development of infra-red thermography ndt …
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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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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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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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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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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).
Literature review
19
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.
Literature review
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)
Chapter Two
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.
Literature review
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)
Literature review
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.
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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.
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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
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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
50
50
50
50 100
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180
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
Quantitative IRT experimental laboratory program
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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
70
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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.
Quantitative IRT experimental laboratory program
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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
Chapter Four
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
7070
80
Quantitative IRT experimental laboratory program
185
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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186
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.
Chapter Four
188
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
189
(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
Chapter Four
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
3.0
8.0
13.0
18.0
23.0
28.0
0 10 20 30 40
Ther
mal
sig
nal Δ
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
-1
4
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)
Chapter Four
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
195
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)
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 20 40 60
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB011-10s at 70cm
Reflection error
Chapter Four
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
0.50
1.50
2.50
3.50
4.50
5.50
6.50
7.50
0 20 40 60
Con
trast
Time (s)
C -UB011-Air Blower at 70cm
Quantitative IRT experimental laboratory program
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(a)
(b)
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
0 20 40 60
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-DB031-5 s at 70cmΔT-DB031-10 s at 70cmΔT-DB031-20 s at 70cm
Chapter Four
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
1.00
3.00
5.00
7.00
9.00
11.00
13.00
15.00
0 20 40 60
Con
trast
Time (s)
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
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 20 40 60
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB052-20 s at 70cm
-1.00
-0.50
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
0 20 40 60
Con
trast
Time (s)
C -UB052-20 s at 70cm
Chapter Four
200
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
-0.3
-0.1
0.1
0.3
0.5
0.7
0.9
0 20 40 60
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB081-20 s at 70cm
-1.00
-0.80
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
0 20 40 60
Con
trast
Time (s)
C -UB081-20 s at 70cm
Chapter Four
202
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
203
(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
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0 20 40 60
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB011-10s at 70cm
ΔT-UBS11-10 s at 70cm
-0.5
0
0.5
1
1.5
2
2.5
0 20 40 60
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-DBS21-10 s at 70cm
ΔT-DB031-10 s at 70cm
Chapter Four
204
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
205
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
Chapter Four
206
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
207
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
209
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
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
0 10 20 30 40
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB012-1s at 50cm-shutter openedΔT-UB012-1s at 50cm-shutter closed
Quantitative IRT experimental laboratory program
211
(b) Pulse length of 5 s
Figure 4.78 Thermal signals of defect UB021
(a) UB051 at 1 s pulse length
-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-UB012-5s at 50cm-shutter opened
ΔT-UB012-5s at 50cm-shutter closed
0.0
0.5
1.0
1.5
2.0
2.5
0 20 40 60 80 100 120
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB051-1s at 50cm-shutter openedΔT-UB051-1s at 50cm-shutter closed
Chapter Four
212
(b) UB051 at 5 s pulse length
(c) UB052 at 1 s pulse length
0.0
2.0
4.0
6.0
8.0
10.0
12.0
0 20 40 60 80 100 120
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB051-5s at 50cm-shutter opened
ΔT-UB051-5s at 50cm-shutter closed
0.0
0.5
1.0
1.5
2.0
2.5
0 20 40 60 80 100 120
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB052-1s at 50cm-shutter opened
ΔT-UB052-1s at 50cm-shutter closed
Quantitative IRT experimental laboratory program
213
(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.
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
0 20 40 60 80 100 120
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UB052-5s at 50cm-shutter opened
ΔT-UB052-5s at 50cm-shutter closed
Chapter Four
214
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.
0
1
2
3
4
5
6
7
8
9
10
0 10 20 30 40 50 60
Ther
mal
Sig
nal ∆
T (o C
)
Time (s)
ΔT-DB031-1s at 50cm-shutter openedΔT-DB031-1s at 50cm-shutter closed
Quantitative IRT experimental laboratory program
215
(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,
-2.0
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
0 5 10 15 20 25 30
Ther
mal
sig
nal
ΔT
(oC
)
Time (s)
ΔT-UBS32-5s at 50cm-shutter opened
ΔT-UBS32-5s at 50cm-shutter closed
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 50 60
Ther
mal
sig
nal
ΔT
(oC
)
Time (s)
ΔT-DBS31-5s at 50cm-shutter opened
ΔT-DBS31-5s at 50cm-shutter closed
Chapter Four
216
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
-2.0
0.0
2.0
4.0
6.0
0 10 20 30 40 50 60
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
ΔT-UBS41-5s at 50cm-shutter closedΔT-UBS41-5s at 50cm-shutter opened
Quantitative IRT experimental laboratory program
217
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
Chapter Four
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
219
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
Chapter Four
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
221
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.
-15
-10
-5
0
5
10
15
20
25
30
0 20 40 60 80 100 120
Ther
mal
Sig
nal ∆
T (o C
)
Time (s)
DB031-5s-50cm-with waterDB031-5s-50cm
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
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
0 30 60 90 120 150
Ther
mal
Sig
nal ∆
T (o C
)
Time (s)
GR171 filled with water
GR171
-1.00
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
0 30 60 90 120 150
Con
trast
Time (s)
GR171 filled with waterGR171
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
231
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.
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
0 20 40 60 80 100 120 140
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
6.0
7.0
8.0
0 50 100
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
10.0
12.0
14.0
0 10 20 30 40
Ther
mal
sig
nal Δ
T (o C
)
Time (s)
UB011-0.05Hz
-2.0
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)
UB011-0.025Hz
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
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
15.0
20.0
25.0
30.0
35.0
40.0
0 20 40 60 80
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
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
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
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
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.
Numerical analysis
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.