshes were assigned to the contact surfaces of the concrete, epoxy and CFRP

layers. The Mapped-face meshing method was employed for the external surface of the

2nd CFRP CF140, where the temperature was planned to be recorded. This method of

meshing allows adjustment and control for element size. Sweep meshing methods were

utilized in the fine epoxy and CFRP layers. Each epoxy layer was subdivided into three

element layers. Similarly, each CFRP was subdivided by the sweep method into three

element layers, as shown in Figure 5.18.

Heat flux (W/m2)

CF140 (0.25mm)

Epoxy (0.5mm)

Concrete (50mm)

Defect

dT/dy = zero

dT/dx = zero

dT/dz = zero

CF140 (0.25mm)

Epoxy (0.5mm)

Chapter Five

298

Figure 5.18 Meshing details of double CFRP layers model

5.3.1.3 Thermal boundary conditions, loading and results

Adiabatic boundaries were applied for all surfaces that did not receive the pulse heat

wave (where ΔT, in both x and y directions, were assumed to be zero). Figure 5.17

shows the model and adiabatic boundary edge conditions. Convection cooling was used

to simulate the effect of free cooling on the CFRP surface during the IR test. The same

air cooling convection factor that was used in 5 s pulses during simulations of

Parametric Studies 1 to 4 was applied in the double CFRP sheets modeling.

PTT with 5 s pulse length only was applied to investigate detectability. The 1 s and 3 s

pulse durations were not investigated due to their low thermal response results. The 5 s

pulses were applied uniformly on the top surface of the 2nd CFRP layer with 1055 W/m2

heat flux intensity.

Surface temperatures were recorded at several points during the thermal simulations.

Thermal signals as a function of time were captured for all simulated trials and the time

of the maximum signal tmax was also documented.

Numerical analysis

299

5.3.2 Parametric Study 5: Verification of analytical simulations

FE simulation run 260 was designed to verify and compare the results of defect UB064

of the experimental program. Analysis setting with 0.1 s as minimum was used to

perform this simulation, and a 120 s time frame was adopted in the analysis.

The maximum thermal signal of this defect in Specimen 6 from the experimental

laboratory program was 7.2 oC. The FE simulation shows ΔTmax of 7.609 oC. The

surface temperature above the defect in the experimental runs was 36.8 oC and the FE

analysis showed 36.055 oC. This small difference at less than 0.7 oC is verifies the

model as excellent for representing defect thermal behaviour. The comparison of the

thermal signals and surface temperature versus time of experimental and simulation

runs for pulses with 5 s length and 1055 W/m2 of defect UB064 is shown in Figure 5.19.

(a) Thermal signal of UB064

-2

0

2

4

6

8

10

0 10 20 30 40 50 60

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

ExperimentalSimulation

Chapter Five

300

(b) Surface temperature above the defect

Figure 5.19 UB064 defect experimental versus simulation data

5.3.3 Parametric Study 6: Influence of materials thermal properties on

defect detection

The 6th FE simulation study concentrated on the effect of changing the specific heat and

conductivity properties on thermal responses. The thermal properties of CFRP, epoxy

and concrete were the same as those used in previous parametric studies shown in Table

5.1. This simulation was subdivided into three parts to study the changes in the three

composite materials. The effect of changes in CFRP thermal properties is highlighted in

the first section. The second and the third sections were focused on the thermal

properties of the resin and concrete substrate materials. Pulses with 5 s were the only

pulse lengths employed in Parametric Study 6 with average intensities of 1055 W/m2.

5.3.3.1 Influence of CFRP material thermal properties

This part studied the effect of changing CFRP heat specification and conductivity of

both CFRP sheets modeled to represent the defect in the bond zone of the first CFRP

layer and the concrete substrate. The densities and thermal properties of the concrete

and epoxy are shown in Table 5.1. The specific heat of CFRP is 800 J/kg.oC when

18

20

22

24

26

28

30

32

34

36

38

0 30 60

Surfa

ce T

empe

ratu

re (o C

)

Time (s)

ExperimentalSimulation

Numerical analysis

301

conductivities are under investigating. The same value of 9.38 W/m. oC was assigned to

the conductivity thermal factor when the change of the specific heat of the CFRP was

studied.

Simulation run results of changing the CFRP specific heat are summarized in Table

5.14. The results show the change is the maximum thermal signal when the specific heat

ranged from 700 J/kg.oC to 1200 J/kg.oC. As shown in this table, the maximum thermal

signal decreases about 20 % when the specific heat increases 400 J/kg.oC. Figure 5.20a

shows the maximum thermal signal as a function of the specific heat for different

applied pulses. The results indicate that the signal is decreased linearly by increasing the

specific heat of the CFRP.

Comparing the values of ΔTmax above defects UB021 and UB064 with results of single

and double CFRP sheets, it can be seen that the thermal signals are decreased by adding

another layer of CFRP. Moreover, the rate of decrease of ΔTmax reduces from 0.0162 to

0.0039 when the defect is covered with double CFRP for the same pulse duration.

Comparisons of Figures 5.8c and 5.20a highlight this point. Surface temperature

changes for different specific heats in both single and double CFRP sheets show similar

trends, as shown in Figures 5.9a and 5.20b. However, the tmax values in the double

CFRP system register higher times at 1.35 s and 1.48 s in the differences in detection of

ΔTmax when specific heats are 700 J/kg.oC and 1200 J/kg.oC respectively. The rate of

tmax increase for single and double CFRP is 0.09 to 0. 11 for each 100 J/kg.oC rise in the

specific heat value, as illustrated in Figures 5.9b and 5.20c.

Table 5.14 Double CFRP sheets specific heat simulations 261 through 271

Run

#

Pulse interval

(s)

Specific heat

(J/kg.oC) ΔTmax (oC) Change (%)

261 5 700 8.0 6.4

262 5 750 7.8 3.1

263 5 800 7.6 0

264 5 850 7.3 -2.9

Chapter Five

302

265 5 900 7.1 -5.7

266 5 950 6.9 -8.3

267 5 1000 6.7 -10.8

268 5 1050 6.6 -13.1

269 5 1100 6.4 -15.4

270 5 1150 6.2 -17.5

271 5 1200 6.1 -19.6

(a) Thermal signal (b) Surface temperature

(c) Time of maximum thermal signals

Figure 5.20 Thermal results versus different specific heats of defect under double CFRP fabrics

y = -0.0039x + 10.773R² = 0.9943

2

3

4

5

6

7

8

9

600 700 800 900 1000 1100 1200 1300

ΔT m

ax(o C

)

CFRP specific heat (J/(kg.oC))

0

2

4

6

8

0 1 2 3 4 5 6 7 8 9 10 11 12

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

700 J/kg.oC750 J/kg.oC800 J/kg.oC850 J/kg.oC900 J/kg.oC950 J/kg.oC1000 J/kg.oC1050 J/kg.oC1100 J/kg.oC1150 J/kg.oC1200 J/kg.oC

y = 0.0011x + 5.98R² = 1

6.5

6.6

6.7

6.8

6.9

7

7.1

7.2

7.3

7.4

7.5

600 700 800 900 1000 1100 1200 1300

t max

(s)

CFRP specific heat (J/(kg.oC))

Numerical analysis

303

FE simulations were set up to investigate the effect of changing the CFRP conductivity.

Table 5.15 summarizes the simulation results from runs 272 to 282which analyzed the

conductivity variation from 6 W/m.oC to 16 W/m.oC at 5 s pulse duration. The influence

was very small with less than 1 % for the entire range of variation.

The results indicate that the maximum thermal signals on the CFRP surface are

decreased slightly by the increase in the thermal CFRP conductivity factor in a linear

trend with the 5 s pulse. There is no change in tmax values over the investigated

conductivity range. Similarly to the single CFRP conductivity investigation, that small

influence of changing the CFRP thermal conductivity over the thermal signal was due to

the small thickness of the CFRP layers. A comparison of the changes in the thermal

signals of CFRP conductivity in single and double CFRP systems reveals that the

maximum thermal signals is increased by the increase of the conductivity contrary to

the single CFRP system for the same pulse interval. This is mainly due to the effect of

the additional CFRP layer and its epoxy resin which raiser the heat to travel less easily

than above the defect in the single CFRP.

Table 5.15 Double CFRP conductivity simulations 272 to 282

Run

#

Pulse interval

(s)

Conductivity

(W/m.oC) ΔTmax (oC)

272 5 6 7.589

273 5 7 7.594

274 5 8 7.6

275 5 9.38 7.609

276 5 10 7.614

277 5 11 7.62

278 5 12 7.628

279 5 13 7.634

280 5 14 7.64

281 5 15 7.646

282 5 16 7.652

Chapter Five

304

5.3.3.2 Influence of epoxy resin material thermal properties

Changes in the specific heat of the epoxy layers beneath the two CFRP fabric sheets are

presented in the simulation analyses from 283 to 289. Table 5.16 and Figure 5.21 show

the results of these simulation runs. The epoxy specific heat varied in these runs from

1600 J/kg.oC to 1900 J/kg.oC. From the results, it can be seen that the maximum thermal

signal is decreased linearly by the increase of the epoxy specific heat. Figure 5.21b

compares the changing rates in the thermal signal of single and double CFRP layers. It

can be seen from this figure that the influence of changing epoxy properties is higher in

the double system compared to the single system due to the increase in the number of

epoxy layers. The rate slope is also changed for the same reason, as the epoxy layer

above the defect changes the thermal signal slope rate. As shown in Figure 5.21, the

maximum thermal signal reduce linearly with the increase of epoxy specific heat. The

maximum change was about 6.26 % (with less than 0.7 oC) for epoxy specific heat

greater than 1900 J/kg.oC. The time for maximum thermal signal was fixed at 6.85 s and

not affected by the change of the epoxy specific heat.

Table 5.16 Epoxy specific heat simulations 283 to 289

Run

#

Pulse interval

(s)

Specific heat

(J/kg.oC) ΔTmax (oC)

283 5 1600 7.872

284 5 1650 7.739

285 5 1700 7.609

286 5 1750 7.484

287 5 1800 7.363

288 5 1850 7.245

289 5 1900 7.132

Numerical analysis

305

(a) (b)

Figure 5.21 (a) Maximum thermal signals versus different specific heats of epoxy, (b) Changing rates for both single and double layers of CFRP

Similarly to the CFRP conductivity study of the single CFRP sheet, FE simulations 290

to 295 were conducted to examine the effects of changing the conductivity of epoxy

over the range from 0.17 W/m.oC to 0.22 W/m.oC. The results of these simulation runs

are presented in Table 5.17. The maximum change in ΔTmax was 3.7 %. However, the

change in temperature was slight at less than 1 oC. The change in the epoxy conductivity

leads the surface temperature to rise in the defect-free area, which causes an increase in

the thermal signal. In the CFRP double system, by comparing the changes in ΔTmax due

to changes in CFRP and epoxy conductivities, it can be seen that the effect of modifying

epoxy conductivity is slightly higher than changing the CFRP conductivity. The time

for the maximum thermal signal was not affected by the change of the epoxy

conductivity values.

y = -0.0025x + 11.81R² = 0.9992

7

7.1

7.2

7.3

7.4

7.5

7.6

7.7

7.8

7.9

8

1500 1600 1700 1800 1900 2000

ΔT m

ax(o C

)

Epoxy specific heat (J/(kg.oC))

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

1500 1600 1700 1800 1900 2000

Cha

nge

in Δ

T max

(%)

Epoxy specific heat (J/(kg.oC))

Single CFRPDouble CFRP

Chapter Five

306

Table 5.17 Epoxy conductivity simulations 290 to 295

Run

#

Pulse interval

(s)

Conductivity

(W/m.oC) ΔTmax (oC)

290 5 0.17 7.406

291 5 0.18 7.509

292 5 0.19 7.609

293 5 0.2 7.706

294 5 0.21 7.801

295 5 0.22 7.892

5.3.3.3 Influence of concrete substrate material thermal properties

Studies of the effect of changing the substrate concrete specific heat on the thermal

signal were carried out in runs 296 to 302. Similarly to the concrete investigations in

Parametric Study 2, the concrete specific heat varied from concrete stone specific heat

at 76 J/kg.oC to the light concrete at 1000 J/kg.oC. Table 5.18 illustrates these

simulation results. The results show that changing the concrete specific heat has very

slight influence on the detected thermal responses with less than 0.5 oC difference over

the entire range. These small changes in the maximum thermal signal were showed a

linear trend. The time for the maximum thermal signal was not influenced by change of

the concrete specific heat.

Table 5.18 Concrete specific heat simulations 296 to 302

Run

#

Pulse interval

(s)

Specific heat

(J/kg.oC) ΔTmax (oC)

296 5 760 7.602

297 5 800 7.609

298 5 840 7.617

299 5 880 7.624

300 5 920 7.63

301 5 960 7.636

302 5 1000 7.642

Numerical analysis

307

Studies of the conductivity of concrete were conducted over a range from 1.3 W/m.oC to

1.8 W/m.oC. Simulation runs from 303 to 308 were conducted to investigate the effects

of changing the concrete conductivity factor, and the results of these simulation runs are

exhibited in Table 5.19. The effect of the change is very small at less than 0.02 oC for

the entire range of conductivities studied. The tmax shows no change for all different

concrete conductivities for the same heating pulse duration.

Table 5.19 Concrete conductivity simulations 303 to 308

Run

#

Pulse interval

(s)

Conductivity

(W/m.oC) ΔTmax (oC)

303 5 1.3 7.604

304 5 1.4 7.607

305 5 1.5 7.609

306 5 1.6 7.612

307 5 1.7 7.614

308 5 1.8 7.617

5.3.4 Parametric Study 7: Thickness of materials

This study highlighted the effects of the change in layer thicknesses of CFRP fabric,

epoxy and concrete. The study was subdivided in three run-sets to study the influence of

changing thicknesses of CFRP, epoxy and concrete. For all sets, the thermal input heat

flux intensity was fixed at 1055 W/m2 at 5 s pulse length.

5.3.4.1 CFRP layer thickness

These studies focused on the range from 0.25 mm to 0.55 mm. Both CFRP sheets

covering the defect were changed together, meaning that if the first layer was 0.3 mm

then the 2nd layer had the same thickness of 0.3 mm. During the seven simulation runs

the thicknesses of the epoxy layers and concrete substrate were fixed at 0.5 mm and 50

mm respectively. Table 5.20 illustrates the effects of changing CFRP thicknesses on the

thermal signals. The maximum thermal signal decreases by the increase in the CFRP

Chapter Five

308

layers thicknesses. The maximum thermal signal detectability deteriorates down to 36 %

when the CFRP thickness is increased to 0.55 mm at of 4.8 oC.

The thicker fabric layers of CFRP show smaller ΔTmax in a nonlinear trend, as shown in

Figure 5.22a. From the result shown in Figures 5.22b and 5.22c, the time for the

maximum thermal signal is increased linearly by increasing of CFRP thickness. The rate

of tmax change increases by the increase of the CFRP layers, as shown by a comparison

of Figures 5.13b and 5.22c. The rate of Δtmax was increased by 0.171 s per 0.1 mm and

0.2 s per 0.1 mm for the CFRP single and double sheets respectively.

Table 5.20 Double CFRP thickness simulations 309 to 315

Run

#

Pulse interval

(s)

CFRP fabric

thickness (mm) ΔTmax (oC) Change (%)

309 5 0.25 7.60 0

310 5 0.3 7.04 -7.4

311 5 0.35 6.46 -15.0

312 5 0.4 5.97 -21.5

313 5 0.45 5.54 -27.0

314 5 0.5 5.18 -31.9

315 5 0.55 4.86 -36.1

(a) (b)

y = 11.586x2 - 18.468x + 11.514R² = 0.9998

2

3

4

5

6

7

8

9

10

0.2 0.3 0.4 0.5 0.6

ΔT m

ax(o C

)

CFRP thickness (mm)

0

1

2

3

4

5

6

7

8

9

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

0.25 mm0.3 mm0.35 mm0.4 mm0.45 mm0.5 mm0.55 mm

Numerical analysis

309

(c)

Figure 5.22 Double CFRP layers simulation (a) Maximum thermal signal versus CFRP thicknesses; (b) Thermal signals versus time; (c) Time of maximum thermal signals

5.3.4.2 Epoxy layer thickness

Analyses of simulations were performed to examine the influence of change in the

epoxy thickness layer on the thermal signal detected under two CFRP layers. The

thickness of epoxy varied from 0.3 mm to 1.5 mm. Pulses of 5 s of 1055.56 W/m2 were

applied to the top of the 2nd CFRP sheet. Table 5.21 illustrates the results of changing

epoxy thickness in the 1st CFRP-concrete bond zone and in the bond surface between

the 1st and the 2nd CFRP fabrics layers. The results show that, by increasing the epoxy

resin layer thickness, the maximum signal is decreased. Similar to the results of the

single CFRP layer system, changing the epoxy thickness has less influence than

changing the CFRP thickness. Simulation 316 shows that the narrower resin layer helps

to present higher ΔTmax in a sharp non-linear trend, as shown in Figure 5.23. By

increasing the epoxy thickness to 1 mm and more, the change in ΔTmax becomes

negligible at less than 1 oC, as shown in runs 319 to 322 in Table 5.21. The signal

reached only 4 oC at the 1.5 mm thickness of epoxy.

y = 2x + 6.35

6.6

6.7

6.8

6.9

7

7.1

7.2

7.3

7.4

7.5

0.1 0.2 0.3 0.4 0.5 0.6t m

ax(s

)

CFRP thickness (mm)

Chapter Five

310

Table 5.21 Epoxy thickness simulations 316 to 322

Run

#

Pulse interval

(s)

Epoxy thickness

(mm) ΔTmax (oC) Change (%)

316 5 0.3 11.19 47.1

317 5 0.5 7.60 0

318 5 0.7 5.80 -23.6

319 5 0.9 4.87 -35.9

320 5 1.1 4.38 -42.3

321 5 1.3 4.23 -44.3

322 5 1.5 4.07 -46.3

Figure 5.23 Maximum thermal signal versus epoxy thickness

5.3.4.3 Concrete layer thickness

Runs from 323 to 326 were designed to analyze the influence of changing the concrete

substrate thickness. The thickness of concrete varied in these runs from 30 mm to 200

mm. ΔTmax showed negligible change when the concrete thickness varied, whilst tmax

showed no change at all. Table 5.22 shows that the percentage change in the maximum

detected thermal signal was approximately 0.1 % when the concrete was reduced to 30

y = 7.8298x2 - 19.366x + 15.862R² = 0.9766

0

2

4

6

8

10

12

0.2 0.5 0.8 1.1 1.4 1.7

ΔT m

ax(o C

)

Epoxy thickness (mm)

Numerical analysis

311

mm. The results of this analysis emphasize the minor effect of concrete thickness on the

thermal signal detected and confirm the reliability of the adiabatic boundary conditions

assumed in all parametric studies presented in this chapter.

Table 5.22 Concrete thickness simulations 323 to 326

Run

#

Pulse interval

(s)

Concrete

thickness (mm) ΔTmax (oC)

323 5 30 7.597

324 5 50 7.609

325 5 100 7.614

326 5 200 7.601

5.3.5 Parametric Study 8: Thermal loads and periods

In this parametric study, simulations with different intensity pulses applied to the top

surface of the 2nd CFRP fabric were analyzed. The same modeling sizes, thermal

properties, thermal boundaries conditions and cooling that applied in the previous

studies were used in this study. The effect of changing the heat flux intensity was

studied in simulation runs 327 to 341, and the results are presented in Table 5.23. Pulses

of 5 s and different heat flux intensities from 444 W/m2 to 2000 W/m2 were applied.

The results shown in Figure 5.24a indicate that the maximum thermal signal increases

linearly with the increasing the heat applied to the specimen. The rate of increase in the

double CFRP system was much smaller than the rate of increase in the single fabric for

the same thermal inputs. A comparison of Figures 5.15 and 5.24a shows this difference.

The time for maximum thermal signal is independent of the injected heat wave as it is

not affected by changing the value of the input heat wave intensity within the same

pulse interval. For all curves of different thermal loads in Figure 5.24ba the tmax

remained at 6.85 s.

Chapter Five

312

Table 5.23 Thermal load simulations 327 to 341

Run #

Pulse

interval

(s)

Input heat flux

(W/m2)

Input heat

flux (W)

ΔTmax

(oC)

327 5 444.44 40 3.2

328 5 555.55 50 4.0

329 5 666.66 60 4.8

330 5 777.77 70 5.6

331 5 888.88 80 6.4

332 5 1000 90 7.2

333 5 1111.11 100 8.0

334 5 1222.22 110 8.8

335 5 1333.33 120 9.6

336 5 1444.44 130 10.4

337 5 1555.55 140 11.2

338 5 1666.66 150 12.0

339 5 1777.77 160 12.8

340 5 1888.88 170 13.6

341 5 2000 180 14.4

Numerical analysis

313

(a) (b)

Figure 5.24 (a) Thermal signal versus input heat flux; (b) Thermal signal versus time of different input heat flux

5.3.6 Summary and findings

The investigations described in Section 5.3 focused on studying the different potential

parameters that may affect the thermal responses of bond defects covered with double

CFRP layers during IRT testing. Detection can be represented in different parameters,

however, the most important thermal response feature that represents the detectability

level is the maximum thermal signal on the investigated surface of the defect area and

the time for that thermal signal. A bonding defect under double CFRP layers was

modeled and investigated. Different parameters were investigated after the results were

verified first by the corresponding thermal responses from the experimental program. It

was noticed that pulses with durations of 1 s and 3 s generate thermal signals with small

values for defects under double CFRP sheets. For that reason, pulses with 5 s only were

applied in these studies.

The 5th parametric study involved the verification of the simulation and experimental

thermal results of unbond defects under a double CFRP CF140 fabric. The results of the

simulated model were very close to the experimental results for all imposed pulse

duration phases. The difference between the experimental and the simulated maximum

thermal signals was less than 0.4 oC.

y = 0.0072x + 3E-14R² = 1

0

2

4

6

8

10

12

14

16

18

20

0 400 800 1200 1600 2000

Ther

mal

Sig

nal ∆

T (o C

)

Input heat flux (W/m2)

-2

0

2

4

6

8

10

12

14

16

0 10 20 30 40 50 60

Ther

mal

Sig

nal ∆

T (o C

)

Time (s)

444 W/m2 555 W/m2666 W/m2 777 W/m2888 W/m2 1000 W/m21111 W/m2 1222 W/m21333 W/m2 1444 W/m21555 W/m2 1666 W/m21777 W/m2 1888 W/m22000 W/m2

Chapter Five

314

The effects of changing material thermal properties in multi-CFRP systems were

investigated in Parametric Study 6. The investigation was subdivided into three parts to

address material property changes in the CFRP, epoxy and concrete components. The

following conclusions are drawn from this study:

The ΔTmax decreases linearly by increasing the specific heat of the double

CFRP.

For the same pulse duration and intensity with different CFRP specific heat,

ΔTmax values in the double CFRP system are smaller than in the single CFRP

system.

The time to the maximum thermal signal rises in a linear trend by the increase

of the specific heat of the double CFRP.

For the same pulse duration and intensity with different CFRP specific heat, tmax

values in the double CFRP system are larger than in the single CFRP system.

Values of ΔTmax show slight reduction (less than 1oC) by increasing the

conductivity of the double CFRP.

There is no change in tmax when the conductivity of the double CFRP changes.

The maximum thermal signal decreases slightly and linearly with the increase

of epoxy specific heat.

For the same pulse duration and intensity with different epoxy specific heat

values, ΔTmax values in the double CFRP system are higher than in the single

CFRP system.

The tmax is independent with respect to changing epoxy specific heat.

ΔTmax is increased by the increase of epoxy conductivity.

There is no change in tmax when the conductivity of the epoxy changes.

Changing the concrete specific heat and conductivity has negligible influence

on ΔTmax and tmax.

Study 7 was designed to examine the thickness effects of each component of concrete

multi-CFRP systems. The results show that:

Thicker CFRP fabrics demonstrate smaller ΔTmax in a nonlinear trend.

Numerical analysis

315

Time for maximum thermal signal increases non-linearly with increasing

thickness of CFRP sheets.

The tmax values in the double CFRP system are larger than in the single CFRP

system for the same pulse duration and intensity with different CFRP

thicknesses.

By increasing the epoxy resin layer thickness, the maximum signal decreases.

Increasing the epoxy thickness to more than 1 mm shows negligible changes.

The ΔTmax values in the double CFRP system are larger than in the single CFRP

system for the same pulse duration and intensity with different epoxy

thicknesses.

Thermal responses show no change with changing substrate concrete thickness.

The final parametric study examined the thermal load with different intensities applied

to the top of the 2nd CFRP sheet surface. One pulse duration length was used in this

study at 5 s duration. The following are the findings of this study:

The value of ΔTmax increases linearly with increasing heat intensity.

The ΔTmax values in the double CFRP system are smaller than in the single

CFRP system for the same pulse duration and different intensities.

The time for maximum thermal signal is independent of changing intensity of

the applied heat wave.

The results have promise for assist thermographers with the selection and design of

thermal heat wave inputs to obtain desired thermal responses, while maintaining and

monitoring the surface temperature to prevent it exceeding the epoxy heat limitation.

Conclusions and recommendations

317

6 CHAPTER SIX: CONCLUSIONS AND

RECOMMENDATIONS

6.1 Introduction

The lack of a standard and reliable method to control and monitor the quality of civil

engineering structures strengthened externally with CFRP systems is a matter of

concern. To date, the traditional method of using a hammer to generate a sound wave

and monitor its eco using the human listening ability is used in the detection of CFRP

bonding faults. With such methods, characterizing the bond defect is a very difficult and

inaccurate mission. The need for a non-destructive method that is able to address bond

defects thoroughly is vital. IRT NDT has potential capabilities that can overcome the

barriers to the investigation of large areas rapidly to detect bond anomalies. IRT NDT

shows promising advantages that make it one of the best NDT methods which can be

employed in the detection of CFRP bonding defects.

Most previous studies on using IRT NDT in CFRP systems in civil engineering

applications have focused only on applying qualitative IRT. The need to study defects in

more detail is an ACI 440 committee recommendation (2008). It is necessary to study

IRT NDT in more detail and understand the different parameters that have an influence

on thermal IR results in order to permit the broad use of this method in the evaluation of

civil engineering structures.

The purposes of this dissertation are: (i) to develop a test configuration and (ii) increase

confidence in using IRT NDT to detect different bond defects in different CFRP

systems attached externally to concrete or steel structures. Both laboratory experimental

and numerical analyses studies were conducted to standardize the NDT method. The

work presented in this thesis is divided into four phases: literature review, experimental

qualitative laboratory works, experimental quantitative program and FE numerical

parametric studies. In the literature review, the fundamentals of IRT NDT and principles

of test methodology were addressed. Different IR techniques were studied thoroughly to

gain a better understanding of the capabilities of different approaches. Factors that can

Chapter Six

318

affect IR readings including emissivity were studied. Many previous studies were

evaluated to address the knowledge gap in the use of IRT NDT in the detection of bond

defects at the CFRP-structures contact zone.

In the second phase of this research, qualitative IRT tests were conducted on 27

concrete and 5 steel specimens. Each specimen had been strengthened with specially-

designed CFRP systems and implanted with artificial faults. The CFRP composites

included fabrics of three types (uni-directional CF130, uni-directional CF140, and bi-

directional 45 degree) and laminate CFRP. These different CFRP products were

attached externally in different designs. Embedded artificial defects ranged from

unbond area, delamination, debond, grooves and cracks in concrete.

The third phase focused on quantitative experimental tests. An extensive experimental

program was conducted in this phase. The studies in this phase were subcategorized into

8 investigation phases to examine the IR observation of different defects, test the ability

to measure defect sizes, use different excitation heat sources, and evaluate and eliminate

errors in readings.

The fourth and final phase concentrated on different parameters that may affect IRT

results. Simulated FEM analyses were performed for defects in different CFRP-concrete

designs. Different 3-D models were built to simulate the different defects. Factors

including: material properties, material thickness and thermal load inputs were studied

in depth after the experimental and simulated results were verified.

The conclusions of this thesis can be divided into two parts: conclusions of

experimental studies and conclusions of parametric numerical studies.

6.2 Conclusions

6.2.1 Experimental studies

The laboratory studies demonstrated that qualitative thermography evaluation has

reliable detection capabilities to discover unbond areas, debond, and delamination

defects under a single CFRP fabric or laminate. This assessment method is unable to

Conclusions and recommendations

319

address bond defects underneath multiple layers of CFRP fabric or laminate, or evaluate

debonding severity. Moreover, the detection of water presence under laminates of

multiple layers of CFRP fabric is not feasible. These limitations are mainly due to the

limitation of the IR detector used to carry out IR testing in qualitative thermography.

The results of these qualitative IR tests show that this technique is very functional for

quick assessment, but not for full defect characterization.

The results of quantitative experimental program indicate that IRT is a potential

practical NDT method that can be employed efficiently to evaluate bond in different

CFRP systems applied to concrete or steel structures. The results show the best

parameter that can be used to represent the thermal response with minimum noise is the

thermal signal. Different bond defects can be detected with 1 s pulses. Other defects,

especially those under thicker multiple-CFRP composite, need longer pulse durations.

Thermal response detectability is proportional to the thickness and the number of layers

of the CFRP systems. Greater thickness means less detectability and thermal signals

decrease with the increase of the CFRP layer numbers, reducing to half with the

doubling of the CFRP layers. A pulse intensity of 500 W/m2 with length of more than 1

s the minimum thermal load that needs to be applied to the investigated surface to detect

the bond defect with a minimum thermal response signal. Detectability does not depend

only on the CFRP composite design and system but also on the substrate material. IRT

is able to determine the severity of unbonding within the debonding zone, which

facilitates the repair priority process. Moreover, the technique shows very good

detectability for small defects from far IR reading. The transmission observation method

is viable only in steel substrate structures.

The technique shows that the sizes of unbond, debond and delamination defects even

under multiple-CFRP fabrics layers, can be measured precisely. However, the precise

size is dependent on different parameters including: IR image capture time, IR detector

position and the thermographer's judgment. Defect shapes and sizes under laminate

CFRP systems are harder to calculate than those under fabric systems.

Chapter Six

320

The study of quantitative thermography including different heating modes and

excitation sources has shown that the use of an air supply system produces irrelevant hot

spots in the multi-CFRP system. The results demonstrate that similar signal behaviours

of bond defects are generated by applying air excitation systems and lamp systems for

both concrete and steel substrate structures.

The IRT quantitative tests conducted show that the technique is able to detect water

presence in different CFRP-concrete systems. However, imposing intensive pulses to

raise the test surface temperature well above its static temperature is recommended to

detect the area with water presence. The study of different heating schemes has shown

that, by using the long pulse duration heating scheme, defect size and shape can be

established easily.

The results of the investigation of the ability of IRT as a NDT to detect and measure

cracks between CFRP fabrics and concrete specimens show that the technique is

capable of detecting the locations and sizes of major cracks adequately. Cracks up to 0.8

mm can be accurately recognized.

The experimental quantitative program provides guidelines that can be used as a tool to

design the thermal heat wave to apply. The guidelines provide the minimum pulse heat

duration for each lamp location (intensity) for many different CFRP systems and for

different bond defects.

6.2.2 Numerical studies

FEM is very useful to investigate and study the effect of different parameters that

influence the thermal response of bond defects in the CFRP-concrete system. The

performances of thermal responses were predicted with high accuracy by the models

employed compared to the experimental results. Maximum thermal signals and the time

to reach them were used to evaluate detectability during the parametric studies. Bond

defects were implanted in two concrete-CFRP models, with single and double CFRP

layers. The parameters of both models investigated were: material thermal properties

Conclusions and recommendations

321

(CFRP, epoxy and concrete), material thicknesses (CFRP, epoxy and concrete), and the

thermal loads applied during pulse heating to generate the thermal responses.

Parametric studies were conducted to investigate the effect of thermal material

properties on the thermal response of bond defects in single and double CFRP-concrete

systems. The specific heat and thermal conductivity of the CFRP, epoxy and concrete

were varied. The studies show that CFRP thermal properties have the greatest influence

on captured thermal responses. The maximum thermal signals and times for these

signals in both single and double CFRP systems increase linearly with the increase in

the CFRP thermal properties. However, the increase rate of signals in the single system

is greater and the tmax values are shorter or show no change for specific heat and

conductivity increases. Epoxy and concrete thermal property variations demonstrate

shallow thermal response sensitivities. The collected thermal responses of IR pulses

have less than 1 oC influence on varying epoxy and concrete specific heat and

conductivity in both single and double CFRP-concrete composites.

Studies 3 and 7 were designed to study the influence of thickness variation for each

component of concrete strengthened with single and multi-CFRP systems. The results

show that, increasing the CFRP fabric thickness produces lower ΔTmax values with

nonlinear tendencies and higher tmax increasing linearly. Values of tmax in the single

CFRP system are smaller than in the multi- CFRP system for the same pulse duration

and intensity. By increasing the pulse length applied to different CFRP thicknesses, the

ΔTmax change rate decreases. Increasing the epoxy thickness reduces the maximum

signal. The ΔTmax values in the double CFRP system are larger than in the single CFRP

system for the same pulse duration and intensity with different epoxy thicknesses.

Thermal responses show negligible change by changing the thickness of the concrete

substrate.

The results of thermal input parametric studies for defects embedded under single and

double CFRP fabrics help to characterize the thermal load input that should be used to

produce a desired thermal signal for defects. A maximum thermal load intensity of the

Chapter Six

322

pulse can be designed according to the minimum desired thermal signal. The time for

the maximum thermal signal is independent of changes in the intensity of the applied

heat wave.

6.3 Recommendations for future work

The experimental and analytical programs presented in this dissertation demonstrate the

capabilities of IRT NDT to detect and characterize bond defects in different CFRP

systems attached externally to both concrete and steel structures. However, future

research is needed to extend the present study. Some suggestions are listed as follows:

Further research is needed to develop a standard test to determine defect depth

with IRT. In particular, more experimental tests are required to optimize the

frequency and amplitude of pulse in the lockin IRT NDT.

Experimental studies are needed to investigate the high wind speed effect on

IRT data. This can help to standardize the procedure and thermal input in the

field as high wind is not a laboratory condition.

Civil engineering structures in situ have different surface shapes. More research

is needed to employ IRT NDT for curved surface areas and anchorage details for

example. Recent IR detector technology has the ability to evaluate accurately

only plain surface. Different surface shapes need IR lenses that have the ability

to resist distortion in thermograms due to the curvature in the investigated

surface. Moreover, IRT NDT needs specially-designed excitation systems to

supply an acceptable uniform heat wave for curved surfaces.

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Appendix A

333

APPENDIX A

Specimen details, Chapter 3, Section 3.2.6

Figure A. 1 Specimen 27 spall details

Figure A. 2 Specimen 4 defect details

Appendix A

334

Figure A. 3 Crack measurement

Figure A. 4 Specimen 25 rough surface preparation with CR253 crack

Appendix A

335

Figure A. 5 Specimen 14

Figure A. 6 Specimen 16 before attaching the CFRP fabric

Appendix A

336

Figure A. 7 Steel specimen attached with CFRP fabric

Figure A. 8 Steel specimen S2

Appendix B

337

APPENDIX B

Cracks CR101 and CR102 profile trends presented in Chapter 4 Part 8

Figure B. 1 At 5 s from 1 m

Figure B. 2 At 3 s from 1 m

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

Appendix B

338

Figure B. 3 At 1 s from 1 m

Figure B. 4 At 5 s from 1.2 m

Figure B. 5 At 3 s from 1.2 m

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

Appendix B

339

Figure B. 6 At 1 s from 1.2 m

Cracks CR101 and CR102 profile trends presented in Chapter 4 Part 8

Figure B. 7 At 5 s from 1 m

Figure B. 8 At 3 s from 1 m

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Single CF130-pixels

CR102CR101

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

Appendix B

340

Figure B. 9 At 1 s from 1 m

Figure B. 10 At 5 s from 1.2 m

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

Appendix B

341

Figure B. 11 At 3 s from 1.2 m

Figure B. 12 At 1 s from 1.2 m

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

CR103CR104

05

1015

2025

20.0

30.0

40.0

50.0

1

51

101

151

201Time (s)

Surface Temperature (oC)

ROI - Double CF130-pixels

List of publications

343

LIST OF PUBLICATIONS

List of publications produced by the candidate as a result of the project are as follow:

1- Tashan, J. and R. Al-Mahaidi (2009), Detection of Bond Defects in CFRP

Sheets Bonded to concrete Using Infrared Thermography, 9th International

Symposium on Fiber Reinforced Polymer Reinforcement for Concrete

Structures FRPRCS-9, Sydney, Australia.

2- Tashan, J. and Al-Mahaidi, R.(2009), Detection of Bond Defects in CFRP

Laminates Bonded to Concrete Using Infrared Thermal Imaging, First Scientific

Conference on Nanotechnology, Advanced Materials and their applications

SCNAMA,Baghdad, Iraq.

3- Tashan, J. and R. Al-Mahaidi (2012), "Investigation of the parameters that

influence the accuracy of bond defect detection in CFRP bonded specimens

using IR thermography", Composite Structures, Vol. 94, No. 2, pp. 519-531.