Evaluation of Durability in Evaluation of Durability in WoodWood--Plastic Composites Plastic Composites Using XUsing X--ray Tomographyray Tomography

Lech Lech MuszyMuszyńńskiskiBrian K. BayBrian K. BayJohn SimonsenJohn SimonsenYu GengYu GengYi WangYi Wang

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Outline

Background and introduction to XMTExperimental setupResultsConclusionsAcknowledgements

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Wood flour in HDPE

0.1 mm

0.3 mm

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WoodWood--Plastic Composites (WPCs)Plastic Composites (WPCs)

Mechanical and physical properties of WPCs may be engineered by changing phase characteristics, proportions and orientation, processing parameters, and internal bonding

Limitations: composite design is limited by the naturally variable wood properties and the limited selection of thermoplastics that may be used with wood (melting temperature <200° C)

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Focus on the Internal BondFocus on the Internal Bond

Challenge: Bonding two dissimilar materials

Hydrophilic wood

Hydrophobic thermoplastics

Facilitated by formulation, processing and coupling agents

Improve mechanical properties

Improve water sorption and durability

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How much can flexural tests reveal about internal bonding?

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WPC micromechanicsWPC micromechanics

Durability and mechanical performance of WPCs are decided on the µ-mechanical level - in the interphase between wood and plastic

Traditional testing methods offer indirect and limited insight to µ-mechanical performance, µ-damage accumulation and governing failure mechanisms –new methods are needed

Any significant progress in this field depends on better understanding of the composite performance and internal bond durability on the µ-mechanical level, and reliable modeling based on that understanding

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OBJECTIVE

To develop experimental procedures for multi-scale evaluation of micro-mechanical performance, governing failure mechanisms and micro-damage accumulation in WPCs

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Experimental questions

Where does the damage take place?

Statistical characterization of the local deformation and internal damage accumulation

How bad is it?

Correlations between the internal damage and the storage modulus

When will it happen?

Accelerated aging

Samples from the field

Predictive models

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Procedure:Multi-scale analysis

Macro level: elastic modulus, static strength, storage modulus, original and aged (meters)

Optical DIC analysis to identify strain concentrations on the specimen surfaces (mm)

Digital Volume Correlation based on low resolution CT scans (20 µm/pxl) to identify internal strain concentration areas of interest

High Resolution CT scans (3 µm/pxl) on those areas identified in the previous steps to reveal and characterize internal damage concentrations

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Damage characterization

Damage is defined as a degradation in microstructure due to an external or internal influence.

mechanical stress

moisture/temperature cycling

chemical changes

Define damage variable, D, such that E = E0(1 - D)

Nondestructive X-Ray Microtomography

Nondestructive measurement allows evaluation of the three-dimensional internal structure before and after the degrading treatments

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X-ray Microtomography: Measurement principles

• 3D maps of x-ray absorption reconstructed from projection images

• High resolution through high performance x-ray source and detector

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Nondestructive 3-D X-ray microtomography

Is it good for more than just cool pictures?oak

2 mm

oak

2 mm2 mm

LVL (transverse plane),aspen

2 mm

LVL (transverse plane),aspen

2 mm2 mm

plywood, birch

2 mm

plywood, birch

2 mm2 mm 5 mm

OSB

5 mm

OSB

1 mm

Oak Oak vessels

side

topfront

top

right side

back

1 mm1 mm1 mm

Oak Oak vessels

side

topfront

top

right side

back

1 mm1 mm

oak LVL plywood OSB

?1 mm

WPC: Wood/PP

1 mm1 mm

WPC: Wood/PP FRP: E-glass/urethane

2 mm

FRP: E-glass/urethane

2 mm2 mm

FRP: E-glass/epoxy

2 mm

FRP: E-glass/epoxy

2 mm2 mm

Who’s next?Wood/PP GF/Urethane GF/Epoxy

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Nondestructive 3-D X-ray microtomography

Is it good for more than just cool pictures?

Digital tools are available to identify visible features and different material phases (solid phases, voids etc.), quantify connected pore structure, and visualize complex microstructure

Internal strains can be evaluated (Digital Volume Correlation)

Digital Image Correlation Digital Volume Correlation

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Types of Image Correlation

In-plane deformations from single-camera surface images (2D)Out-of-plane deformations from multiple-camera surface images (3D, Poisson’s ratio)Volumetric deformations from tomographic data sets (Digital Volume Correlation)

A 3D extension of DICApplicable to materials with inherent texturePorous materials, composites, large-scale microarchitecture

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Integrated Testing and ImagingDetector Sample Stage X-ray Source

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Hardware Details

The x-ray source:FeinFocus 160 kVp10 micron focal spot

The detector:Thompson TH9438HX image intensifier Retiga 1024x1280 10-bit CCD, lens coupled

The sample stage:Newport RV120 high load rotational stages, opposedInstron 4444 load frame, 2000N capacity

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Software DetailsImage collection:

Field of view between .5 and 10 cm 1000 projections (360 degrees) @ 4 sec/ea

Reconstruction:Feldkamp-style filtered back-projection~ 1billion voxels, res. range 5 - 100 µm

Data volumes:Projection images ~ 2GB, reconstruction volumes ~1 GBCollection ~ 3 h (PC/GPIB based)Reconstruction (2 vols) ~14 hrs (2 Sun processors)

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Volumetric Strain Measurement – How it works

Strain is quantified using correlation methods that compare loaded and unloaded data volumes.

3. Texture Correlation in 2D

1. Marker Tracking in 2D 2. Speckle Metrology in 2D

4. Texture Correlation in 3D

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Strain Measurement - Details

Displacement Vectors Measured at Many Points

Throughout a Sample

Strain Tensors Calculated at Each Point From Groups of Displacement Vectors

INITIAL EXPERIMENTS

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Component Materials

Wood flour

40 mesh pine from American Wood Fibers

Oven dried prior to use for 24 hours at 103°

Plastic

High Density Polyethylene: BP Solvay B53 35H FLK, melt flow = 0.49 g/10 min

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Blending

Brabender Intelli-Torque Plasticorder

Melt HDPE at 170° CAdd gold n-spheresAdd wood flourMix 10 minRemove and store for compression molding

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Pressure molding

Carver Press

Mold: 101.6 x 101.6 x 2 mmTemperature: 185o CPreheat time: 10 minPress time: 10 minPress pressure: 344.8 kPaCooling pressure: 344.8 kPa

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PARTICLE CHARACTERIZATION

Perticle Area Distribution

0

50

100

150

200

0.02

0.04

0.06

0.08 0.1 0.12

0.14

0.16

more

Area [mm]

Cou

nt

Particle Aspect Ratio Distribution

0

25

50

75

100

1.5 2 2.5 3 3.5 4 4.5 5more

Aspect Ratio

Cou

nt

Particle Area Distribution

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Specimens

10 specimens for each wood-PE composite boardSpecimen size

L: 54.5 ±2.0 mmW: 12.5 ±2.0 mm(w: 9.2 ±0.1 mm)t: 2.6 ±0.5 mm

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Density profiles

Wood cell 1.5 g/cc

HDPE 0.95 g/cc

PVC 1.3 to 1.58 g/cc

PP 0.9 g/cc

Wood particles and the polymer matrix materials have similar densities and x-ray absorption levels (CHO).

CONTRAST PROBLEM

1 mm

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GOLD NANOSPHERES

HAuCl4 in water Two phase system: water/toluene

(C8H17)4N+ Br- Gold moves to toluene phaseRemove aqueous phase

Metallic gold precipitatesas spheres, 2 – 5 nm diameterNaBH4

Centrifuge to remove gold nano-spheresAdd to HDPE in Brabender Plasticorder mixer

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Enhanced CT contrast:with a price tag…

MOE [GPa]

0

1

2

3

control 0.1% gold 1% gold

MOR [MPa]

0

10

20

30

40

control 0.1% gold 1% gold

density [g/ccm]

0.0

0.3

0.6

0.9

1.2

control 0.1% gold 1% gold

Property change comparison

0%

20%

40%

60%

80%

100%

control 0.1% gold 1% gold

MOEMOR

density

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Enhanced CT contrast

Ref1%Au

0.1%Au

Ref1%Au

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Enhanced CT contrast

Ref1%Au

0.1%Au

Reconstruction of a longitudinal

section20 µm/voxel

1%Au

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Static tensile tests

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Static tensile tests

0

4

8

12

16

0 0.01 0.02 0.03 0.04 0.05 0.06

Strain, -

Stre

ss, M

Pa

#1#2#3

E* UTS

# MPa MPa

1 1755 14.80

2 1934 14.68

3 1527 12.71

*linear fit to a section of non-linear data

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Static tensile tests: nonlinearity

Etan* E 1%*

# MPa MPa

1 3131 487

2 3846 481

3 2776 387

0

500

1000

1500

2000

2500

3000

3500

0 0.005 0.01 0.015 0.02

Strain, -

E, M

Pa

#1#2#3

*from exponential fit to E(eyy) data

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Static tensile tests: nonlinearity

0

4

8

12

16

0 0.01 0.02 0.03 0.04 0.05 0.06

Strain, -

Str

ess,

MPa

#1#2#3

Etan* E sec1% E sec2%

MPa MPa

721

731

629

1221

1242

1082

E1%*

# MPa MPa

1 3131 487

2 3846 481

3 2776 3870

500

1000

1500

2000

2500

3000

3500

0 0.005 0.01 0.015 0.02

Strain, -

E, M

Pa

#1#2#3

*from exponential fit to E(eyy) data

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Static tensile tests: Poisson effect

ν0%* ν2%*

# - -

1 -0.3516 -0.2959

2 -0.3597 -0.3033

3 -0.3412 -0.2805

*linear fit to a section of experimental data (0.5% - 2.5% strain)

Poisson effect

-0.4

-0.3

-0.2

-0.1

0

0% 2% 4% 6% 8%

ε yy, %

εxx/εy

y, -

#1#2#3

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Degrading procedure

Degradation Procedure, Spec#09

0

100

200

300

400

0 120 240 360 480 600 720 840 960

time, s

load

, N

0.010.00 window 15x15

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Degrading procedure

0.010.00 window 15x15

WPC #1 & #6

0

4

8

12

16

-0.01 0 0.01 0.02 0.03 0.04 0.05

avg strains, -

Stre

ss, M

Pa

#1#06

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D e g r a d a t i o n P r o c e d u r e , S p e c # 0 9

0

1 0 0

2 0 0

3 0 0

4 0 0

0 1 2 0 2 4 0 3 6 0 4 8 0 6 0 0 7 2 0 8 4 0 9 6 0

t i m e , s

load

, N

150 N 175 N 200 N 225 N

0.0050.00 window 15x15

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D e g r a d a t i o n P r o c e d u r e , S p e c # 0 9

0

1 0 0

2 0 0

3 0 0

4 0 0

0 1 2 0 2 4 0 3 6 0 4 8 0 6 0 0 7 2 0 8 4 0 9 6 0

t i m e , s

load

, N

250 N 275 N 300 N 325 N

0.0100.00 window 15x15

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D e g r a d a t i o n P r o c e d u r e , S p e c # 0 9

0

1 0 0

2 0 0

3 0 0

4 0 0

0 1 2 0 2 4 0 3 6 0 4 8 0 6 0 0 7 2 0 8 4 0 9 6 0

t i m e , s

load

, N

350 N 375 N ultimate

max = 0.015 max = 0.020 max = 0.035

Consistent weak areas…

strain

max0.00 window 15x15

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Degrading procedure

0.0350.00 window 15x15

Degradation Procedure, Spec#06

0

4

8

12

16

0 0.005 0.01 0.015 0.02 0.025 0.03

strains, -

stre

ss, M

Pa

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Digital Volume Correlation of WPCs

Just getting started

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XRT 3D volumetric reconstruction of gold-modified 40% wood/HDPE composite

2 mm

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Gold and holes

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Gold and holes

Work in progress…

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AcknowledgementAcknowledgement

This research is funded by the OSU General Research Fund Award, Fall 2004.