DEVELOPMENT OF INFRA-RED 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

To all people who made life at this stage of civilization, in the hope that this work will contribute

III

Summary

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

V

Summary

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. VI

Acknowledgments

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.

VII

Declaration

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

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Table of contents

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 XI

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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 XIII

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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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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

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List of figures

LIST OF FIGURES

Figure 2.1 Infra-red 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 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 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 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 XVII

List of figures

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 , 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 XVIII

List of figures

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 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 XIX

List of figures

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 XX

List of figures

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 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

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List of figures

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 XXII

List of figures

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 mode, (b) using the flood light mode ...... 190

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List of figures

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 XXIV

List of figures

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

XXV

List of figures

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

XXVI

List of figures

Figure 5.24 (a) Thermal signal versus input heat flux; (b) Thermal signal versus time of different input heat flux ...... 313

XXVII

List of tables

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

XXIX

List of tables

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

XXX

List of notations

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 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.

XXXI

List of notations

σ = Stefan-Boltzmann constant

XXXII

Introduction

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

1

Chapter One

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 2

Introduction

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

3

Chapter One

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- 4

Introduction

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.

5

Literature review

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.

7

Chapter Two

The experiments of 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 , 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.

8

Literature review

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 and visible light on the , as shown in Figure 2.1. The 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 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. 9

Chapter Two

 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 μ m 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. 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.

10

Literature review

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. , 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

11

Chapter Two

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, 3 Eλb = spectral emissive power for a blackbody (W/m ), 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, 2 -16 2 C1 = the first radiation constant (2πhco ) = 3.7419 × 10 (W/m ),

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

12

Literature review

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:

13

Chapter Two

( )

[ ( )] [ ] 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.

14

Literature review

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: 15

Chapter Two

( ) ( ) Equation 2 .7 ( ) where, ε (T,λ) = spectral emissivity, 3 Eλ = spectral emissive power for grey body (W/m ).

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

16

Literature review

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

17

Chapter Two

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 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). 18

Literature review

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

19

Chapter Two

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.

20

Literature review

Figure 2 .9 IR diagnosis of water leaks in ceiling (Chicago Infrared Thermal Imaging Inc. 2011)

Passive IRT has also been used to investigate furnaces and heating structures to diagnose the causes of heat losses (Ljungberg 1997). General thermal building performance can also be investigated by this technique. Heat losses can be formalized and estimated by adopting passive IRT techniques (Vavilov, Anoshkin, Kourtenkov, Trofimov and Kauppinen 1997). Gas emission tracking and detection are usually carried out in a passive testing scenario (Ljungberg and Jonsson 2002b). Figure 2.10 shows the tracking of emissions by thermal images in field. Although there are some gases that cannot be distinguished by IRT imaging, the passive approach can be supported with heated or cooled backgrounds to solve the problem of gas invisibility in the thermal images. This application provides a valuable solution for the monitoring of gas leaks in gas pipe- lines.

Figure 2 .10 Gas leak thermography test from a pipe buried at 80 cm depth (Ljungberg and Jonsson 2002b)

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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.

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(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”.

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Figure 2 .13 The Virgin of the Rocks under-drawing infrared image

In meteorology, weather satellites equipped with infra-red technology scanning in the range of 10.3 to 12.5 µm facilitate the calculation of water and land temperature, and cloud monitoring. The Australian region infrared satellite image issued by the Australian Bureau of Meteorology at 11:37 am EST Sunday on 28 August 2011 is shown in Figure 2.14. Infra-red satellite images are used in weather warnings and predictions. For example, people can receive advance warnings about possibly severe hurricanes. Figure 2.15 shows the IR satellite image of hurricane Irene at 12 pm on Sunday, 28 of August 2011 before hitting New York City. Such information helped the New York City government to give the order for the evacuation off residents well before the hurricane’s arrival.

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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.

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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 m apping (Khauv 2011)

Figure 2 .18 Load traffic IR monitoring ( Khauv 2011)

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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.

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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).

External Applied Heat

Subsurface defect

Hot spot

Subsurface defect 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 28

Literature review

evaluations carried out with thermal 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, 29

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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.

Infrared Detector Infrared Detector

Spot Line Heating ` Heating ` ` Heating Source Source Source Processing Processing Processing

Specimen under investigation Specimen under investigation Specimen under investigation

Direction of scanning (a) (b) (c) Field of view and observation area 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

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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 P ulsed heat and IR recorded waves in pulsed thermography approach 31

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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 32

Literature review

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)

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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.

Processing

Controlling

Ultrasonic transducer Amplifier

Infrared Camera

Figure 2 .27TT L set-up with ultrasonically modulated internal simulation

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Thermal wave Optical mean to generate Subsurface thermal waves defect for Lockin thermography

Ultrasonic source to Material surface generate thermal Subsurface waves for Lockin defect thermography

Ultrasonic wave 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 35

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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.

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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). 37

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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.

Infrared Detector

Reflected radiation Radiation emitted from material surface

Material surface

Figure 2 .29 Background reflection [Reproduced from Childs (2001)]

Additional source of background radiation

In this position the thermal detector measures both the emitted and the reflected radiation on the target In this position the thermal detector is shielded from the additional source of radiation by the target

Target Figure 2 .30 Shielding the test to minimize the significant background reflection [Reproduce from Childs (2001)]

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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 39

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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 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.

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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

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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.

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Figure 2 .33 Representation of C FRP 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.

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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)

Elastic Ultimate tensile Tensile strength Type modulus (GPa) strain (%) (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

44

Literature review

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

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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.

Wet layup warrping Procured column jacketing Prepregs wall strengthening 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

46

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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 47

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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 Carino Starnes, ; 2002 Klinkhachorn and and Klinkhachorn

Brown, Jeff R. Brown, Jeff and ; Shives2003 Marinetti 2007Marinetti zi, Grinzato, zi, PellegrinoGrinzato, and 2003 Kausel and2009 Modena Halabe, Vasudevan,Halabe, ( Hamilton, H. Hamilton,R. 2004 H. Levar and Hamilton 2003Levar and Hamilton Hu, Shih, Delpak and Tann Tann Hu, Delpak Shih, and ( Grinzato, Trentin, Bison and Grinzato, Bison and Trentin, ( R. 2004 Starnes 2002 Valluz ( Brown, J. R. and Hamilton, H. Brown, H. R.Hamilton, and J. GangaRao, ( ( ( CFRP fabric CFRP laminate GFRP composite

E-Class Materials Parameters Numbers of layers Cracked section

Different NDT Under-loading Excitation system L Q HL,K HL H,IRL A HL Passive approach Test configuration PTT approach 48

Literature review

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

49

Chapter Two

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 50

Literature review

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 51

Chapter Two

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. 52

Literature review

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 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 53

Chapter Two

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) 54

Literature review

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 mm5 to 1 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. 55

Chapter Two

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 o defect implanted needed around 180 s of heating time to emit a Tdefect of 3 C, while the o foam insulation defect needed only 10 s to develop a Tdefect of more than 5 C. 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. 56

Literature review

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.

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Chapter Two

Figure 2 .37 Test set-ups for long-pulse and m odulated (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

58

Literature review

to gain better understanding. Two preliminary reduced-scale concrete plates 400 mm× 400 mm× 50m m 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. 59

Chapter Two

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.

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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

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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.

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Qualitative IRT experimental laboratory program

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

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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 Mould ing the concrete

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Qualitative IRT experimental laboratory program

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

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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.

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Qualitative IRT experimental laboratory program

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)

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Table 3 .2 CFRP fabric properties (BASF 2011a), ( Varat 2011), (Fyfe-Co. LLC 2011)

Properties

) 2

)

)

C 3

Materials o (%) (mm) (GPa) Tensile Tensile Tensile (g/cm Density Density Thermal Thermal Ultimate Ultimate Modulus (W/m. Thickness Thickness Elongation Conductivity Weight (g/m Weight Strength (GPa) Strength MBrace CF 130 4.9 230 1.55 1.76 300 9.38 0.176 CF 140 400 0.235 TYFO BCC (± 3.79 230 2.1 1.8 607 9.38 0.55 45o)

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.

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Qualitative IRT experimental laboratory program

Table 3 .3 E poxy manufacturers; material properties (BASF 2012a), (Huntsman Advanced Materials 2011)

Properties

Full Cure at

(days)

material Materials

Color C C

o o (Mix ratio) Resin Resin Type 25 40 Specific Gravity Substrate Number of component Flexural Strength (MPa) Modulus Elasticityof (GPa) Compressive Strength (MPa) 2 (3A:1B MBrace Opaque Epoxy 1.12 Concrete 3.0 80 by 120 7 - Saturant Grey volume) 2 (3A:1B MBrace Concrete Epoxy 1.08 0.7 - by Transparent 24 0.208 0.125 Primer + Steel volume) 2 (2A:1B Araldite Epoxy 1.2 Steel 4 - by Dark green 61 7 0.167 2014 volume)

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

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achieve the required strengthening design. In this case a topcoat of MBrace saturant was applied.

Resin apply to the specimen before the installation of CFRP fabric Resin in two parts mixing by roller

Fabric lay up Part 1 Part 2 Threaded roller Specimen squeeze out air-void from interface

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.

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Figure 3 .8 MBrace laminate (BASF 2011b)

Table 3 .4 CFRP laminate properties (BASF 2011b) Properties

)

3

(%) Materials (W/m.K) Width (mm) Density (g/cm Thickness (mm) Ultimate Deformation Thermal Conductivity Tensile Strength (GPa) Tensile Modulus (GPa)

X 7

MBrace 2.5 165 1.3 120 1.6 Y 0.8 1.3 Laminate

Z 0.8

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Table 3 .5 Concrete - CFRP laminate adhesive properties

Properties

Full Cure at

(days) C)

o

lor Materials

Co (MPa)

C C

o o (Mix ratio) Resin Resin Type

25 40 Specific Gravity TransitionGlass Temperature( Compressive Strength Number of component Flexural Strength (MPa) Modulus Elasticityof (GPa) MBrace 2 (3A:2B Laminate Epoxy 1.5 > 65 10 60 Red 30 7 3 by weight) Adhesive

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.

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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.

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Debond defect Delamination defect Unbond defect

CFRP layers Adhesive Crack defect Concrete Spall defects substrate structure

Reinforcement bars 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

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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. sA imilar unbond strip was fabricated in Specimen 7, however, the second CFRP fabric in that specimen was of the TYFO b i-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.

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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. 76

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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

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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 2 3

UB011

50 DB031 UB021 50 50 50 UB012 UB013

50 50 100 100 70

50 7 120 8 UB081 9 80

210 220 180 70

DL072 UB071 100 100 UB091 UB092

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S1 S2 S3 50 50

50 UBS32 UBS15 UBS12 50

DBS21 DLS31 UBS11

UBS14 UBS13

S4 40 80 S5

UBS53 UBS51

70 UBS41

140 UBS54 UBS52

Labels:

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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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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.

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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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Table 3 .6 Identification of artificial defects

Unbonding Debonding Grooves in Cracks in Spalls in Delaminations defects defects concrete concrete concrete Specimen 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

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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) 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

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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 testg in 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.

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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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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. 88

Qualitative IRT experimental laboratory program

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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Figure 3 .21 Thermogram of Specimen 6

Figure 3 .22 Thermogram of Specimen 7

Figure 3 .23 Thermogram of Specimen 8

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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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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

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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

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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

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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

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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 96

Qualitative IRT experimental laboratory program

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.

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. 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.

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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. 99

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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 100

Quantitative IRT experimental laboratory program

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)

2 2 2 2

(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

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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.

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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 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. 103

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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

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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 mm2 Ø 15 Ø 30 area

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 mm 15 25 radius

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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 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.

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Rigid Frame

Styrofoam Styrofoam Sliding Shutter 1.85m Sliding Shutter (50 mm) (50 mm)

Front View 3 m 0.8 m

Top View Rigid Styrofoam Sliding Shutters Frame (a) The insulated sliding shutters [not to scale]

Rigid Frame 305 * 305 mm specimen 300 * 300 mm Angle controller 0-90 o

Rigid Holder 1.3 m

(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

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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.

Processing

Specimen Infra-Red Detector

Excitation Rigid System Sliding Shutter Frame (a)

Processing

Specimen Infra-Red Detector

Rigid Excitation System Sliding Shutter Frame (b)

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(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 109

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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.

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1000

900 1s Pulse at 120cm

800 1s Pulse at 100cm

) 1s Pulse at 70cm 2 700 600 1s Pulse at 50cm 500 400

Heat Flux (W/m Flux Heat 300 200 100 0 0 1 2 3 4 5 6 7 Time (s)

(a) Pulse length of 1 s

1600

1400 3s Pulse at 120cm

1200 3s Pulse at 100cm ) 2 3s Pulse at 70cm 1000 3s Pulse at 50cm 800

600 Heat Flux (W/m Flux Heat 400

200

0 0 1 2 3 4 5 6 7 Time (s)

(b) Pulse length of 3 s

2000 3s Pulse at 120cm 3s Pulse at 100cm 1800 5s Pulse at 70cm 5s Pulse at 50cm 1600 )

2 1400 1200 1000 800

Heat Flux (W/m Flux Heat 600 400 200 0 0 1 2 3 4 5 6 7 Time (s)

(c) Pulse length of 5 s Figure 4 .7 Pulses in PTT versu s time at different distances and durations (Specimen 24)

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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.

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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.

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14.0

12.0

C) 10.0 o T ( T

Δ 8.0

6.0

4.0

2.0 Thermal signal signal Thermal UB011-0.05Hz 0.0

-2.0 0 10 20 30 40 Time (s)

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. 114

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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.

1400

1200

) 1000 2

800

600

Heat Flux (W/m Flux Heat 400

200

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Time (s)

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, 115

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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, o Tambient = the ambient temperature, most of the tests were conducted at 20. C

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 4.12 116

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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

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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.

Maximum response Maximum response Thermal(ΔT or C) response Thermal response(ΔT or C) t t Thermalor response(ΔT C) tmax Time min max Time Time (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

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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. 119

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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.

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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.

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Table 4 .3 Quantitative IRT tests

Parts 1 2, 3 and 8 4 5 6 7 PTT LTT tests Specimen Excitation Excitation intensity Long pulse IRT (10s) Long pulse IRT (20s) Water presence tests presence Water Far distance detection Far distance Transmission pulse IRT Emissivity determination Hot Air excitation source Air Hot excitation Reflection error estimation Reflection 1 12 6 3 4 1 1 4 2 2 12 4 4 1 4 3 12 4 3 4 4 1 4 4 2 12 4 3 4 4 1 5 2 12 3 4 1 2 6 12 3 1 7 12 3 1 8 2 12 3 1 9 12 1 10 12 3 5 1 11 12 4 4 1 12 12 1 13 2 12 3 1 14 12 1 15 12 4 4 1 16 12 1 17 3 18 2 12 4 2 19 12 4 4 20 12 4 4 21 12 4 3 4 22 12 4 4 23 12 24 12 4 3 4 25 12 26 12 4 4 27 12 4 4 S1 12 1 3 1 1 4 S2 12 1 3 4 1 1 1 4 S3 12 4 1 1 4 S4 12 1 4 1 1 4 S5 12 4 4 IRT tests 12 372 3 6 44 39 76 24 20 4 34 Total 634

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Table 4 .4 Specimens CFRP designs

CFRP materials Design purpose Specimen

1 Unidirectional Fabric CF130 Unbond defect detection, defect size accuracy 2 Unidirectional Fabric CF140 Unbond defect detection, defect size accuracy 3 Unidirectional Fabric CF130 Debonding detection,water presence detection 4 Unidirectional Fabric CF130 Water presence detection Unbond defect detection (single and double CFRP layers), defect size 5 CFRP laminate accuracy,water presence detection Unbond defect, debonding and delamination detection (single and double CFRP 6 Unidirectional Fabric CF140 layers), defect size accuracy Unidirectional Fabric CF140 and bi-directional 7 Unbond defect detection (single and double CFRP layers), Bi-CF detection Fabric 45 Unbond defect detection (single and double CFRP layers), effect of epoxy on top 8 Unidirectional Fabric CF140 specimen surface Unidirectional Fabric CF140 and CFRP 9 Unbond defect detection (combination of fabric and laminate) laminate 10 Unidirectional Fabric CF130 Cracks detection (single and double CFRP fabrics),water presence detection 11 Unidirectional Fabric CF130 Narrow loading cracks detection 12 Unidirectional Fabric CF130 Very fine loading cracks detection Debond and delamination defect detection (single and double CFRP layers), Bi- 13 Bi-directional Fabric 45 CF detection, ,very rough surface preparation 14 Unidirectional Fabric CF130 Narrow loading cracks detection 15 Unidirectional Fabric CF140 and CFRP Cracks detection (CFRP fabrics and laminate),water presence detection Unidirectionallaminate Fabric CF130 and CFRP Unbond defect and delamination detection (combination of fabric and laminates), 16 laminate defect size accuracy 17 CFRP laminate Water presence detection 18 Unidirectional Fabric CF130 Cracks detection,water presence detection 19 Unidirectional Fabric CF140 Debond detection 20 Unidirectional Fabric CF140 Debond detection 21 Unidirectional Fabric CF140 Debond detection 22 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 accuracy 25 Unidirectional Fabric CF130 Cracks detection,very rough surface preparation 26 Unidirectional Fabric CF140 Debond detection 27 Unidirectional Fabrics CF130 and CF140 Unbond defect detection (combination of fabrics), defect size accuracy S1 Unidirectional Fabric CF130 Bond defect detection, defect size accuracy S2 Unidirectional Fabric CF130 Debonding detection,water presence detection Unbond defect and delamination detection (single and double CFRP layers), S3 Unidirectional Fabrics CF130 and CF140 defect size accuracy S4 CFRP laminate Unbond defect detection, defect size accuracy S5 Unidirectional Fabric CF130 and CFRP Unbond defect detection (single and double CFRP layers), defect size accuracy laminate

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

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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

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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.

Painted area

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.

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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.

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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 0.5 127

Chapter Four

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

12.0 11.0 10.0 ΔT-UB011-1s at 50 cm 9.0 C)

o ΔT-UB011-1s at 70 cm 8.0 T ( T

Δ 7.0 ΔT-UB011-1s at 100 cm 6.0 ΔT-UB011-1s at 120 cm 5.0 4.0 3.0

Thermal signal signal Thermal 2.0 1.0 0.0 -1.0 0 10 20 30 40 Time (s)

(b) Defect UB011 thermal responses at different distances Figure 4 .17 Defects in Specimen 1

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Quantitative IRT experimental laboratory program

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

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22.0

18.0 ΔT-UB011-5s at 50 cm

C) ΔT-UB011-1s at 50 cm o ΔT-UB011-1s at 50 cm-ROI2 T ( T 14.0 Δ ΔT-UB011-5s at 50 cm-ROI2 10.0

6.0 Thermal signal signal Thermal 2.0

-2.0 0 10 20 30 40 50 60 Time (s)

(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.

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Quantitative IRT experimental laboratory program

ΔT(q)max = 0.032 q – 5.746 Equation 4 .3

22.0

18.0 ΔT-UB011-1s at 50 cm

C) ΔT-UB011-3s at 50 cm o ΔT-UB011-5s at 50 cm T ( T 14.0 Δ

10.0

6.0 Thermal signal signal Thermal 2.0

-2.0 0 10 20 30 40 50 60 Time (s)

Figure 4 .19 Defect UB011 thermal responses at different pulse intervals

1000 900 800

) 700 2 600 500 400

Heat Flux (w/m Flux Heat 1 s 300 3 s 200 5 s 100 0 0 5 10 15 20 25 o ∆Tmax ( C)

Figure 4 .20 Heat flux versus maximum thermal signal in Specimen 1 for different pulse intervals

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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 per formed 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

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Quantitative IRT experimental laboratory program

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.

18

UB242- 3s at 50cm 14 UB241- 3s at 50cm

C) UB242- 3s at 70cm o UB241- 3s at 70cm 10

6

Thermal Signal ∆T ∆T Signal ( Thermal 2

-2 0 5 10 15 20 Time (s)

(a) 3 seconds pulse duration, heat source at 50 and 70 cm

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22

18 UB242- 5 s at 50 cm

C) UB241- 5 s at 50 cm o 14 UB242- 1s at 50cm UB241- 1s at 50cm 10

6 Thermal Signal ∆T ∆T ( Signal Thermal 2

-2 0 5 10 15 20 Time (s)

(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

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Quantitative IRT experimental laboratory program

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 2 o W/m are produce ΔTmax less than 2.5 C, 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.

1800 UB241-1s 1500 UB241-3s UB241-5s ) 2 1200

900

Heat flux flux (w/m Heat 600

300

0 0 5 10 15 20 o ∆Tmax ( C)

(a) Defect UB241

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Chapter Four

1800

UB242-1s 1500 UB242-3s ) 2 1200 UB242-5s

900

Heat flux (w/m flux Heat 600

300

0 0 5 10 15 20 o ∆Tmax ( C)

(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.

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Quantitative IRT experimental laboratory program

16.0

14.0 ΔT-UB063-5s at 50cm ΔT-UB063-5s at 70cm

C) 12.0 o

T ( T ΔT-UB063-5s at 120cm

Δ 10.0

8.0

6.0

4.0 Thermal signal signal Thermal

2.0

0.0 0 20 40 60 80 Time (s)

(a)

8.0 ΔT-UB064-5s at 50cm 7.0 ΔT-UB064-5s at 70cm

C) 6.0

o ΔT-UB064-5s at 120cm T ( T

Δ 5.0

4.0

3.0

2.0 Thermal signal signal Thermal

1.0

0.0 0 20 40 60 80 Time (s)

(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

137

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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.

6.00

5.00 UB063-5s at 50cm 4.00 UB064-5s at 50cm 3.00

2.00 Contrast

1.00

0.00

-1.00 0 50 100 150 Time (s)

(a)

3.00

2.50 UB063-5s at 120cm 2.00

1.50 UB064-5s at 120cm

1.00

Contrast 0.50

0.00

-0.50

-1.00 0 50 100 150 Time (s)

(b) Figure 4 .25 Thermal contrast of Specimen 6 with 5 s pulse: (a) excitation at 50 cm, (b) excitation at 120 cm

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Quantitative IRT experimental laboratory program

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.

6.00 UB063-5s at 50cm 5.00 UB063-5s at 70cm

4.00 UB063-5s at 100cm

UB063-5s at 120cm 3.00

2.00 Contrast

1.00

0.00

-1.00 0 50 100 150 Time (s)

Figure 4 .26 Contrast of UB063 with 5 s pulses at different distances

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4.00 3.50

3.00 UB063-5s at 100cm 2.50 UB063-3s at 100cm 2.00 UB063-1s at 100cm 1.50

Contrast 1.00 0.50 0.00 -0.50 -1.00 0 50 100 150 Time (s)

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

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Quantitative IRT experimental laboratory program

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.

ΔT-UB051-5s at 50cm 10.0 ΔT-UB051-5s at 70cm ΔT-UB051-5s at 100cm

C) ΔT-UB051-5s at 120cm

o 8.0 T ( T Δ 6.0

4.0 Thermal signal signal Thermal 2.0

0.0 0 50 100 150 Time (s)

(a)

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8.0 ΔT-UB052-5s at 50cm 7.0 ΔT-UB052-5s at 70cm ΔT-UB052-5s at 100cm

C) 6.0 ΔT-UB052-5s at 120cm o T ( T

Δ 5.0

4.0

3.0

2.0 Thermal signal signal Thermal

1.0

0.0 0 50 100 150 Time (s)

(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

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Quantitative IRT experimental laboratory program

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.

ΔTmax (oC) 12

10

8

6

4

2

0 50 UB051-5s UB051-3s 70 UB051-1s UB052-5s 100 120 UB052-3s UB052-1s Excitation distance (cm) Figure 4 .30 Specimen 5 unbonded areas maximum thermal signals recorded at different distances

143

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2.0 ΔT-UB052-5s at 100cm 1.8 ΔT-UB052-3s at 100cm 1.6 ΔT-UB052-1s at 100cm C) o 1.4 T ( T

Δ 1.2 1.0 0.8 0.6

Thermal signal signal Thermal 0.4 0.2 0.0 0 50 100 150 Time (s)

(a)

2.0 ΔT-UB052-5s at 120cm 1.8 ΔT-UB052-3s at 120cm 1.6 ΔT-UB052-1s at 120cm C) o 1.4 T ( T

Δ 1.2 1.0 0.8 0.6

Thermal signal signal Thermal 0.4 0.2 0.0 0 50 100 150 Time (s)

(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.

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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

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44.0 6 s UB091 UB092 8.5 s 39.0 10.25 s 13.5 s

C) 26.75 s o 34.0

29.0 Temperature Temperature (

24.0

19.0 130 180 230 280 Pixles

(a) Defects of Specimen 9 surface temperatures

Surface Temperature (oC) UB091 50.0

40.0 UB092

30.0

20.0 0 5 10 15 20 25 101 30 51 35 Time (s) 40 ROI 1-pixels 1 (b) Three-dimensional profile of ROI line Figure 4 .33 Line temperature profile of Specimen 9

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Quantitative IRT experimental laboratory program

25 UB091-1s at 50cm UB092-1s at 50cm 20 UB091-5s at 50cm

C) UB092-5s at 50cm o

15

10

Thermal Signal ∆T ( ∆T Signal Thermal 5

0 0 30 60 90 Time (s)

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 o around 1 C, 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.

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4.0 ΔT-UB161-5s at 50cm 3.5 ΔT-UB161-5s at 100cm ΔT-UB161-1s at 50cm

C) 3.0

o ΔT-UB161-1s at 100cm T ( T

Δ 2.5

2.0

1.5

1.0 Thermal signal signal Thermal

0.5

0.0 0 20 40 60 80 100 120 Time (s)

Figure 4 .35 Specimen 16 thermal signals

11.50 C -UB161-5s at 50cm

9.50 C -UB161-5s at 100cm

7.50

5.50 Contrast 3.50

1.50

-0.50 0 20 40 60 80 100 120 Time (s)

Figure 4 .36 Specimen 16 thermal contrasts at 5 s pulse

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C -UB161-1s at 50cm 4.50 C -UB161-1s at 100cm

3.50

2.50 Contrast 1.50

0.50

-0.50 0 20 40 60 80 100 120 Time (s)

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

149

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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.

24.0

ΔT-UB011-5s at 50cm 19.0

C) ΔT-UBS11-5s at 50cm o

T ( T ΔT-UB011-5s at 100cm Δ 14.0 ΔT-UBS11-5s at 100cm

9.0 Thermal signal signal Thermal 4.0

-1.0 0 5 10 15 20 25 Time (s)

(a) Pulse duration of 5 s

12.0

10.0 ΔT-UB011-1s at 50cm ΔT-UBS11-1s at 50cm C) o 8.0 ΔT-UB011-1s at 100cm T ( T

Δ ΔT-UBS11-1s at 100cm 6.0

4.0

2.0 Thermal signal signal Thermal

0.0

-2.0 0 5 10 15 20 25 30 Time (s)

(b) Pulse duration of 1 s Figure 4 .38 Defects: UB011 and UBS11 signals

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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.

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11.0 ΔT-UB051-5s at 50cm 9.0

C) ΔT-UBS41-5s at 50cm o

T ( T ΔT-UB051-5s at 100cm

Δ 7.0 ΔT-UBS41-5s at 100cm

5.0

3.0 Thermal signal signal Thermal 1.0

-1.0 0 20 40 60 80 100 120 140 Time (s)

(a) Pulse duration of 5 s

4.0 3.5 3.0 ΔT-UB051-1s at 50cm

C) ΔT-UBS41-1s at 50cm o 2.5

T ( T ΔT-UB051-1s at 100cm

Δ 2.0 ΔT-UBS41-1s at 100cm 1.5 1.0 0.5

Thermal signal signal Thermal 0.0 -0.5 -1.0 0 20 40 60 80 100 120 Time (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.

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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.

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30

25 DB031-5s-50cm DB031-5s-70cm C) o DB031-5s-100cm 20 DB031-5s-120cm

15

10 Thermal Signal ∆T ( ∆T Signal Thermal 5

0 0 20 40 60 80 100 120 140 Time (s)

(a) 30 DB031-3s-50cm 25 DB031-3s-70cm

C) DB031-3s-100cm o 20 DB031-3s-120cm

15

10 Thermal Signal ∆T ( ∆T Signal Thermal 5

0 0 20 40 60 80 100 120 140 Time (s)

(b) 10 9 DB031-1s-50cm DB031-1s-70cm 8 DB031-1s-100cm C) o 7 DB031-1s-120cm 6 5 4 3 Thermal Signal ∆T ( ∆T Signal Thermal 2 1 0 0 20 40 60 80 100 120 140 Time (s)

(c) Figure 4 .41 Specimen 3 debonding area signals: (a) Pulse is 5 s, (b) pulse is 3 s, (c) pulse is 1 s

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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)

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(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

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Quantitative IRT experimental laboratory program

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.

23.0 ΔT-DB261-5s at 50cm

C) ΔT-DB031-5s at 50cm o 18.0 T ( T Δ 13.0

8.0 Thermal signal signal Thermal 3.0

-2.0 0 50 100 150 Time (s)

Figure 4 .43 Specimens 3 and 26 debonding responses

12.0 ΔT-DB261-5s at 50cm 10.0 ΔT-DB261-5s at 70cm ΔT-DB261-1s at 50cm C)

o 8.0 ΔT-DB261-1s at 70cm T ( T Δ 6.0

4.0

2.0 Thermal signal signal Thermal

0.0

-2.0 0 50 100 150 Time (s)

Figure 4 .44 Debond DB261 signals

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15.00 C -DB261-5s at 50cm 13.00 C -DB261-5s at 70cm 11.00

9.00

7.00

Contrast 5.00

3.00

1.00

-1.00 0 50 100 150 Time (s)

(a)

11.00 C -DB261-1s at 50cm C -DB261-1s at 70cm 9.00

7.00

5.00 Contrast

3.00

1.00

-1.00 0 50 100 150 Time (s)

(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

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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.

28.0 ΔT-DBS21-5s at 50cm ΔT-DBS21-5s at 70cm 23.0

C) ΔT-DBS21-5s at 100cm o

T ( T ΔT-DBS21-5s at 120cm

Δ 18.0

13.0

8.0 Thermal signal signal Thermal 3.0

-2.0 0 50 100 150 Time (s)

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.

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28 ΔT-DB031-5s at 50cm ΔT -DB031-5s-100cm 23

C) ΔT-DBS21-5s at 50cm o

T ( T ΔT-DBS21-5s at 100cm

Δ 18

13

8 Thermal signal signal Thermal 3

-2 0 50 100 150 Time (s)

Figure 4 .47 Comparison of S pecimens’ 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.

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Quantitative IRT experimental laboratory program

12.00

10.00

8.00

6.00

4.00

2.00 Contrast 0.00 Poly. (C -DBS21-5s at 70cm) -2.00 Poly. (C -DBS21-3s at 70cm) -4.00 Poly. (C -DBS21-1s at 70cm) -6.00 0 50 100 150 Time (s)

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.

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20 DB131-1s at 50 18 DB131-1s at 70 16 DB131-1s at 100 DB131-1s at 120 14 C)

o DB131-3s at 50 12 DB131-3s at 70 DB131-3s at 100 10 DB131-3s at 120 8 DB131-5s at 50 DB131-5s at 70

Thermal Signal ∆T ∆T ( Signal Thermal 6 DB131-5s at 100 4 DB131-5s at 120

2

0 0 30 60 90 120 150 Time (s)

(a)

1400

1200 ) 2 1000

800

600 DB131- 1 s DB131- 3 s 400 DB131- 5 s Input Heat Flux (W/m Flux Heat Input

200

0 0 5 10 15 20 25 o ∆Tmax ( C)

(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

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Quantitative IRT experimental laboratory program

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.

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Table 4 .6 Debonding defects summary

o Debonding ID ΔTmax ( C) defects and 100 120 thickness at 50 cm 70 cm cm cm (mm) 1 s 9.4 7.1 4 2.7 DB191(0.1) 3 s 16.4 12.5 6.9 4.8 5 s 19.4 16 8 5.6 1 s 12.7 6.7 3.1 1.9 DB192(0.25) 3 s 20.9 11.3 4.9 3.3 5 s 24.5 12.2 5.6 3.7 1 s 3.2 1.1 0.8 0.5 DB201(0.4) 3 s 7 4 2 1.1 5 s 10.5 7 3.9 1.9 1 s 3.2 1.9 1 0.7 DB211(0.5) 3 s 7.9 4.6 2.6 1.8 5 s 11.9 7.2 4.3 2.7 1 s 9.2 5.7 2.9 1.9 DB212(1) 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

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Quantitative IRT experimental laboratory program

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)

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5.0 ΔT-DL162-5s at 50cm 4.0 ΔT-DL162-5s at 100cm ΔT-DL162-1s at 50cm C)

o ΔT-DL162-1s at 100cm

T ( T 3.0 Δ

2.0

1.0 Thermal signal signal Thermal 0.0

-1.0 0 50 100 150 Time (s)

(b)

4.00 C -DL162-5s at 50cm 3.50 C -DL162-5s at 100cm 3.00 2.50 2.00 1.50

Contrast 1.00 0.50 0.00 -0.50 -1.00 0 50 100 150 Time (s)

(c)

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5.00 C -DL162-1s at 50cm 4.00 C -DL162-1s at 100cm

3.00

2.00 Contrast 1.00

0.00

-1.00 0 50 100 150 Time (s)

(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

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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

o ΔTmax ( C) Defect ID 100 120 at 50 cm 70 cm cm cm 1 s 7 6.6 2.6 1.8 DL061 3 s 13 9.2 4.9 3.3 5 s 15.7 11.4 6.5 4.5 1 s 6.1 4.3 1 0.5 DL062 3 s 11.7 5.5 1.6 1 5 s 14 6.9 2.4 1.6 1 s 7.1 3.5 1.3 0.9 DL072 3 s 13.8 7.1 3.6 2.5 5 s 18.3 9.6 5.3 3.5 1 s 8.4 3.6 1.6 0.8 DL132 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

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Quantitative IRT experimental laboratory program

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 1 169

Chapter Four

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.

15.0

UB011 at 5 s UB011 at 3 s C)

o UB011 at 1 s 10.0

5.0 Thermal Signal ∆T Signal ( Thermal

0.0 0 10 20 30 40 Time (s)

(a) Captured from 5 m distance

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15.0

UB011 at 5 s UB011 at 3 s C)

o UB011 at 1 s 10.0

5.0 Thermal Signal ∆T Signal ( Thermal

0.0 0 10 20 30 40 Time (s)

(b) Captured from 10 m distance Figure 4 .52 Thermal responses of Defect UB011

22.0

18.0 ΔT-UB011-5 s at 10 m

C) ΔT-UB011-5 s at 5 m o

T ( T 14.0 ΔT-UB011-5s at 70 cm Δ

10.0

6.0 Thermal signal signal Thermal 2.0

-2.0 0 10 20 30 40 Time (s)

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

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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 o scheme, being only 4 C when recorded as ΔTmax with 10 s pulses. The steel specimen 172

Quantitative IRT experimental laboratory program

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.

1.0

0.0 C) o

T ( T -1.0 Δ

-2.0

ΔT-UBS41-Transmission -3.0 Thermal signal signal Thermal -4.0

-5.0 0 20 40 60 80 100 120 140 Time (s)

(a) Thermal signal

2.00

1.50 C -UBS41-Transmission 1.00

0.50

0.00

Contrast -0.50

-1.00

-1.50

-2.00 0 20 40 60 80 100 120 140 Time (s)

(b) Thermal contrast Figure 4 .54 UBS41 transmission observation method thermal responses

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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: 174

Quantitative IRT experimental laboratory program

. 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.

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. 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 176

Quantitative IRT experimental laboratory program

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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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 178

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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.

50

50 100

50

50

Figure 4 .57 Measuring defects in Specimen 1 in mm

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100 70

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.

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220 180

100

Figure 4 .59 Specimen 8 defect sizes in mm

70

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

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S1. Several 3-dimensional profiles of this region of interest were constructed at different times after the end of the 1 s pulse from 50 cm distance. Both defects read 8 oC thermal signals immediately after the end of the pulse, as shown in Figure 4.61c, however, the shapes of the defects were not clear, due to the increase in the defect-free area neighbouring the defect. After 3.25 s from the pulse end, the signal reduced but the shape detection increased, as shown in Figure 4.61d. Figure 4.61e shows that when the ΔT reaches to 4 oC at 4.25 s from pulse end, defect shapes become easier to determine. After 7 s the signals become around 2 oC, but with clear defect size dimensions for UBS11 and UBS14.

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(a) Specimen S1 defects (b) ROI of defects UBS11 and UBS14

Surface Surface Temperature (oC) Temperature (oC) UBS11 40.0 40.0 UBS11 38.0 36.0 36.0 UBS14 34.0 32.0 32.0 UBS14 30.0 28.0 28.0 26.0 24.0 24.0 22.0 20.0 20.0

(c) 3-D profile at t = 0 s after pulse end (d) 3D-profile at t = 3.25 s after pulse end

Surface Surface Temperature (oC) Temperature (oC) UBS11 UBS11 40.0 30.0 38.0 29.0 36.0 28.0 34.0 UBS14 27.0 UBS14 32.0 26.0 30.0 25.0 28.0 24.0 26.0 23.0 24.0 22.0 22.0 21.0 20.0 20.0

(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

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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.

70 70

80

Figure 4 .62 Specimen 5 thermogram measurements in mm

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50

25

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.

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Figure 4 .64 Specimen 16 defects measurement

(a) (b)

(c) Figure 4 .65 Groove size detection in GR171: (a) the actual size of the groove under the CFRP laminate, (b) the measured detected defect, (c) groove end details at the concrete surface

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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. o . Defects with ΔTmax values less than 2 C do not generate well-defined boundaries. Shape and size cannot be determined accurately in this case. . Increasing the number of the CFRP layers over the defect reduces the ability to calculate the defect area accurately. . Setting the multi-CFRP fabrics in different fibre directions reduces the ability to calculate the defect area. . The defect size calculation in CFRP-steel system needs higher IR frame rate analysis due to the high speed of heat wave fading in steel substrate. . Defect shape and size under laminate CFRP system are harder to calculate than under the fabric systems. . The technique shows that defect sizes of unbond under multi-CFRP fabric layers cannot be measured precisely. . The exact size of the groove in the concrete-CFRP laminate bond surface is undetermined.

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4.5.4 Part 4: Excitation system design

The main aim of this experimental program was to investigate the efficiency of using different excitation systems. Heating tungsten halogen lamps in spot and flood modes were compared. In addition, an air blower excitation system was investigated. Different kinds of implanted artificial defects were subjected to these excitation schemes and observed thermographically using quantitative IR testing. The experimental program in this part was conducted through 44 IR tests for lamps with different heating shape functions. The second heating scheme was achieved by applying a total of 39 PTT IRT runs using an air blower excitation system.

4.5.4.1 Lamps heating modes The heating tungsten halogen light lamps used in the design as an excitation source to generate heat waves in the active thermography had maximum capacity of 2000 watts with varibeam capability. The light beam can vary from spot to flood mode. The spot mode was utilized for most of the IR tests to generate the surface detection shown in Figure 2.22c with high thermal responses. However, studies were performed using both spot and flood modes in this part of the quantitative active thermography program. As shown in Figure 4.66, the injected heat waves struck the surface with non- homogenous behaviour. The heat wave was designed to hit the centre of the specimen, and for that reason the UB051 and UB052 artificial defects in the centre of that specimen have higher thermal signals compared to the off-centre defects GR053 and GR054. Moreover, within the same UB051 defect, the area close to the centre of the specimen (the epicentre of the heat wave) has a higher temperature than the unbonded areas far from this point, as shown in Figure 4.66c.

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(a) (b)

(c) Figure 4 .66 Thermograms of Specimen 5 (a) before the test, (b) during the heat pulse, and (c) 1s after the heat pulse

The spot mode highlights the maximum response causing it to generate a larger heat wave within the defect zone, while the flood lighting mode helps the thermographer to draw the boundaries of the defect clearly. Figure 4.67 illustrates the two types of heating light modes generated by means of tungsten halogen lamps on Specimen 24. As shown in Figure 4.67a, the maximum temperature was recorded in the centre of the specimen surface where the heat wave was designed to strike. This was an advantage for enhancing the detectability of the unbonding defect. At the same time, it could mislead the thermographer’s analysis, especially during the location of the ROIs. Choosing a large ROI with the ability to record the maximum temperature during the IR sequence run can cause misinterpretation of the location of a defect, particularly with the presence of small hot spots unrelated to the subsurface defects. However, this challenge

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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.

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Moreover, the fading time for both mode signals where the signals record around zero values was very similar.

28.0

ΔT-UB021-5s at 50cm-spot mode 23.0

C) ΔT-UB021-5s at 50cm-flood mode o ΔT-UB021-1s at 50cm-spot mode T ( T

Δ 18.0 ΔT-UB021-1s at 50cm-flood mode

13.0

8.0 Thermal signal signal Thermal 3.0

-2.0 0 10 20 30 40 Time (s)

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.

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(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.

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30

25 DB031-1s-50cm-Spot mode DB031-1s-50cm-Flood mode C) o 20 DB031-5s-50cm-Spot mode DB031-5s-50cm-Flood mode 15

10 Thermal Signal ∆T Signal ( Thermal 5

0 0 50 100 150 Time (s)

(a)

24 C-DB031-5s-50cm-spot mode C-DB031-5s-50cm-flood mode Poly. (C-DB031-5s-50cm-spot mode) 19 Poly. (C-DB031-5s-50cm-flood mode)

14

Contrast 9

4

-1 0 50 100 150 Time (s)

(b)

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24 C-DB031-1s-50cm-spot mode C-DB031-1s-50cm-flood mode 19 Poly. (C-DB031-1s-50cm-spot mode) Poly. (C-DB031-1s-50cm-flood mode)

14

Contrast 9

4

-1 0 50 100 150 Time (s)

(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

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defect. The temperature reached just above 2 oC when the system introduced air for 10 s, as shown in Figure 4.71a. The difference between lamps and air excitation systems was broad. For example, for the same 70 cm distance of excitation source from the surface, the maximum signal traced when using the lamp for only 1 s was 5.7 oC (see Figure 4.18), more than double the signal collected after using the air blower for 10 s. The test of the air blower on Specimen 1 experienced some reflection error at the surface during the IR experimental run. The reflection altered the thermal signal with 0.4 oC by about 10 s half a minute after the start of the test. The error area with the signal curve is highlighted with a yellow rectangle in Figure 4.71a. The computed thermal contrast date for this defect with air excitation has some noise that makes the categorization of the contract behaviour very difficult, as shown in Figure 4.71b. The characterized maximum thermal contrast was around 2.5. It is certain that the error noticed in the thermal signal affected the computing of the contrast. Moreover, the IRT tests of Specimen 1 highlight the high probability of introducing different kinds of errors in the IR results.

3.0

2.5 ΔT-UB011-10s at 70cm C)

o 2.0 T ( T

Δ Reflection error 1.5

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0.5 Thermal signal signal Thermal

0.0

-0.5 0 20 40 60 Time (s)

(a)

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7.50

6.50

5.50 C -UB011-Air Blower at 70cm

4.50

3.50 Contrast 2.50

1.50

0.50

-0.50 0 20 40 60 Time (s)

(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.

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(a)

2.5 ΔT-DB031-5 s at 70cm ΔT-DB031-10 s at 70cm 2.0 ΔT-DB031-20 s at 70cm C) o

T ( T 1.5 Δ

1.0

0.5 Thermal signal signal Thermal 0.0

-0.5 0 20 40 60 Time (s)

(b)

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15.00 C -DB031-5 s at 70cm 13.00 C -DB031-10 s at 70cm C -DB031-20 s at 70cm 11.00

9.00

7.00

Contrast 5.00

3.00

1.00

-1.00 0 20 40 60 Time (s)

(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

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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.

3.0

2.5 ΔT-UB052-20 s at 70cm C)

o 2.0 T ( T Δ 1.5

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0.5 Thermal signal signal Thermal

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-0.5 0 20 40 60 Time (s)

(a) Thermal signal

3.50

3.00 C -UB052-20 s at 70cm

2.50

2.00

1.50

1.00 Contrast 0.50

0.00

-0.50

-1.00 0 20 40 60 Time (s)

(b) Thermal contrast Figure 4 .73 Thermal results of UB052 using air excitation of 20 s

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Increase the number of layers in the CFRP fabric systems decreases the thermal responses significantly. Figure 4.74 illustrates the thermal response of UB081 after it was subjected to air blowing for 20 s. The signal shown in Figure 4.74a considers small to distinguish the defect properly. Detection of a defect through two layers of CF140 fabric by means of an air blower is not practical with the limited capacity of the air blower and the temperature of the hot air. Detection could be enhanced if an air blower of more than 2000 W was used during the IRT test or the temperature of the input air was higher and better controlled. However, increasing the amount and capacity of the air may affect the accuracy of the IR image. An air blower with the ability to produce a controlled temperature air beam is recommended to produce hot spots with higher thermal responses with the same input volume of air.

The contrast in the multi-CFRP fabric sheets revealed irrelevant values and behaviour, as illustrated in Figure 4.74b. This may be attributed mainly to two reasons: (i) by increasing the number of CFRP layers, the thermal contrast in the thermograms contains more noise and misleads the C values; (ii) the air blowing process influences the temperature at the surface. From all data collected in the air blowing excitation program, it was found that the thermal contrast showed in general non-relevant behaviour and it did not follow a specific pattern. Most of the maximum thermal contrast values were not able to be calculated.

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0.9 ΔT-UB081-20 s at 70cm 0.7 C) o

T ( T 0.5 Δ 0.3

0.1

-0.1 Thermal signal signal Thermal

-0.3

-0.5 0 20 40 60 Time (s)

(a) Thermal signal for 20 s exposure time

1.00 0.80 0.60 0.40 0.20 0.00

Contrast -0.20 -0.40 C -UB081-20 s at 70cm -0.60 -0.80 -1.00 0 20 40 60 Time (s)

(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

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o values of ΔTmax was small at 0.7 C. 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.

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3.0

2.5 ΔT-UB011-10s at 70cm ΔT-UBS11-10 s at 70cm C)

o 2.0 T ( T Δ 1.5

1.0

0.5 Thermal signal signal Thermal

0.0

-0.5 0 20 40 60 Time (s)

(a) Thermal signals of defects UB011 and UBS11

2.5

2 ΔT-DBS21-10 s at 70cm C) o ΔT-DB031-10 s at 70cm

T ( T 1.5 Δ

1

0.5 Thermal signal signal Thermal 0

-0.5 0 20 40 60 Time (s)

(b) Thermal contrasts of defects DB031 and DBS21 Figure 4 .75 Thermal responses in concrete and steel- CFRP systems

By comparing the IR data collected from heating lamp and air blower excitation systems, it can be noted that by using the heating air blower the detectability of unbond, debonding and delamination defects is greatly reduced. Using the hot air system, it was

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noticed that due to the air’s high speed the IR images experienced a large amount of noise. It is true that the speed of the air did not exceed 50 kph (the maximum limit for conducting an IR test (ASTM D 4788 1997)), but the noise level was noticeably high. The probability of reflection error was also increased by using the hand air blower.

4.5.4.3 Summary of Part 4 experimental program The fourth stage of the experimental quantitative study focused on defect detectability using different designs and modes of excitation systems. The study used halogen lamps and air blower systems. Unbond, debond, delamination and grooves were investigated in CFRP laminates and fabric attached externally to both concrete and steel substrates. IR analyses were performed on the data collected from about 80 IR tests of both excitation systems.

A number of conclusions can be drawn, based on the results of IR analysis:

. Spot heating mode provides higher signals for defects located under the centre of the injected heat wave, which makes the thermal signals of defects located far from the centre not comparable. . Due to the intense heating wave that can be generated, the spot mode is recommended when the study of defects within the bond zone is required. . Non-related hot spots in the thermograms decrease significantly when flood- light mode is used. . Thermal signals are clearer when spot heating is used than flood mode for all the different defects studied. . Flood mode is not recommended for defect with small area, as clear detection may be not achieved with the low heat intensity applied in this mode. . Capture time of the maximum thermal signals is not affected by mode heating change. . Differences between spot and flood modes in debonds are higher than in unbonded areas. . Excitation with air supply systems produces very small signals and high noise levels in the thermal contrasts for different types of defects. 204

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. The air excitation system is highly likely to produce errors in the recording of thermograms. This may be caused by the air blower system or the reflection on the CFRP surface from the hand movement. . The accuracy of thermal signals when hot air beams are applied with pulse lengths less than 20 s is not acceptable. . In general, the maximum contrast from the air heating system cannot be determined from the analysis of the IR images. . Thermal signals of defect underlying multi-CFRP layers are irrelevant when using an air blower as excitation source. . In spite of the small thermal signals collected using the air excitation system, the signals follow the same behaviour as signals from the lamp system in both concrete and steel and for unbonding and debonding defects. . Air blower devices with the ability to provide high temperature air at acceptable pumping speed may be more useful to produce higher thermal responses. 4.5.5 Part 5: Infra-red errors and noise

IRT has many convenient features that make it applicable in many fields and in superior to other nondestructive tests in many fields. However, similarly to other NDT methods, it is common for the captured thermograms to contain errors. This part of the quantitative program studied the confidence level of the acquired thermograms.

4.5.5.1 Errors in IRT The errors that contribute seriously to IR misreading can be classified into three main groups: transmission path errors which involve absorption, scattering, size of object effects and vignetting; errors that can occur during signal processing and finally, process of characterization that involves surface emissivity and reflections. Emissivity has already been identified for specimen testing as shown in Part 1 of this quantitative program.

While the radiation is passing the medium between the IR detector and the target surface, transmission path errors can occur. IR transmitted energy that crosses the air medium may be subject to absorption or scattering at various levels which leads to errors in the IR reading. The severity of these errors is dependent on the gases in the 205

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medium. Air transparency is not absolute, part of the IR radiation will be absorbed during its crossing in the air. Water vapour (H2O), carbon dioxide (CO2) and ozone (O3) are the gases that cause most absorption in air. However, IR transmittance is heavily dependent on the IR radiation wavelength, reading distance, and meteorological conditions. Each IR detector has specific band infra-red wavelengths with which it can work with. The efficient IR spectrum range that has the minimum effect of the atmosphere and gases is positioned in the window of LWIR between 8 to 13 µm. To minimize the transmission path errors in the IR result both of the IR detectors’ radiation wavelength used in this study were located in this LWIR band.

In addition, a clear and clean test environment was ensured to minimize the effect of suspended solid particles in the medium like dust and smoke. All laboratory tests were conducted in controlled humidity, and ventilation was maintained during the tests. The IR sight-line was always clear of any object that might cause a vignetting effect and reduce the amount of radiation received.

Some errors in thermal signal processing were noticed which had very minor effects. Some points produced irrelevant temperatures during the capture of several thermograms, mainly due to the IR decoder reset time during testing, when the decoder reset the temperature mapping every time the detector functioned. However, these errors appear could be detected easily and their effect eliminated.

Reflection is the most frequent error that influences temperature accuracy in the thermal image data. To minimize this kind of error it is essential to recognize and avoid undesired background atmosphere reflections on the investigated surface from all external sources. It is true that background reflections are normally due to external objects being warmer than the investigated specimen, but error reflection from colder sources should also be taken into consideration. However, if the investigated specimen’s surface is heated well above the external objects, background radiation from external sources will be hardly noticeable in the thermal images. The elimination of these background reflections depends on their nature. Point source reflection, for example, can be solved by relocating the IR detector until its best position is identified 206

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where no error is noticed. It strongly recommended to block the line of sight between any unwanted emittance source and the tested surface. Due to the IR detector’s limited capabilities in distinguishing these background radiations that reflect on the specimen’s surface, shielding the detector from these external radiation sources is a solution to minimize undesired reflection. A special design was adopted during the performance of all IR tests. To prevent all unwanted radiation from objects in the laboratory that could affect the thermograms, a dark curtain was used to cover the entire test equipment, as shown in Figure 4.76a. Moreover, a rigid steel frame was built with sliding shutters coated with matt black paint, to simulate black body emissivity and reduce the reflected radiation of the steel.

In spite of all these actions to reduce the reflection from outside objects, the thermograms were still able to receive reflections from open windows that allowed heat to come through or from the thermographer’s body if he moved during the test. Figure 4.76b shows reflection on the CFRP fabric coming from the open window. This is an indication that reflection error needs to be minimized from all directions including the test’s camera line. The thermographer needs to trial IRT in advance of the main test to set the position of the IR detector to have the minimum reflection on the investigated surface. This can be achieved when IR testing on site is supported by with the ability to analyses the captured thermogram sequences instantaneously.

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(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

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turned-off lamps. Figure 4.77 illustrates the thermograms for the IRT site when it was not covered with the curtain and when the lamp was turned off. As shown in the figure, even with turned off lamps, there is still radiation being emitted from the excitation lamp and many objects in the laboratory. This lamp’s emittance caused an error in the surface temperature recorded on Specimen 1 in Figure 4.77. To study the effect of this unwanted emittance from the turned-off excitation lamps, many IR tests were carried out to compare the IR readings when the shutter was closed and when it was open. Tests were performed on different specimens to cover different defect types. Two pulse lengths at 1 s and 5 s were chosen for CFRP applications with closed and opened shutter. The lamp was positioned at 0.5 m.

Figure 4 .77 Thermogram of the uncovered site with no shutter in use

A comparison of thermal signals recorded with closed and opened shutter revealed that unwanted radiations were emitted from the excitation lamp after it was turned off. Figure 4.78 illustrates the difference in UB021 signals when shielding was used. As expected, the difference in temperature starts to appear after the thermal signal peak. From the results in Figure 4.78 it can be seen that the pulse length influences the amount of error coming from the lamp. For short pulses of 1 s, the IR reading had an error of 0.6 oC in the thermogram sequence recorded when no shutter was used. For 5 s pulse duration the surface was heated well with more than 20 oC increase, which means 209

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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.

10.0

ΔT-UB012-1s at 50cm-shutter opened 8.0 ΔT-UB012-1s at 50cm-shutter closed C) o

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(a) Pulse length of 1 s

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22.0

18.0 ΔT-UB012-5s at 50cm-shutter opened

C) ΔT-UB012-5s at 50cm-shutter closed o

T ( T 14.0 Δ

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-2.0 0 10 20 30 40 Time (s)

(b) Pulse length of 5 s Figure 4 .78 Thermal signals of defect UB021

2.5 ΔT-UB051-1s at 50cm-shutter opened ΔT-UB051-1s at 50cm-shutter closed 2.0 C) o T ( T

Δ 1.5

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Thermal signal signal Thermal 0.5

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(a) UB051 at 1 s pulse length

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12.0 ΔT-UB051-5s at 50cm-shutter opened 10.0 ΔT-UB051-5s at 50cm-shutter closed C) o

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0.0 0 20 40 60 80 100 120 Time (s)

(b) UB051 at 5 s pulse length

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2.0 ΔT-UB052-1s at 50cm-shutter opened C) o ΔT-UB052-1s at 50cm-shutter closed T ( T

Δ 1.5

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Thermal signal signal Thermal 0.5

0.0 0 20 40 60 80 100 120 Time (s)

(c) UB052 at 1 s pulse length

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8.0 ΔT-UB052-5s at 50cm-shutter opened 7.0 ΔT-UB052-5s at 50cm-shutter closed

C) 6.0 o T ( T

Δ 5.0

4.0

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2.0 Thermal signal signal Thermal

1.0

0.0 0 20 40 60 80 100 120 Time (s)

(d) UB052 at 5 s pulse length Figure 4 .79 Error in thermal signals of Specimen 5 defects

A comparison of Figures 4.78 and 4.80 shows that unwanted radiation from turned-off excitation lamps cause almost the same amount of error in thermograms as debonded and unbonded areas. Defect DB031 was covered with the same CFRP fabric as defect UB021, however, for the same pulse duration, the error in the debonding flaw was around 0.65 oC. The errors were taken as an average, due to the high alteration rate in the temperatures.

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10

9 ΔT-DB031-1s at 50cm-shutter opened 8 ΔT-DB031-1s at 50cm-shutter closed C) o 7 6 5 4 3 Thermal Signal ∆T Signal ( Thermal 2 1 0 0 10 20 30 40 50 60 Time (s)

Figure 4 .80 Specimen 3 defect signals

Defects in steel-CFRP specimens showed similar behaviour to concrete-CFRP defects but with smaller error. However, the recognized temperature error when pulses were applied at 1 s was negligible, mainly due to the thermal properties of steel, which allow the heat wave to fade rapidly. The 5 s heat pulse injections again showed small errors in both unbonded and debonded areas, as shown in Figure 4.81 for defects UBS32 and DBS31. However, the debond defect in this steel specimen shows the maximum error at 10 s from the starting time of the pulse injection, then the error rate reduce to almost zero toward the end. This may be attributed to the air pocket in this defect that can change the surface temperature with different rates.

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16.0

14.0

12.0 ΔT-UBS32-5s at 50cm-shutter opened C)

o ΔT-UBS32-5s at 50cm-shutter closed 10.0 T ( T Δ 8.0

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4.0 Thermalsignal 2.0

0.0

-2.0 0 5 10 15 20 25 30 Time (s)

(a) UBS32 at 5 s pulse length

20.0 18.0

16.0 ΔT-DBS31-5s at 50cm-shutter opened C)

o 14.0 ΔT-DBS31-5s at 50cm-shutter closed T ( T

Δ 12.0 10.0 8.0 6.0 Thermalsignal 4.0 2.0 0.0 0 10 20 30 40 50 60 Time (s)

(b) DBS31 at 5 s pulse length Figure 4 .81 Specimen S3 defect signals

The error in the thermal signal of a laminate CFRP-steel system defect is shown in Figure 4.82. The errors are again small and are at their maximum after the pulse peak point. Errors in this system have slightly higher values than the concrete system,

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possibly due to the thermal properties of the steel substrate. The figure shows a similar alteration rate in the two thermal signals.

6.0

ΔT-UBS41-5s at 50cm-shutter closed

C) 4.0 ΔT-UBS41-5s at 50cm-shutter opened o T ( T Δ

2.0

0.0 Thermal signal signal Thermal

-2.0 0 10 20 30 40 50 60 Time (s)

Figure 4 .82 DBS31 errors in signal of 5 s pulse length

In summary, the results presented in this part show the need to cut off the radiation from turned-off excitation systems by using a shutter. Moreover, the results highlight the need to eliminate unwanted radiation from objects surrounding the surface of interest.

4.5.5.2 Noise in the IRT Noise in thermograms can be evaluated by constructing noise population histogram, which are usually calculated to predict the probability density function. This histogram usually follows normal distribution, which is often assumed in noise distribution processes in IRT analysis. However, there is still a chance of non-normal noise occurring.

To identify the noise content in IR images, it is necessary to analyze two images at pixel level. If the two thermal images show the same scene under the same condition, noise will appear as the differences between the two images. The subtraction process was followed during the IR analysis of several specimens to study the noise level of their thermograms. To fulfill the constant scene conditions, thermogram frames were recorded before the heating application. Figure 4.83 displays Specimen 5 noise analysis

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and evaluation. As mentioned, two frames at different times were captured in a static scene before the IR testing of this specimen. Frame number two was recorded 2 s after frame 1. Figures 4.83a and 4.83b show these thermograms. Figure 4.83c shows the subtraction thermogram produced by subtracting frame 2 from frame 1 IR images. Figure 4.83d illustrates the histogram of the noise evaluation after the subtraction of the two thermal images captured of Specimen 5 in the static scene. From the results of the histogram shown in Figure 4.83d it can be seen the bell shape has normal distribution which means that random noise content is slight.

(a) Thermogram frame number 1

(b) Thermogram frame number 8

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(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 218

Quantitative IRT experimental laboratory program

MATLAB has more sophisticated facilities and greater capabilities. Figure 4.84 shows examples of filters employed with IR images and 3-dimensional profiles of defect UB081. It was found that the most efficient filters that can reduce the sharp noise within the construction of the 3-D profiling are Gaussian 5×5, and neighbourhood averaging 5×5. It was noticed that sharp points were eliminated with these two filters in the thermograms. However, the thermal signal of this defect did not show significant change when these two filters were applied, mainly because of the size of ROI that was designed to measure the IR data from the thermograms and the method of recording the temperature within the ROI area of that defect. Different filters can be applied to increase some feature of the data. However, using different filters to enhance the quality of images during thermogram processing was not one of the aims of this study.

(a) Normal image (b) Averaging 5× 5 filter 5 times

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(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

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4.5.6 Part 6: IR detection of the presence of water

The ability of the IRT testing to detect moisture at debond areas was investigated in this part of the research. During the quantitative thermography tests, several defects were filled with water to investigate water detectability using this technique. Only concrete specimens were investigated with this defect.

The water was inserted using a 60 ml syringe into the defect area. The temperature of the injected water was the same as that of the surrounding environment before conducting the thermography test for most tests. Active PTT tests were applied following the injection of the water. PTT was adopted when the temperature of the injected water was the same as the investigated object in a static scene.

Grooves in Specimen 4 were filled with water to investigate the detection of water under CFRP fabric using IRT. During the IR test, one groove was filled with water and the other remained without water. The thermal result shows that the water in the groove can be detected, but not easily as shown in Figure 4.85. The water acts as a good medium to transfer and alter the heat wave so that the detection will be low. For that reason, it was found that to provide a good detection of water it is necessary to supply a high pulse for a long time. This intensive heat will increase temperature of the entire investigated surface by several degrees and in this case the defect saturated with water will appear as a cold spot. Generating the 3-dimensional profiles in this investigation aids detection markedly. Figure 4.85b exhibits the cold spot clearly in defect GR042.

Nevertheless, Figure 4.85 illustrates some imperfection on the surface during the making of this specimen when excessive epoxy bled on the surface and caused the irrelevant hotspot shown on the surface.

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(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

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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.

30 25 DB031-5s-50cm-with water C) o 20 DB031-5s-50cm 15 10 5 0 -5 Thermal Signal ∆T ( ∆T Signal Thermal -10 -15 0 20 40 60 80 100 120 Time (s)

Figure 4 .86 DB031 signal with water presence

According to the requirement of the ASTM standard D4788, surfaces to be investigated with IRT should be dried for at least 24 hours before the test (ASTM D 4788 1997). This condition was hard to apply when water was inserted into the CFRP fabric system, mainly because of the fabric weave design that allowed water to escape to the surface during the injection. Figure 4.87 demonstrates water escaping from DB031 which led to the cancellation the IR test. IRT testing was postponed 1 day in all cases of water escaping.

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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

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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.

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(a) Water filling the groove (b) Quarter of groove filled

(c) Filled with 60% Figure 4 .88 W ater injection process of GR171 before the pulse injection

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4.00

3.50 GR171 filled with water GR171 C)

o 3.00

2.50

2.00

1.50

1.00 Thermal Signal ∆T ∆T ( Signal Thermal

0.50

0.00 0 30 60 90 120 150 Time (s)

(a) Thermal signals

10.00 9.00 GR171 filled with water GR171 8.00 7.00 6.00 5.00 4.00 Contrast 3.00 2.00 1.00 0.00 -1.00 0 30 60 90 120 150 Time (s)

(b) Contrast Figure 4 .89 Specimen 17 IR results

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(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, 228

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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.

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26

22 ΔT-UB011-1s at 50 cm C)

o 18 ΔT-UB011-3s at 50 cm

T ( T ΔT-UB011-5s at 50 cm Δ 14 ΔT-UB011-10s at 50 cm

10

6 Thermal signal signal Thermal

2

-2 0 10 20 30 40 50 60 Time (s)

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.

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16.0

14.0 ΔT-UB063-5s at 70cm 12.0 C)

o ΔT-UB064-5s at 70cm

T ( T 10.0 Δ ΔT-UB063-10s at 70cm 8.0 ΔT-UB064-10s at 70cm

6.0

Thermalsignal 4.0

2.0

0.0 0 20 40 60 80 100 120 140 Time (s)

Figure 4 .92 Defects UB0 63 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 behaviou r to the 5 s pulses length. In contrast, the maximum thermal signal values of 5 s and 10 s levelled off for defect UB052 under two layers of CFRP laminates. However, after reaching the peak of the thermal signal, defection under multiple laminates showed slight enhancement with 0.5 oC difference in ΔT, as illustrated in Figure 4.93.

Long PTT in laminate CFRP concrete shows a good improvement in the thermal signals detected for both defects under single- and multi-laminate layers. The results show that long PTT, even with more than 10 s pulse lengths, can be recommended when concrete- multi CFRP laminate is under IRT investigation. This heating approach can improve the thermal response of any expected defect under laminates, especially if the laminate’s surface temperature increase does not exceed the limit. However, if a combination of laminate and CFRP fabric is used, the fabric’s surface temperature can be critical with more than 10 s heating.

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8.0 ΔT-UB051-10s at 70cm 7.0 ΔT-UB052-10s at 70cm ΔT-UB051-5s at 70cm

C) 6.0 ΔT-UB052-5s at 70cm o T ( T

Δ 5.0

4.0

3.0

2.0 Thermal signal signal Thermal

1.0

0.0 0 50 100 Time (s)

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.

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25

20 DB031-5s-70cm C) o DB031-10s-70cm 15

10

Thermal Signal ∆T ∆T ( Signal Thermal 5

0 0 50 100 Time (s)

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.

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24.0 UBS11-5s at 70cm

UBS11-10s at 70cm 19.0 C) UBS11-20s at 70cm o T ( T Δ 14.0

9.0 Thermal signal signal Thermal 4.0

-1.0 0 10 20 30 40 Time (s)

Figure 4 .95 D efect 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

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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 235

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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.

14.0 16.0 UB011-0.025Hz 12.0 14.0 12.0 C) C) 10.0 o o T ( T T ( T 10.0 Δ Δ 8.0 8.0 6.0 6.0 4.0 4.0

2.0 signal Thermal Thermal signal signal Thermal 2.0 UB011-0.05Hz 0.0 0.0

-2.0 -2.0 0 10 20 30 40 0 20 40 60 80 Time (s) Time (s) (a) Frequency of 0.05 Hz (b) Frequency of 0.025 Hz Figure 4 .96 Specimen 1 thermal signals by applying LTT

10.0 12

9.0 UBS11-0.05Hz UBS11-0.025Hz 10 8.0 C) C) o 7.0 o

T ( T ( T 8

Δ 6.0 Δ 5.0 6 4.0 4 3.0

Thermal signal signal Thermal 2.0 signal Thermal 2 1.0 0.0 0 0 10 20 30 40 0 20 40 60 80 Time (s) Time (s)

(a) Frequency of 0.05 Hz (b) Frequency of 0.025 Hz Figure 4 .97 Defect UBS11 thermal signals by applying LTT

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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.

20.0 40.0

18.0 35.0 DB031-0.025Hz 16.0

C) C) 30.0 o 14.0 o T ( T ( T

Δ 12.0 Δ 25.0 10.0 20.0

8.0 15.0 6.0 10.0 Thermal signal signal Thermal 4.0 signal Thermal DB031-0.05Hz 2.0 5.0 0.0 0.0 0 10 20 30 40 0 20 40 60 80 Time (s) Time (s) (a) Frequency of 0.05 Hz (b) Frequency of 0.025 Hz Figure 4 .98 Defect DB031 thermal signals by applying LTT

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40 20.0 DBS21-0.05Hz 35 DBS21-0.025Hz

C) C) 30 o o 15.0 T ( T ( T

Δ Δ 25

20 10.0 15

10 Thermal signal signal Thermal 5.0 signal Thermal 5

0.0 0 0 10 20 30 40 0 20 40 60 80 Time (s) Time (s)

(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.

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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.

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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.

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(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 241

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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.

CR101 CR102

CR104 CR103

(a) ROIs in IR image

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CR101 CR101 50.0 CR102 50.0 CR102 Surface Surface o Temperature (oC) Temperature ( C)

40.0 40.0

30.0 30.0

120.0 120.0 51 51

101 101

151 151 0 ROI - Single 0 ROI - Single 5 CF130-pixels 5 CF130-pixels 10 10 201 15 201 15 Time (s) 20 Time (s) 20 25 25 (b) At 5 s from 50cm (c) At 3 s from 50cm

CR101 CR101 50.0 CR102 50.0 CR102 Surface Surface Temperature (oC) Temperature (oC)

40.0 40.0

30.0 30.0

120.0 120.0 51 51

101 101

151 151 0 ROI - Single 0 ROI - Single 5 CF130-pixels 5 CF130-pixels 10 10 201 15 201 15 Time (s) 20 Time (s) 20 25 25 (d) At 1 s from 50cm (e) At 5 s from 70cm

CR101 CR101 50.0 CR102 CR102 50.0 Surface Surface Temperature (oC) Temperature (oC)

40.0 40.0

30.0 30.0

120.0 120.0 51 51

101 101

151 151 0 ROI - Single 0 ROI - Single 5 CF130-pixels 5 CF130-pixels 10 201 10 15 15 201 Time (s) 20 Time (s) 20 25 25 (f) At 3 s from 70cm (g) At 1 s from 70cm Figure 4 .102 C racks 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. 243

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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.

CR104 CR104 50.0 CR103 CR103 50.0 Surface Surface Temperature (oC) Temperature (oC)

40.0 40.0

30.0 30.0

120.0 120.0 51 51

101 101

151 151 0 ROI - Double 0 ROI - Double 5 CF130-pixels 5 CF130-pixels 10 201 10 15 15 201 Time (s) 20 Time (s) 20 25 25 (a) At 5 s from 50cm (b) At 3 s from 50cm

CR104 50.0 CR103 50.0 Surface Surface o Temperature ( C) Temperature (oC)

40.0 40.0

30.0 30.0

120.0 120.0 51 51

101 101

151 ROI - Double 151 0 0 ROI - Double 5 CF130-pixels 5 CF130-pixels 10 201 10 15 15 201 Time (s) 20 Time (s) 20 25 25 (c) At 1 s from 50cm (d) At 5 s from 70cm

CR104 50.0 CR103 50.0 Surface Surface Temperature (oC) Temperature (oC)

40.0 40.0

30.0 30.0

120.0 120.0 51 51

101 101

151 151 0 ROI - Double 0 ROI - Double 5 CF130-pixels 5 CF130-pixels 10 10 15 201 15 201 Time (s) 20 Time (s) 20 25 25 (e) At 3 s from 70cm (f) At 1 s from 70cm Figure 4 .103 Cracks CR103 and CR104 profile trends

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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.

2.5

CR153 at 5s from 50 cm 2.0 C)

o CR155 at 5s from 50 cm T ( T Δ 1.5

1.0

Thermal Signal Signal Thermal 0.5

0.0 0 10 20 30 40 50 60 Time (s)

(a) Thermal signals

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CR155

CR153

(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

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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 247

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than 1 m. Pulses of less than 3 s and applied from further than 70 cm show no good thermal responses for this crack.

CR121

(a) Location of ROI 1 in the Specimen 12

50.0 50.0 CR121 CR121 Surface Surface o Temperature ( C) Temperature (oC) 40.0 40.0

30.0 30.0

120.0 1 20.0 51 51 101 101 151 151 201 201 251 251 ROI 1-pixels ROI 1-pixels 301 301 0 0 351 5 351 5 10 10 15 15 20 20 Time (s) 25 Time (s) 25 (b) At 5 s from 50cm (c) At 3 s from 50cm

50.0 50.0 CR121 CR121 Surface Surface Temperature (oC) Temperature (oC) 40.0 40.0

30.0 30.0

120.0 120.0 51 51 101 101 151 151 201 201 251 ROI 1-pixels 251 ROI 1-pixels 301 301 0 0 5 351 5 351 10 10 15 15 20 20 Time (s) 25 Time (s) 25 (d) At 1 s from 50cm (e) At 5 s from 70cm

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50.0 50.0 CR121 Surface CR121 Surface o Temperature (oC) Temperature ( C)

40.0 40.0

30.0 30.0

120.0 120.0 51 51 101 101 151 151 201 201 251 ROI 1-pixels 251 ROI 1-pixels 301 301 0 0 5 351 5 351 10 10 15 15 20 20 Time (s) 25 Time (s) 25 (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.

Surface Surface Temperature (oC) Temperature (oC) 40.0 CR142 60.0 CR141 CR142

CR141 50.0

40.0 30.0

30.0

120.0 120.0

51 51 0 0 5 ROI 1-pixels 5 ROI 1-pixels 10 101 10 101 15 15 20 20 Time (s) 25 Time (s) 25 (a) At 5 s from 50cm (b) At 5 s from 70cm

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Surface Surface Temperature (oC) Temperature (oC) 40.0 CR141 CR142 40.0 CR141 CR142

30.0 30.0

1 120.0 20.0

51 51 0 0 ROI 1-pixels 5 ROI 1-pixels 5 10 101 10 101 15 15 20 20 Time (s) Time (s) 25 25 (c) At 5 s from 100cm (d) At 5 s from 120cm

Surface Surface o Temperature ( C) Temperature (oC) 60.0 CR142 CR142 60.0

CR141 CR141 50.0 50.0

40.0 40.0

30.0 30.0

120.0 120.0

51 51 0 0 5 ROI 1-pixels 5 ROI 1-pixels 10 101 10 101 15 15 20 20 Time (s) 25 Time (s) 25 (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.

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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 251

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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.

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(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 253

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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

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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

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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 Recommended Substrate Lamp distance Defect type CFRP system range pulse length material (cm) (s) 50 1 – 3 70 1 – 3 Unbonding Single fabric CF130 Concrete 100 1 – 3 120 1 – 3 50 1 – 3 70 1 – 3 Unbonding Single fabric CF140 Concrete 100 1 – 3 120 3 – 5 50 3 – 5 70 3 – 5 Unbonding Double fabric CF140 Concrete 100 3 – 5 120 >5 50 1 – 3 70 3 – 5 Unbonding Single laminate Concrete 100 >5 120 >5 50 3 – 5 70 3 – 5 Unbonding Double laminate Concrete 100 >5 120 >5 50 1 – 3 Single fabric and single 70 3 – 5 Unbonding Concrete laminate combination 100 3 – 5 120 >5 50 3 – 5 Single fabric and double 70 >5 Unbonding Concrete laminate combination 100 >5 120 >5

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50 1 – 3 70 1 – 3 Unbonding Single fabric CF130 Steel 100 1 – 3 120 3 – 5 50 3 – 5 70 3 – 5 Unbonding Single laminate Steel 100 >5 120 >5 50 1 – 3 70 1 – 3 Debonding Single fabric CF130 Concrete 100 3 – 5 120 3 – 5 50 1 – 3 70 1 – 3 Debonding Single fabric CF140 Concrete 100 3 – 5 120 3 – 5 50 1 – 3 70 1 – 3 Debonding Single fabric CF130 Steel 100 3 – 5 120 3 – 5 50 1 – 3 Single fabric 45 bi- 70 1 – 3 Debonding Concrete directional 100 1 – 3 120 3 – 5 50 1 – 3 70 3 – 5 Delamination laminate Concrete 100 >5 120 >5 50 1 – 3 70 1 – 3 Delamination Fabric CF140 Concrete 100 3 – 5 120 >5 50 1 – 3 70 1 – 3 Delamination Fabric 45 bi-directional Concrete 100 3 – 5 120 >5

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Night-time is the best time to conduct an IR test in the field, because unwanted reflection radiation that might come from objects surrounding the investigated surface will be minimized. However, it is sometimes very difficult to eliminate the radiations from surrounding objects in the field. In this case, the effect of the surrounding objects should be taken into consideration during the IR analysis of the recorded images. There is no signal standard that can be applied, and normally it depends on the object's temperature and emissivity.

With all the above guidelines there still remain limited specifications and studies for the applications of IRT in the field conditions, and site conditions play a pivot role in IR readings. It is obvious that the temperature at the time of IR testing affects the temperatures of surfaces under test. Cloudy skies, high winds and surface moisture also affect the radiation recorded by the IR decoder.

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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,

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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) MBrace CFRP saturant Properties Concrete fabric Air epoxy CF140 resin 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 260

Numerical analysis

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

Epoxy layer subdivded into three elements

CFRP fabric layer subdivded into three elements

Figure 5 .2 CFRP and epoxy layers mesh details

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(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.

CFRP-CF140 Artificial defect- MBrace epoxy UB021 y

x

z

300 mm

110 70mm Concrete Specimen 2 300 mm (a) Specimen 2 model

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Heat flux (W/m2)

CF140 (0.25mm)

Epoxy (0.9mm)

Concrete (50mm)

dT/dz = zero Defect

dT/dx = zero

dT/dy = zero (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

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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 264

Numerical analysis

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

Input heat flux Pulse length (s) (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 265

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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.

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Table 5 .3 Simulations thermal results

Input Pulse Experimental Simulation Change (%) Run heat length # flux ΔTmax tmax ΔTmax tmax (s) o o ΔTmax (W/m2) ( C) (s) ( C) (s) 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

35

30

C) 25 Experimental o Simulated 20

15

10

5 Thermal Signal ∆T ∆T Signal ( Thermal

0

-5 0 20 40 60 80 100 120 Time (s)

Figure 5 .6 Comparison of experimental and simulated thermal signals at run 3

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35

30

1 s

C) 25 o 3 s 20 5 s 15

10

Thermal Signal ∆T ∆T ( Signal Thermal 5

0

-5 0 20 40 60 80 100 120 Time (s)

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

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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 pmerfor ed 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 o pattern altered when the specific heat was less than 750 J/kg. C. 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.

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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 o 5 s. It can be seen the tmax calculated for specific heat of 1200 J/kg. C 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 Specific heat o ΔTmax ( C) Change (%) # (s) (J/kg.oC) 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

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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

12 24

23 y = -0.0197x + 36.942 11 R² = 0.984 22 y = -0.0107x + 19.237 10 R² = 0.9771 21 C) C) o o 20 ( ( 9 max max T T 19 Δ Δ

8 18

17 7 16

6 15 600 700 800 900 1000 1100 1200 1300 600 700 800 900 1000 1100 1200 1300 CFRP specific heat (J/(kg.oC)) CFRP specific heat (J/(kg.oC))

(a) At 1 s pulse (b) At 3 s pulse

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33 20

32 15 y = -0.0162x + 41.581 5 s 31 10 R² = 0.9955 30 3 s 5 1 s

29 (%) 0 max

C) 28 o T

( -5 27 Δ max

T -10

Δ 26 -15 25 Change in in Change 24 -20 23 -25 22 -30 21 -35 600 700 800 900 1000 1100 1200 1300 600 700 800 900 1000 1100 1200 1300 CFRP specific heat (J/(kg.oC)) CFRP specific heat (J/(kg.oC))

(c) At 5 s pulse (d) Changing of different pulses Figure 5 .8 Maximum thermal signal versus different specific heat of CFRP fabric

35 6

30 5.9 y = 0.0009x + 4.7714 25 R² = 0.9995

C) 5.8 o 20 5.7 (s) 15 1200J/kg.oC max

1150J/kg.oC t 1100J/kg.oC 5.6 10 1050J/kg.oC 1000J/kg.oC 5.5 Thermal Signal ∆T Signal ( Thermal 950J/kg.oC 5 900J/kg.oC 850J/kg.oC 0 800J/kg.oC 5.4 750J/kg.oC 700J/kg.oC -5 5.3 0 1 2 3 4 5 6 7 8 9 10 11 600 700 800 900 1000 1100 1200 1300 Time (s) CFRP specific heat (J/(kg.oC))

(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

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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 Conductivity o ΔTmax ( C) # (s) (W/m.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

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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

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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

o o Run Pulse interval (s) Specific heat (J/kg. C) ΔTmax ( C) 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

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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.

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Table 5 .7 Epoxy conductivity simulations 91 to 108

Run Pulse interval Conductivity o ΔTmax ( C) # (s) (W/m.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

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30

30

29 C)

o 29

28

28

27 0.22W/m.oC 0.21W/m.oC 27 0.2W/m.oC Thermal Signal ∆T ∆T ( Signal Thermal 26 0.19W/m.oC 0.18W/m.oC 26 0.17W/m.oC

25 4.50 4.85 5.20 5.55 5.90 6.25 Time (s)

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.

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Table 5 .8 Concrete specific heat simulations 109 to 130

Run Pulse interval Specific heat o ΔTmax ( C) # (s) (J/kg.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

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5.65 5.64 5.63 5.62 5.61 5.60 y = 0.0001x + 5.465 5.59 R² = 1

(s) 5.58

max 5.57 t 5.56 5.55 5.54 5.53 5.52 5.51 5.50 700 800 900 1000 1100 1200 Concrete specific heat (J/(kg.oC))

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.

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Table 5 .9 Concrete conductivity simulations 131 to 148

Run Pulse interval Conductivity o ΔTmax ( C) # (s) (W/m.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:

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. 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. 282

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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 o maximum thermal signal is difficult when the value of ΔTmax reaches only 4 C 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.

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Table 5 .10 CFRP thickness simulations 149 to 175

Run Pulse interval CFRP fabric o ΔTmax ( C) Change (%) # (s) thickness (mm) 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

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18 35

16 30 14 y = 85.19x2 - 89.484x + 28.114 R² = 0.9922 25 y = 161.63x2 - 171.4x + 55.018 12 R² = 0.9934 C) C) 20 o o

10 ( ( max max T T 8 15 Δ Δ

6 10 4 5 2

0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.1 0.2 0.3 0.4 0.5 0.6 CFRP thickness (mm) CFRP thickness (mm)

(a) At 1 s pulse (b) At 3 s pulse

35 60

33 40 31 y = 76.921x2 - 101.26x + 48.923 R² = 0.9987 29 1 s

(%) 20 27 3 s max C) T o ( 5 s 25 Δ 0 max T

Δ 23 -20 21 in Change

19 -40 17

15 -60 0.1 0.2 0.3 0.4 0.5 0.6 0.1 0.2 0.3 0.4 0.5 0.6 CFRP thickness (mm) CFRP thickness (mm)

(c) At 5 s pulse (d) Changing of different pulses Figure 5 .12 Maximum thermal signal versus CFRP thickness

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40 6.2 0.55 mm 0.5 mm 35 0.45 mm 0.4 mm 6 0.35 mm 30 0.3 mm

C) 0.25 mm o 0.2 mm 5.8 25 0.175 mm (s) 20 5.6 y = 1.7143x + 5.1571 max t

15 5.4

Thermal Signal ∆T ∆TSignal ( Thermal 10 5.2 5

0 5 0 1 2 3 4 5 6 7 8 9 10 0.1 0.2 0.3 0.4 0.5 0.6 Time (s) CFRP thickness (mm)

(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.

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Table 5 .11 Epoxy thickness simulations 176 to 196

Run Pulse interval Epoxy thickness o ΔTmax ( C) Change (%) # (s) (mm) 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

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11.2 22.6

y = 1.4042x2 - 3.3343x + 23.219 11.1 22.4 R² = 0.9595

2 11 y = 0.6744x - 1.7111x + 11.561 22.2 R² = 0.9915

10.9 22 C) C) o o ( ( 10.8 21.8 max max T T Δ Δ 10.7 21.6

10.6 21.4

10.5 21.2

10.4 21 0.2 0.5 0.8 1.1 1.4 1.7 0.2 0.5 0.8 1.1 1.4 1.7 Epoxy thickness (mm) Epoxy thickness (mm)

(a) At 1 s pulse (b) At 3 s pulse

32 10

31 8

30 (%) 6 1 s max C) T o (

Δ 3 s 29 4 max 5 s T Δ

28 2 Change in in Change

27 0 y = -1.8264x3 + 7.6277x2 - 11.116x + 33.719

26 -2 0.2 0.5 0.8 1.1 1.4 1.7 0.2 0.5 0.8 1.1 1.4 1.7 Epoxy thickness (mm) Epoxy thickness (mm)

(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

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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 Concrete o ΔTmax ( C) # (s) thickness (mm) 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

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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. o . ΔTmax shows negligible changes at less than 1 C 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 290

Numerical analysis

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.

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Table 5 .13 Thermal load studies 215 to 259

Pulse Input heat flux Input heat ΔTmax Run # interval (W/m2) flux (W) (oC) (s) 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

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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

60 1 s y = 0.0108x + 0.0009 R² = 1 50 3 s y = 0.0232x + 6E-05 R² = 1 C) o 40 y = 0.0271x - 0.0002 5 s R² = 1

30

20 Thermal Signal ∆T ∆T ( Signal Thermal 10

0 0 400 800 1200 1600 2000 Input heat flux (W/m2)

Figure 5 .15 Thermal signal versus input heat flux for different pulses

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25 455 W/m2 555 W/m2 666 W/m2 20 777 W/m2 888 W/m2

C) 1000 W/m2 o 1111 W/m2 15 1222 W/m2 1333 W/m2 1444 W/m2 10 1555 W/m2 1666 W/m2 1777 W/m2 1888 W/m2 5 2000 W/m2 Thermal Signal ∆T Signal ( Thermal

0 0 20 40 60 Time (s)

(a) At 1 s pulse interval

50 455 W/m2 45 555 W/m2 666 W/m2 40 777 W/m2

C) 888 W/m2 o 35 1000 W/m2 1111 W/m2 30 1222 W/m2 1333 W/m2 25 1444 W/m2 1555 W/m2 20 1666 W/m2 1777 W/m2 15 1888 W/m2 2000 W/m2 10 Thermal Signal ∆T ∆T ( Signal Thermal 5 0 -5 0 5 10 15 20 25 30 35 40 Time (s)

(b) At 3 s pulse interval

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55 444 W/m2 555 W/m2 666 W/m2 45 777 W/m2

C) 888 W/m2 o 1000 W/m2 35 1111 W/m2 1222 W/m2 1333 W/m2 25 1444 W/m2 1555 W/m2 1666 W/m2 1777 W/m2 15 1888 W/m2 2000 W/m2 Thermal Signal ∆T ∆T Signal ( Thermal 5

-5 0 5 10 15 20 25 30 Time (s)

(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

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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.

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Heat flux (W/m2) CF140 (0.25mm)

Epoxy (0.5mm) CF140 (0.25mm)

Epoxy (0.5mm)

Concrete (50mm)

dT/dz = zero Defect

dT/dx = zero

dT/dy = zero 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.

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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.

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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 o o laboratory program was 7.2 C. The FE simulation shows ΔTmax of 7.609 C. 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.

10 Experimental Simulation 8 C) o 6

4

2 Thermal Signal ∆T ∆T Signal ( Thermal 0

-2 0 10 20 30 40 50 60 Time (s)

(a) Thermal signal of UB064

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38

36 Experimental 34 Simulation C) o 32

30

28

26

24

Surface Temperature ( Temperature Surface 22

20

18 0 30 60 Time (s)

(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 300

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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 o o ΔTmax when specific heats are 700 J/kg. C and 1200 J/kg. C respectively. The rate of o tmax increase for single and double CFRP is 0.09 to 0. 11 for each 100 J/kg. C 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 Specific heat o ΔTmax ( C) Change (%) # (s) (J/kg.oC) 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

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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

9

700 J/kg.oC 8 8 750 J/kg.oC 800 J/kg.oC 850 J/kg.oC 900 J/kg.oC 7 C) o 6 950 J/kg.oC 1000 J/kg.oC 1050 J/kg.oC C) 6 o

( y = -0.0039x + 10.773 1100 J/kg.oC R² = 0.9943 1150 J/kg.oC max 1200 J/kg.oC T 5 4 Δ

4 ∆T ( Signal Thermal 2 3

2 0 600 700 800 900 1000 1100 1200 1300 0 1 2 3 4 5 6 7 8 9 10 11 12 o Time (s) CFRP specific heat (J/(kg. C)) (a) Thermal signal (b) Surface temperature

7.5

7.4

7.3 y = 0.0011x + 5.98 R² = 1 7.2

7.1

(s) 7 max t 6.9

6.8

6.7

6.6

6.5 600 700 800 900 1000 1100 1200 1300 CFRP specific heat (J/(kg.oC))

(c) Time of maximum thermal signals Figure 5 .20 Thermal results versus different specific heats of defect under double CFRP fabrics

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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 Conductivity o ΔTmax ( C) # (s) (W/m.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

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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 Specific heat o ΔTmax ( C) # (s) (J/kg.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

304

Numerical analysis

8 4

7.9 3

7.8 2 1 7.7 (%) 0 7.6 max C) T o

( -1 7.5 Δ max

T -2

Δ 7.4 -3

7.3 in Change -4

7.2 -5 y = -0.0025x + 11.81 Single CFRP 7.1 R² = 0.9992 -6 Double CFRP 7 -7 1500 1600 1700 1800 1900 2000 1500 1600 1700 1800 1900 2000 Epoxy specific heat (J/(kg.oC)) Epoxy specific heat (J/(kg.oC))

(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.

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Table 5 .17 Epoxy conductivity simulations 290 to 295

Run Pulse interval Conductivity o ΔTmax ( C) # (s) (W/m.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 Specific heat o ΔTmax ( C) # (s) (J/kg.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 7.642 306

Numerical analysis

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 Conductivity o ΔTmax ( C) # (s) (W/m.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

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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 CFRP fabric o ΔTmax ( C) Change (%) # (s) thickness (mm) 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

10 9 0.25 mm 0.3 mm 9 y = 11.586x2 - 18.468x + 11.514 8 0.35 mm R² = 0.9998 0.4 mm 7 0.45 mm 8 0.5 mm

C) 0.55 mm o 6 7 C)

o 5 ( 6 max

T 4 Δ 5 3

4 ∆T ( Signal Thermal 2

3 1

2 0 0.2 0.3 0.4 0.5 0.6 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 CFRP thickness (mm) Time (s)

(a) (b)

308

Numerical analysis

7.5 y = 2x + 6.35 7.4

7.3

7.2

7.1 (s) max t 7

6.9

6.8

6.7

6.6 0.1 0.2 0.3 0.4 0.5 0.6 CFRP thickness (mm)

(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.

309

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Table 5 .21 Epoxy thickness simulations 316 to 322

Run Pulse interval Epoxy thickness o ΔTmax ( C) Change (%) # (s) (mm) 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

12

10

y = 7.8298x2 - 19.366x + 15.862 8 R² = 0.9766 C) o ( 6 max T Δ

4

2

0 0.2 0.5 0.8 1.1 1.4 1.7 Epoxy thickness (mm)

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

310

Numerical analysis

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 Concrete o ΔTmax ( C) # (s) thickness (mm) 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.

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Table 5 .23 Thermal load simulations 327 to 341

Pulse Input heat flux Input heat ΔTmax Run # interval (W/m2) flux (W) (oC) (s) 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

312

Numerical analysis

20 16 444 W/m2 555 W/m2 18 14 666 W/m2 777 W/m2 888 W/m2 1000 W/m2 16 1111 W/m2 1222 W/m2 12 1333 W/m2 1444 W/m2 1555 W/m2 1666 W/m2 C) C) o

14 o y = 0.0072x + 3E-14 10 1777 W/m2 1888 W/m2 R² = 1 2000 W/m2 12 8 10 6 8

6 4 Thermal Signal ∆T ∆T ( Signal Thermal Thermal Signal ∆T ∆T ( Signal Thermal 4 2

2 0

0 -2 0 400 800 1200 1600 2000 0 10 20 30 40 50 60 2 Input heat flux (W/m ) Time (s)

(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.

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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. o . Values of ΔTmax show slight reduction (less than 1 C) 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. 314

Numerical analysis

. 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.

315

Conclusions and recommendations

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

317

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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 318

Conclusions and recommendations

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.

319

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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

320

Conclusions and recommendations

(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 321

Chapter Six

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.

322

References

REFERENCES

Aamodt, L. C., J. W. Spicer and J. C. Murphy (1990), "Analysis of characteristic thermal transit times for time-resolved infrared radiometry studies of multilayered coatings", Journal of Applied Physics, Vol. 68, No. 12, pp. 6087- 6098.

ACI Committee 440, (2008), Guide for the Design and Construction of Externally Bonded FRP Systems for Strengthening Concrete Structures, American Concrete Institute

ASM (1992), Nondestructive Evaluation and Quality Control, USA, ASM Handbook Committee.

ASTM D 4788, (1997), Standard Test Method for Detecting Delaminations in Bridge Decks Using Infrared Thermography, Pennsylvania, American Society for Testing and Materials Vol. 4.3

ASTM E1933-99a(2005)e1, (2007), Standard Test Methods for Measuring and Compensating for Emissivity Using Infrared Imaging Radiometers, Pennsylvania, American Society for Testing and Materials Vol. 3.3

ASTM E 1316, (2001), Standard Terminology for Nondestructive Examinations, Pennsylvania, American Society for Testing and Materials Vol. 3.3

ASTM E 1933-99a, (2005), Standard Test Method for Measuring and Compensating for Emissivity Using Infrared Imaging Radiometers, Pennsylvania, American Society for Testing and Materials Vol. 3.3

ASTM E 1965, (2003), Standard Specification for Infrared Thermometers for Intermittent Determination of Patient Temperature, Pennsylvania, American Society for Testing and Materials Vol. 14.02

323

References

Australian Bureau of Meteorology, (2011), Australian Region Infrared Satellite Image, Retrieved 27 August 2011, .

BASF, (2011a), CFRP Fabric Sheet, Retrieved 1 March, 2011, .

BASF, (2011b), CFRP Laminate Typical Applications, Retrieved 1 March, 2011, .

BASF, (2012a), MBrace, An overview of products Retrieved 1 March, 2012, .

BASF, (2012b), MBrace, Application Guide line, Retrieved 1 March, 2012, .

Bejan, A. and D. Allan (2003), Heat Transfer Handbook, USA, Wiley, John & Sons.

Broutman, L., T. Kobayashi and D. Carrillo (1969), "Determination of fracture sites in composite materials with liquid crystal", Journal of Composite Materials, Vol. 3, pp. 702-704.

Brown, J., (2005), Infrared Thermography Inspection of Fiber-Reinforced Polymer Composites Bonded To Concrete, Florida, University of Florida, PhD thesis

Brown, J. R. and H. R. Hamilton (2004), NDE of fiber-reinforced polymer composites bonded to concrete using IR thermography, Thermosense XXVI Orlando, FL, USA, SPIE-Int. Soc. Opt. Eng.

Brown, J. R. and H. R. Hamilton (2004), Phase thermography inspection of multi-layer FRP composites bonded to concrete, International SAMPE Technical 324

References

Conference, San Diego, CA, United States, Soc. for the Advancement of Material and Process Engineering, Covina, CA 91724-3748, United States.

Brown, J. R. and H. R. Hamilton (2007), "Heating methods and detection limits for infrared thermography inspection of fiber-reinforced polymer composites", ACI Materials Journal, Vol. 104, No. 5, pp. 481-490.

Brown, J. R. and H. R. Hamilton (2010), "Quantitative infrared thermography inspection for FRP applied to concrete using single pixel analysis", Construction and Building Materials, Vol. Available online 18 January 2010, .

Busse, G. (1994), "Nondestructive evaluation of polymer materials", NDT & E International, Vol. 27, No. 5, pp. 253-262.

Byrnes, J. (2009), Unexploded Ordnance Detection and Mitigation, Ciocco, Springer.

CEB-FIP Bulletin 14, (2001), Externally Bonded FRP Reinforcement for RC Structures, Switzerland, FIB

Center for Ecology and Conservation Biology-Boston University, (2011), Brazilian free-tailed bat Retrieved 1 Sept, 2011, .

Chicago Infrared Thermal Imaging Inc., (2011), Home Moisture Management by IR thermography, Retrieved 1 Sept, 2011, .

Childs, P. R. N. (2001), Practical Temperature Measurement, Oxford, Boston, Butterworth-Heinemann.

Clemente Ibarra-Castanedo, Stéphane Guibert, Jean-Marc Piau, Xavier P. V. Maldague and Abdelhakim Bendada (2007), "Inspection of aerospace materials by pulsed thermography, lock-in thermography and vibrothermography: A comparative

325

References

study", Proceedings of SPIE - The International Society for Optical Engineering,Thermosense XXIX, Vol. 6541, pp. 6541161-6541169.

European Space Agency, (2011a), Herschel's sneak preview: PACS images of M51, Retrieved 1 March, 2011, .

European Space Agency, (2011b), A three-colour far-infrared image of M51, Retrieved 1 March, 2011, .

FLIR, (2011), B200/B300, Retrieved 1 March, 2011, .

Fyfe-Co. LLC, (2011), Tyfo® BCC Fabric Composite, Retrieved 1 March, 2011, .

Gerhard, H. and G. Busse (2006), "Lockin-ESPI interferometric imaging for remote non-destructive testing", NDT & E International, Vol. 39, No. 8, pp. 627-635.

Grinzato, E., R. Trentin, P. G. Bison and S. Marinetti (2007), Control of CFRP strengthening applied to civil structures by IR thermography, Thermosense XXIX Orlando. FL, United States, SPIE.

Haddon, J. F. (1988), "Generalised threshold selection for edge detection", Pattern Recognition, Vol. 21, No. 3, pp. 203.

Halabe, U. B., A. Vasudevan, H. V. S. GangaRao, P. Klinkhachorn and G. L. Shives (2003), Nondestructive evaluation of fiber reinforced polymer bridge decks using digital infrared imaging, Proceedings of the 35th Southeastern Symposium, Morgantown, WV, USA, IEEE.

Head, J. F., C. A. Lipari, F. Wang and R. L. Elliott (1997), Cancer risk assessment with a second-generation infrared imaging system, Infrared Technology and Applications XXIII, Orlando, FL, United states, SPIE. 326

References

Hearle, J. W. S. (2001), High-Performance Fibres, Cambridge- England, Woodhead Publishing Ltd and CRC Press LLC.

Herschel, W. (1800a), Experiments on the Solar, and on the Terrestrial Rays that Occasion Heat; with a comparative view of the laws to which light and heat, London, W. Bulmer and Co.

Herschel, W. (1800b), Investigation of the Powers of the Prismatic Colours to Heat and Illuminate Objects, &c. Experiments on the Refrangibility of the Invisible Rays, London, London, W. Bulmer and Co.

Hindle, P. H. (2008). Historical Development. Handbook of Near-Infrares Analysis. D. A. Burns and W. W. Ciurczak. Boca Raton, CRC Press Taylor & Francis Group.

Hu, C. W., J. K. C. Shih, R. Delpak and D. B. Tann (2002), Detection of air blisters and crack propagation in FRP strengthened concrete elements using infrared thermogaphy, Infrared Camera Application Conference, Orlando, Florida.

Hudson, R. D. (1969), Infrared System Engineering, New York, Wiley-Interscience.

Hukse Flux, (2011), PU seriesheat flux sensors and specials, Retrieved 12 Dec., 2010, .

Huntsman Advanced Materials, (2011), Araldite 2014 data sheet, Retrieved 28 Dec, 2011, .

IANIRO, (2011), Heat Lamp Datasheet, Retrieved 1 March, 2011, .

Kanstad, S. and P. Nordal (1979), "Infrared Photoacoustic Spectroscopy of Solids and Liquids", Infrared physics, Vol. 19, No. 3, pp. 413-422.

Karbhari, V. M. and F. Seible (1999), "Design Considerations for the Use of Fiber Reinforced Polymeric Composites in the Rehabilitation of Concrete Structures", NISTIR 6288, pp. 3/59-72.

327

References

Kett, W. G. (1958), "The Nineveh Lens", The Australasian Journal of Optometry, Vol. 41, No. 7, pp. 317-318.

Khauv, K. (2011). Presentation on FLIR IR systems. Swinburne University of Technology. Melbourne.

Lesniak, J. (1995), "Differential thermography applied to structural integrity assessment", Proceedings of SPIE - The International Society for Optical Engineering, Vol. 2473, pp. 179-189.

Levar, J. M. and H. R. T. Hamilton (2003), "Nondestructive evaluation of carbon fiber- reinforced polymer-concrete bond using infrared thermography", ACI Materials Journal, Vol. 100, No. 1, pp. 63-72.

Lienhard, J. H. (1981), A Heat Transfer Textbook, Massachusetts, USA, Phlogiston Press.

Lipari, C. A. and J. F. Head (1997), Advanced infrared image processing for breast cancer risk assessment, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society,, Piscataway, NJ, USA, IEEE.

Ljungberg, S.-A. (1997), Information potential using IR technology for condition monitoring of reheating furnaces within steel and iron industry, Thermosense XIX: An International Conference on Thermal Sensing and Imaging Diagnostic Applications Orlando, FL, USA, SPIE.

Ljungberg, S.-A. and O. Jonsson (2002a), Infrared thermography - A tool to map temperature anomalies of plants in a greenhouse heated by gas fired infrared heaters, Thermosense XXIV, Orlando, FL, USA, SPIE.

Ljungberg, S.-A. and O. Jonsson (2002b), Passive gas imaging - Preliminary results from gas leak simulations a field study performed during real world conditions, Thermosense XXIV Orlando, FL, USA, SPIE.

328

References

Lyberg, M. D. and S. A. Ljungberg (1991), Thermography and complementary methods-a tool for cost-effective measures in retrofitting buildings, Thermosense XIII Orlando, FL, USA, Publ by Int Soc for Optical Engineering.

Maldague, X. (1993), Non-destructive Evaluation of Materials by Infrared Thermogrphy, London, Spring- Verlag London Lmitied

Maldague, X. and S. Marinetti (1996), "Pulse phase infrared thermography", Journal of Applied Physics, Vol. 79, No. 5, pp. 2694-2694.

Maldague, X. and P. Moore (2001), Nondestructive Testing Handbook - Infrared and Thermal Testing, USA, American Society for Nondestructive Testing.

Malhotra, V. M. and N. J. Carino (2004), Handbook on Nondestructive Testing of Concrete, USA, ASTM International, CRC Press LLC.

MBrace, (2011), MBrace Primer-thermal properties., Retrieved 1 July, 2011, .

MBrace, (2012), MBrace CF130-thermal properties, Retrieved 1 July, 2011, .

Meditherm Inc., (2009), Thermography -Meditherm, Retrieved 12 May, 2009, .

Meditherm Inc., (2011a), A diagnosis of jaw problem, Retrieved 18 March 2011, .

Meditherm Inc., (2011b), Football player with stress fracture, Retrieved 18 March 2011, .

329

References

Meditherm Inc., (2011c), IR image of Breast, Retrieved 18 March 2011, .

Nagarajan, S., P. Banerjee, W. Chen and B. A. Chin (1992), "Control of the welding process using infrared sensors", IEEE Transactions on Robotics and Automation, Vol. 8, No. 1, pp. 86-93.

Nagarajan, S., H. C. Wikle and B. A. Chin (1992), "On-line weld position control for fusion reactor welding", Journal of Nuclear Materials, Vol. 191-94, No. pt B, pp. 1060-1064.

Nanni, A. (1999), "Composites: Coming on Strong", Concrete Construction, Vol. 44, pp. 120.

Nanni, A. and A. Lopez (2004), Validation of FRP Composite Technology Trhough Field Testing, 16th World Conference on Nondestructive Testing, Montreal, Canada, CINDE.

NASA ipac, (2007), Near, Mid and Far-Infrared, Retrieved 01 Sept, 2011, .

NEC, (2011), Field of View Diagram -Thermal Image, Retrieved 1 March, 2011, .

Osiander, R. and J. W. M. Spicer (1998), "Time-resolved infrared radiometry with step heating. A review", Revue Générale de Thermique, Vol. 37, No. 8, pp. 680-692.

Planck, M. and M. Masius (1914), The Theory of Heat Radiation, Philadelphia, P. Blakiston's Son & Co.

Ptolemy and A. M. Smith (1996), Ptolemy's Theory of Visual Perception: An English Translation of the Optics with Introduction and Commentary, Pennsylvania, Diane Publishing.

330

References

Rantala, J. (1996), "Lock-in vibrothermography applied for nondestructive evaluation of polymer materials", Materials Science Forum, Vol. 210, No. 1, pp. 433-438.

Sabra, A. I. (1989), The Optics of Ibn al-Haytham. Books I-II-III: On Direct Vision. English Translation and Commentary, London, The Warburg Institute, University of London.

Salerno, A., D. Wu and G. Busse (1997), "Thermographic inspection with ultrasonic excitation ", Review of Progress in Quantitative Nondestructive Evaluation, pp. 345-352.

Shull, P. J. (2002), Nondestructive evaluation: theory, techniques, and applications, New York, Marcel Dekker, Inc.

Starnes, M. A., (2002), Development of Technical Bases for Using IR Thermography for NDE of FRP Composites Bonded to Concrete, Massachusette Institute of Technology, PhD thesis

Starnes, M. A., N. J. Carino and E. A. Kausel (2003), "Preliminary thermography studies for quality control of concrete structures strengthened with fiber- reinforced polymer composites", Journal of Materials in Civil Engineering, Vol. 15, No. 3, pp. 266-273.

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.

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.

Teng, J. G., J. F. Chen, S. T. Smith and L. L. (2002), FRP-strengthened RC structures, John Wiley and Sons.

331

References

The City of New York, (2011), NYC Severe Weather, Retrieved 28 August, 2011, .

U.S. Navy, (2006), US Navy infrared 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, Retrieved 1 Sept, 2011, .

Valluzzi, M. R., E. Grinzato, C. Pellegrino and C. Modena (2009), "IR thermography for interface analysis of FRP laminates externally bonded to RC beams", Materials and Structures, Vol. 42, No. 1, pp. 25-34.

Varat, (2011), Metrel HSN Variac, Retrieved 1 July 2011, 2011, .

Vavilov, V. and X. Maldague (1994), "Optimization of heating protocol in thermal NDT, short and long heating pulses: A discussion", Research in Nondestructive Evaluation, Vol. 6, No. 1, pp. 1-17.

Vavilov, V. P., I. A. Anoshkin, D. G. Kourtenkov, C. D. Trofimov and T. T. Kauppinen (1997), Quantitative evaluation of building thermal performance by IR thermography inspection data, Thermosense XIX: An International Conference on Thermal Sensing and Imaging Diagnostic Applications Orlando, FL, United states, SPIE.

W. Hillger, R. Meier and R. Henrich (2004), "Inspection of CFRP Components by Ultrasonic Imaging with Air Coupling", Insight - Non-Destructive Testing and Condition Monitoring, Vol. 46, No. 3, pp. 147-150.

Wilson, J. (1991), Thermal analysis of the bottle forming process, Thermosense XIII Orlando, FL, USA, SPIE.

332

Appendix A

APPENDIX A

Specimen details, Chapter 3, Section 3.2.6

Figure A. 1 Specimen 27 spall details

Figure A. 2 Specimen 4 defect details

333

Appendix A

Figure A. 3 Crack measurement

Figure A. 4 Specimen 25 rough surface preparation with CR253 crack

334

Appendix A

Figure A. 5 Specimen 14

Figure A. 6 Specimen 16 before attaching the CFRP fabric

335

Appendix A

Figure A. 7 Steel specimen attached with CFRP fabric

Figure A. 8 Steel specimen S2

336

Appendix B

APPENDIX B

Cracks CR101 and CR102 profile trends presented in Chapter 4 Part 8

CR101 CR102 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Single 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 1 At 5 s from 1 m

CR101 CR102 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Single 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 2 At 3 s from 1 m

337

Appendix B

CR101 CR102 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Single 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 3 At 1 s from 1 m

CR101 CR102 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Single 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 4 At 5 s from 1.2 m

CR101 CR102 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Single 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 5 At 3 s from 1.2 m

338

Appendix B

CR101 CR102 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Single 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 6 At 1 s from 1.2 m

Cracks CR101 and CR102 profile trends presented in Chapter 4 Part 8

CR104 CR103 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Double 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 7 At 5 s from 1 m

CR104 CR103 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Double 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 8 At 3 s from 1 m

339

Appendix B

50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Double 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 9 At 1 s from 1 m

CR104 CR103 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Double 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 10 At 5 s from 1.2 m

340

Appendix B

CR104 CR103 50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Double 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 11 At 3 s from 1.2 m

50.0 Surface Temperature (oC)

40.0

30.0

120.0 51

101

151 0 ROI - Double 5 CF130-pixels 10 15 201 Time (s) 20 25 Figure B. 12 At 1 s from 1.2 m

341

List of publications

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.

343