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Digital Image Correlation Application to
Structural Health Monitoring
Erin Santini-Bell, Ph.D., P.E. , University of New Hampshire
Philip A. Brogan, New Hampshire Department of Transportation
Paul J. Lefebvre, Mitchie Corporation
Jason Peddle, University of New Hampshire
Brian Brenner, P.E., Fay, Spofford and Thorndike, INC.
Masoud Sanayei, Ph.D., Tufts University
Presentation Outline
• Background
• Digital Image Correlation
• Verification Tests
• Field Applications
– Vernon Ave Bridge in Barre, Massachusetts
– Belknap Mountain Rd in Gilford, New Hampshire
• Conclusions
2
Motivation
• 1 in 3 Bridges Near End of Design Life (FHWA, 2009)
• Entering Rebuilding Phase
• Increased Public Awareness
• Advances in Digital Imaging Technology
• Opportune Time to Consider Changes to Management Paradigm
Tobin Memorial Bridge
3
Bridge Management
• Bridge management includes
– Visual Inspections
– Load Rating
– Rehabilitation
– Overload permitting
– Maximum-load postings
– Salting
4
Bridge Inspections
• Bridges are inspected every 2 years – Initial inspection – Routine inspection – Special inspection
• Condition Ratings (AASHTO Manual for Bridge Evaluation, 2008)
5
Traditional Bridge Monitoring
• Traditional Instruments
– Linear Varying Differential Transducer (LVDT)
– Strain Gauge
– Accelerometer
– Visual Observations
– Non-Destruction Evaluation Techniques
6
What is Digital Image Correlation?
• Employs Digital Photography
• Measures deformation of surfaces
• Ability to measure stress, strain, and displacement of a field of view
• Results are visual and objective
An Optical Non Contact Method
7
Digital Image Correlation (DIC)
8
How Does it Work - Equipment
DIC Cameras
Displacement Target
9
Digital Image Correlation (DIC)
• Uses multiple cameras to create a 3D image • Calibration process defines camera orientation • Target is covered with a high-contrast speckle pattern • Post-processing software calculates the pixel
movement throughout images • Calculated data includes:
– Displacement – Velocity – Acceleration – Strain – Rotation
10
How Does it Work – Post Processing
Correlated Solutions, Inc.
11
Laboratory Verification
12
• Purpose of experiment was to address accuracy concerns with 3D DIC
• Is 3D analysis as accurate as 2D at this scale?
• Need to be able to trust the data
LVDT
Calibration Card
LOAD
Laboratory Verification
13
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0 20 40 60 80 100 120 140 160
Dis
pla
cem
en
t (m
m)
Time (s)
Beam Displacement by Method of Measurement/Calibration Target
4mm
6mm
7mm
9mm
LVDT
Calibration Std Dev Analysis Projection Error
4mm Target .014 .017
6mm Target .017 .019
7mm Target .021 .015
9mm Target .020 .018
DIC Applications
• Deflection measurements were collected using DIC on…
– A 3 span steel girder bridge for model verification
– A single span concrete bridge with FRP strips for retrofit assessment
14
Vernon Avenue over the Ware River Bridge Barre, MA
15
Image Courtesy of Google Maps
WM Barre Landfill
Vernon Avenue Bridge (VAB) • 6 Steel Girders with Reinforce Concrete Deck
• Beams and Deck are
Composite
• 3 Continuous Spans • Field splice in center
span
• 150 Feet Long with 75 ft Center Span
Vernon Ave Bridge, Looking South
16
Instrumentation Plan
17
0 10 11 12
9 8 7 6 5 4 3 2 1
NORTH SECTION GIRDER 2
TEMPERATURE GAUGE
ACCELEROMETER
TILTMETER
STRAIN GAUGE
LEGEND
PRESSURE CELLS
Strain Gauges
Steel Temperature
Concrete Temperature
Girder Section at Station 10
Instrumentation Summary
18
Quantity Instrument Type
100 Strain Gauges
36 Girder Temperature Sensors
30 Concrete Temperature Sensors
16 Accelerometers
16 Tiltmeters
3 Ambient Temperature Sensors
Non-Destructive Load Tests
19
2 Types of Tests • Stop Locations Tests • Crawl Speed Tests 3 Trials of each • One 72 Kips Truck
3 Lanes • West Shoulder • Center • East Shoulder
Load Test Lane and Stop Location Plan
NORTH ABUT
SOUTH ABUT
SOUTH PIER
NORTHPIER
0 4 6 8 10 12 14 2
LANE 1
LANE 2
LANE 3
20
Verification
Vernon Avenue Bridge – Barre, Massachusetts
• Deflection Measurements were collected using DIC and LVDTs simultaneously
21
Verification Results
22
Verification Results
23
Stop on Span 1
Stop on Span 2
Stop on Span 3
Enhanced Designer Model (EDM) Modeling Requirements
24
Girders: Frame Elements Deck: Shell Elements Boundary Conditions: Roller-Roller-Roller-Pin
SAP2000® Bridge Information Modeler (BrIM)
ERM Calibrated Model Stop Location Load Test Strains
25
Bottom Flange of Girder #2 at North Pier (Station 8)
Implementation
26
DIC Data for Independent Evaluation
27
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0 100 200 300
De
fle
ctio
n (
in)
Time (s)
Vertical Deflection of Vernon Ave Bridge near MidspanTruck in West Lane
DIC
Original
Updated
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0.04
0 50 100 150 200 250 300 350
De
fle
ctio
n (
in)
Time (s)
Vertical Deflection of Vernon Ave Bridge at South SpanTruck in West Lane
DIC
Original
Updated
DIC as part of the Load Rating Process
• Similar ratings for Exterior Girders
• Interior Girders gain extra capacity in EDM Rating
• System Behavior • Stiffer Exterior Girder picks
up more load
• Lowers rating of Exterior Girders
• Increases rating of Interior Girders
28
LRFR vs. Baseline EDM Rating by Girder #
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
1 2 3 4 5 6
Loa
d R
ati
ng
Girder Number
EDM Rating
LRFR Rating
Glenn Bridge
29
• Located in Gilford, New Hampshire on Belknap Mountain Road
• 16’ Span – concrete slab on steel beams
• Retrofitted in Fall of 2010 – DIC & LVDT used to verify increase in strength
Glenn Bridge
30
• Steel beams were removed • Non-composite
• FRP strips installed on the underside • Dubois & King
• Sheet metal was glued to the bridge for a speckle pattern
Glenn Bridge
31
• DIC data follows the trend of LVDTs – not as clean
• This test revealed the lower deflection limits of DIC usage on bridges
• A heavier truck would have been beneficial during testing
Glenn Bridge
32
• DIC data follows the trend of LVDTs – not as clean
• This test revealed the lower deflection limits of DIC usage on bridges
• A heavier truck would have been beneficial during testing
-0.06
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
0 20 40 60 80 100 120
Def
lect
ion
(m
m)
Time (s)
Glenn Bridge Midway Measurements
Midway LVDT
Midway DIC
Conclusions
• Detailed 3D FEM of typical highway bridges is feasible to a high degree of accuracy
• Truck load testing performed on a newly constructed bridge can provide highly reliable strain data for calibrating baseline FEM’s.
• DIC data verified the FEM independently
• Calibrated FEM and load test strain data matched closely
• DIC can also be used to validate the use of innovative material.
33
Future Work
• Additional Verification Experiments
• Conduct a third load test at the Vernon Ave Bridge using DIC and applying the lessons learned through the verification experiments
• Load Rating Comparison: AASHTO: LRFR and DIC
34
Thank You for Listening
35
Acknowledgements
NSF CAREER Grant No 0644683, NSF-PFI Grant No. 0650258 MassDOT – Bridge Construction Town of Barre, MA – Owner Fay, Spofford & Thorndike, Inc. – Bridge Design Geocomp Corporation – Instrumentation Bridge Diagnostics, Inc. – Bridge Testing
Erin.Bell@unh.edu for further information, questions or comments
Backup Slides
36
Instrumentation
Strain Gauges
37
Instrumentation
Tiltmeter
Accelerometer
38
Instrumentation Concrete Temp
Pressure Cells
39
Model Updating
1. AS-BUILT MATERIAL PROPERTIES
3. BOUNDARY CONDITIONS
2. CONCRETE SAFETY CURB
4. DECK REINFORCEMENT
40
Material
PropertyOriginal Updated Units
Density, wc 2403 2236 kg/m3
Unconfined
Compressive
Strength, fc'
28 35 MPa
Modulus of
Elasticity, E 24856 26790 MPa
Degree of
FreedomOriginal Updated Units
Axial, Uz Fixed 560.5 kN/mm
Shear, Uy Free 0.992 kN/mm
Shear, Ux Free 0.992 kN/mm
Rotation, Rx Free 1.77E+06 kN-mm/rad
Rotation, Ry Free 1.77E+06 kN-mm/rad
Torsion, Rz Free 1.77E+05 kN-mm/rad
– Elemental Design
Effective width of slab, be
– Composite Behavior
– Distribution Factor, mg, and Impact Factor, IM
Current AASHTO Bridge Design Process
• Typical Design Assumptions
41
(Adapted from AASHTO LRFD,2008) 𝑃𝑢 ,𝑡𝑟𝑢𝑐𝑘 = η𝛾 𝑚𝑔 (1 + 𝐼𝑀)𝑃𝑡𝑟𝑢𝑐𝑘
Modeling for Bridge Management: AASHTO Load and Resistance Factor Rating (LRFR)
42
(Adapted from AASHTO Manual for Bridge Evaluation, 2008)
𝑅𝐹𝑀𝑜𝑑𝑒𝑙 =𝐶 − 𝐷𝐿𝑀𝑜𝑑𝑒𝑙
𝐿𝐿 𝑀𝑜𝑑𝑒𝑙(1 + 𝐼𝑀)
𝑅𝐹𝐿𝑅𝐹𝑅 =𝐶 − 𝛾𝐷𝐶𝐷𝐶
𝛾𝐿𝐿𝐿𝐿(1 + 𝐼𝑀)
Modeling for Bridge Management: AASHTO Load and Resistance Factor Rating (LRFR)
• γDC=1.25; γLL = dependent on rating type
• 2 Ratings:
o Inventory Rating:
– Based on LL that can safely utilize bridge indefinitely.
– RFINV => γLL=1.75
o Operational Rating :
– Based on maximum permissible LL.
– RFOP => γLL=1.25
• Elemental Approach—LL and DL Distribution Factors
43
(Adapted from AASHTO Manual for Bridge Evaluation, 2008)
𝑅𝐹𝐿𝑅𝐹𝑅 =𝐶 − 𝛾𝐷𝐶𝐷𝐶
𝛾𝐿𝐿𝐿𝐿(1 + 𝐼𝑀)
Modeling for Bridge Management: EDM Rating
• γDC=1.25 and
γLL=1.75 factored into applied loads
• DL from self weight of bridge
• LL applied to mimic 2008 LRFD Bridge Design Specs for Worst-Case Traffic Loading Scenario
• Accounts for System Behavior—No Distribution Factors
44
𝑅𝐹𝑀𝑜𝑑𝑒𝑙 =𝐶 − 𝐷𝐿𝑀𝑜𝑑𝑒𝑙
𝐿𝐿 𝑀𝑜𝑑𝑒𝑙(1 + 𝐼𝑀)
Field Displacement Data
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