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The work presented in this thesis concerns the problem of detecting and characterising the effect of fibre-matrix debonds in a fibre-reinforced composite, on ultrasonic backscattering. Theoretical and experimental investigations were conducted into this problem. Three mathematical models were examined. The first assumed that the debond was a thin crack with non-contacting faces surrounding the fibre. The second modelled the debond by allowing tangential slip between the matrix and fibre defined by an effective shear modulus, K. For the third model, the debond was approximated by a thin visco-elastic layer separating the matrix and fibre. The results of the modelling suggested that for an incident longitudinal wave, the first model acts as an air-filled void with a sharp resonance present in the low ka region. The second and third models both show the backscattering to be attenuated. Experimental investigations were carried out on scale models of a single fibre embedded in an araldite matrix. Steel or copper wires were used for the reinforcing fibre. The agreement between theory and experiment for a well-bonded wire was excellent. The effect on the longitudinal backscattered wave of the wire immediately after debonding was to attenuate heavily the resonances in the backscatter form function. However, after approximately an hour the scatter is seen to relax, closely resembling that from a well-bonded wire. In view of the only partial ability of longitudinal incident waves to detect debonds, shear wave (SH) incidence was investigated. It was shown that shear waves were far more sensitive to the presence of fibre-matrix debonds.

This thesis evaluates a particular ultrasonic nondestructive testing (NDT) system in order to determine its capabilities and limitations in locating defects in concrete structures; specifically tunnel linings, bridge decks, and pavements. The device, a phased-array ultrasonic tomography (UST) system that utilizes shear waves, is a significant advancement in NDT systems. Consequently, there is a need in structural engineering to verify new technologies by assessing their flaw-detecting capabilities in a variety of structural applications. The UST technique does not currently have a testing methodology that is field-ready. In order to develop a methodology, the system was evaluated based on its ability to detect simulated defects, then taken to the field to evaluate natural structural defects on public tunnels, pavements, and airport runways. Types of concrete defects the system is used to detect and localize include air- and water-filled voids, vertical cracks, horizontal delaminations, and abnormalities such as clay lumps. The device is also used to determine reinforcement depth and spacing as well as concrete thickness measurements. This research concludes that the UST system is exceptional at locating horizontal delaminations ranging from 0.05-2.0 mm (0.002-0.079 in.), and is able to differentiate between fully debonded and partially-bonded areas. Vertical cracks could only be detected once they begin to form parallel to the testing surface; however, omission of surface details was found to be a strong indicator of crack presence. Backwall surfaces up to a depth of 762 mm (30 in.) were successfully and accurately determined. Air- and water-filled voids as well as reinforcement details such as layout and depth were also successfully determined and located. With the exception of some medium-sized clay lumps (with a diameter of approximately 102 mm, or 4 in.) surrounding reinforcement, all clay lumps tested were also highly successful.

Nondestructive testing is used extensively throughout the industry for quality assessment and detection of defects in engineering materials. The range and variety of anomalies is enormous and critical assessment of their location and size is often complicated. Depending upon final operational considerations, some of these anomalies may be critical and their detection and classification is therefore of importance. Despite the several advantages of using Nondestructive testing for flaw detection, the conventional NDT techniques based on the heuristic experience-based pattern identification methods have many drawbacks in terms of cost, length and result in erratic analysis and thus lead to discrepancies in results. The use of several statistical and soft computing techniques in the evaluation and classification operations result in the development of an automatic decision support system for defect characterization that offers the possibility of an impartial standardized performance. The present work evaluates the application of both supervised and unsupervised classification techniques for flaw detection and classification in a semi-infinite half space. Finite element models to simulate the MASW test in the presence and absence of voids were developed using the commercial package LS-DYNA. To simulate anomalies, voids of different sizes were inserted on elastic medium. Features for the discrimination of received responses were extracted in time and frequency domains by applying suitable transformations. The compact feature vector is then classified by different techniques: supervised classification (backpropagation neural network, adaptive neuro-fuzzy inference system, k-nearest neighbor classifier, linear discriminate classifier) and unsupervised classification (fuzzy c-means clustering). The classification results show that the performance of k-nearest Neighbor Classifier proved superior when compared with the other techniques with an overall accuracy of 94% in detection of presence of voids and an accuracy of 81% in determining the size of the void in the medium. The assessment of the various classifiers’ performance proved to be valuable in comparing the different techniques and establishing the applicability of simplified classification methods such as k-NN in defect characterization. The obtained classification accuracies for the detection and classification of voids are very encouraging, showing the suitability of the proposed approach to the development of a decision support system for non-destructive testing of materials for defect characterization.

Nondestructive testing is used extensively throughout the industry for quality assessment and detection of defects in engineering materials. The range and variety of anomalies is enormous and critical assessment of their location and size is often complicated. Depending upon final operational considerations, some of these anomalies may be critical and their detection and classification is therefore of importance. Despite the several advantages of using Nondestructive testing for flaw detection, the conventional NDT techniques based on the heuristic experience-based pattern identification methods have many drawbacks in terms of cost, length and result in erratic analysis and thus lead to discrepancies in results. The use of several statistical and soft computing techniques in the evaluation and classification operations result in the development of an automatic decision support system for defect characterization that offers the possibility of an impartial standardized performance. The present work evaluates the application of both supervised and unsupervised classification techniques for flaw detection and classification in a semi-infinite half space. Finite element models to simulate the MASW test in the presence and absence of voids were developed using the commercial package LS-DYNA. To simulate anomalies, voids of different sizes were inserted on elastic medium. Features for the discrimination of received responses were extracted in time and frequency domains by applying suitable transformations. The compact feature vector is then classified by different techniques: supervised classification (backpropagation neural network, adaptive neuro-fuzzy inference system, k-nearest neighbor classifier, linear discriminate classifier) and unsupervised classification (fuzzy c-means clustering). The classification results show that the performance of k-nearest Neighbor Classifier proved superior when compared with the other techniques with an overall accuracy of 94% in detection of presence of voids and an accuracy of 81% in determining the size of the void in the medium. The assessment of the various classifiers’ performance proved to be valuable in comparing the different techniques and establishing the applicability of simplified classification methods such as k-NN in defect characterization. The obtained classification accuracies for the detection and classification of voids are very encouraging, showing the suitability of the proposed approach to the development of a decision support system for non-destructive testing of materials for defect characterization.

The poly(glycidyl methacrylate)-modified magnetite nanoparticles, Fe3O4-PGMA NPs, were investigated and applied in nondestructive flaw detection of polymeric materials in this research. The Fe3O4 endowed magnetic property to the materials for flaw detection while the PGMA promoted colloidal stability and prevented particle aggregation. The magnetite nanoparticles (Fe3O4 NPs) were successfully synthesized by coprecipitation and then surface-modified with PGMA to form PGMA-modified Fe3O4 NPs by both grafting-from and grafting-to approaches. For the grafting-from approach, the Fe3O4 NPs were surface-functionalized with α-bromo isobutyryl bromide (BIBB) to form BIB-modified Fe3O4 NPs (Fe3O4-BIB NPs) with covalent linkage. The resultant Fe3O4-BIB NPs were used as surface-initiators to grow PGMA by surface-initiated atom transfer radical polymerization (SI-ATRP). For the grafting-to approach, the Fe3O4 NP were surface-functionalized with (3-mercaptopropyl)triethoxysilane (MCTES) to form MCTES-modified Fe3O4 NPs (Fe3O4-MCTES NPs). The PGMA with Br-end group was pre-synthesized by ATRP and then was grafted to the surface of the Fe3O4-MCTES NPs by coupling reaction. Both bare and modified Fe3O4 NPs exhibited superparamagnetism and the existence of iron oxide in the form of Fe3O4 was confirmed. The particle size of individual Fe3O4 NPs was about 8 – 24 nm but they aggregated to form clusters. The PGMA-modified NPs formed stable dispersion in chloroform and had larger cluster sizes than the unmodified ones because of the PGMA polymer layer. However, the uniformity of the NP clusters could be improved with PGMA surface grafting. The PGMA surface layer of the grafting-from (Fe3O4-gf-PGMA) NPs was thin and dense while that of the grafting-to (Fe3O4-gt-PGMA) NPs was thick and loose. The hydrodynamic diameters (Zave) of Fe3O4-gf-PGMA NP clusters could be controlled between 176 to 643 nm, dependent on the PGMA contents and reaction conditions. During SI-ATRP, side reactions happened and caused NP aggregation as well as increase of size of NP clusters. However, the aggregation has been minimized through optimization of reaction conditions. Oppositely, Zave values of Fe3O4-gt-PGMA NPs had little variation of about 120 – 190 nm. And the PGMA content of the Fe3O4-gt-PGMA NPs was limited to 12.5% because of the spatial hindrance during grafting process. The saturation magnetization (Ms) of the unmodified Fe3O4 NPs was about 77 emu/g, while those of the grafting-from and grafting-to Fe3O4-PGMA NPs were 50 – 66 emu/g and 63 – 70 emu/g, respectively. For Fe3O4-PGMA NPs with similar Fe3O4 contents, the grafting-to NPs had slightly higher Ms than the grafting-from counterparts. In addition, the Ms of both kinds of the Fe3O4-PGMA NPs with higher Fe3O4 content (> 87%) were also higher than that of the fluidMAG-Amine, the commercially available amine-modified MNPs. Besides, both kinds of Fe3O4-PGMA NPs also had much higher Fe3O4 contents and Ms values than most of the reported PGMA-modified MNPs. The magnetic epoxy nanocomposites (MENCs) were prepared by blending the modified Fe3O4 NPs into bisphenol A diglycidyl ether (BADGE)-based epoxy system and the distributions of both kinds of the PGMA-modified NPs were much better than that of the oleic acid-modified Fe3O4 NPs. Similar to the NPs, the MENCs also exhibited superparamagnetism. By cross-section TEM observation, the grafting-to Fe3O4-PGMA NPs formed more homogeneous distributions with smaller cluster size than the grafting-from counterparts and gave higher Ms of the MENCs. Nondestructive flaw detection of surface and sub-surface defects could be successfully achieved by brightness contrast of images given through eddy current testing (ET) method, which is firstly reported. The mechanical properties of the materials were influenced very slightly when 2.5% or lower Fe3O4-gt-PGMA NPs were present while the presence of the Fe3O4-gf-PGMA NPs (1 – 2.5 %) gave mild improvement of the storage modulus and increase of the glass-rubber transition temperature(Tg) of the MENCs. Furthermore, the Fe3O4-PGMA NPs could be evenly coated onto the functionalized ultra-high molecular weight poly(ethylene) (UHMWPE) textiles. The Fe3O4-gt-PGMA NPs were coated on the textile in order to prepare NP-coated textile-reinforced composite. Preliminary result of ET measurement showed that the Fe3O4-gt-PGMA NPs coated on the textiles could visualize the structure of the textile hidden inside and their relative depth. Accordingly, the incorporation of MNPs to polymers opens a new pathway of damage-free structural health monitoring of polymeric materials.

The poly(glycidyl methacrylate)-modified magnetite nanoparticles, Fe3O4-PGMA NPs, were investigated and applied in nondestructive flaw detection of polymeric materials in this research. The Fe3O4 endowed magnetic property to the materials for flaw detection while the PGMA promoted colloidal stability and prevented particle aggregation. The magnetite nanoparticles (Fe3O4 NPs) were successfully synthesized by coprecipitation and then surface-modified with PGMA to form PGMA-modified Fe3O4 NPs by both grafting-from and grafting-to approaches. For the grafting-from approach, the Fe3O4 NPs were surface-functionalized with α-bromo isobutyryl bromide (BIBB) to form BIB-modified Fe3O4 NPs (Fe3O4-BIB NPs) with covalent linkage. The resultant Fe3O4-BIB NPs were used as surface-initiators to grow PGMA by surface-initiated atom transfer radical polymerization (SI-ATRP). For the grafting-to approach, the Fe3O4 NP were surface-functionalized with (3-mercaptopropyl)triethoxysilane (MCTES) to form MCTES-modified Fe3O4 NPs (Fe3O4-MCTES NPs). The PGMA with Br-end group was pre-synthesized by ATRP and then was grafted to the surface of the Fe3O4-MCTES NPs by coupling reaction. Both bare and modified Fe3O4 NPs exhibited superparamagnetism and the existence of iron oxide in the form of Fe3O4 was confirmed. The particle size of individual Fe3O4 NPs was about 8 – 24 nm but they aggregated to form clusters. The PGMA-modified NPs formed stable dispersion in chloroform and had larger cluster sizes than the unmodified ones because of the PGMA polymer layer. However, the uniformity of the NP clusters could be improved with PGMA surface grafting. The PGMA surface layer of the grafting-from (Fe3O4-gf-PGMA) NPs was thin and dense while that of the grafting-to (Fe3O4-gt-PGMA) NPs was thick and loose. The hydrodynamic diameters (Zave) of Fe3O4-gf-PGMA NP clusters could be controlled between 176 to 643 nm, dependent on the PGMA contents and reaction conditions. During SI-ATRP, side reactions happened and caused NP aggregation as well as increase of size of NP clusters. However, the aggregation has been minimized through optimization of reaction conditions. Oppositely, Zave values of Fe3O4-gt-PGMA NPs had little variation of about 120 – 190 nm. And the PGMA content of the Fe3O4-gt-PGMA NPs was limited to 12.5% because of the spatial hindrance during grafting process. The saturation magnetization (Ms) of the unmodified Fe3O4 NPs was about 77 emu/g, while those of the grafting-from and grafting-to Fe3O4-PGMA NPs were 50 – 66 emu/g and 63 – 70 emu/g, respectively. For Fe3O4-PGMA NPs with similar Fe3O4 contents, the grafting-to NPs had slightly higher Ms than the grafting-from counterparts. In addition, the Ms of both kinds of the Fe3O4-PGMA NPs with higher Fe3O4 content (> 87%) were also higher than that of the fluidMAG-Amine, the commercially available amine-modified MNPs. Besides, both kinds of Fe3O4-PGMA NPs also had much higher Fe3O4 contents and Ms values than most of the reported PGMA-modified MNPs. The magnetic epoxy nanocomposites (MENCs) were prepared by blending the modified Fe3O4 NPs into bisphenol A diglycidyl ether (BADGE)-based epoxy system and the distributions of both kinds of the PGMA-modified NPs were much better than that of the oleic acid-modified Fe3O4 NPs. Similar to the NPs, the MENCs also exhibited superparamagnetism. By cross-section TEM observation, the grafting-to Fe3O4-PGMA NPs formed more homogeneous distributions with smaller cluster size than the grafting-from counterparts and gave higher Ms of the MENCs. Nondestructive flaw detection of surface and sub-surface defects could be successfully achieved by brightness contrast of images given through eddy current testing (ET) method, which is firstly reported. The mechanical properties of the materials were influenced very slightly when 2.5% or lower Fe3O4-gt-PGMA NPs were present while the presence of the Fe3O4-gf-PGMA NPs (1 – 2.5 %) gave mild improvement of the storage modulus and increase of the glass-rubber transition temperature(Tg) of the MENCs. Furthermore, the Fe3O4-PGMA NPs could be evenly coated onto the functionalized ultra-high molecular weight poly(ethylene) (UHMWPE) textiles. The Fe3O4-gt-PGMA NPs were coated on the textile in order to prepare NP-coated textile-reinforced composite. Preliminary result of ET measurement showed that the Fe3O4-gt-PGMA NPs coated on the textiles could visualize the structure of the textile hidden inside and their relative depth. Accordingly, the incorporation of MNPs to polymers opens a new pathway of damage-free structural health monitoring of polymeric materials.:1. Introduction 2. Theoretical section 2.1. Magnetite Nanoparticles (MNPs) 2.2. Applications of MNPs 2.3. Atom transfer radical polymerization (ATRP) 2.4. Magnetic nanocomposites (MNCs) 2.5. Damage-free structural health monitoring (SHM) using MNPs 3. Objective of the work 4. Materials, methods and characterization 4.1. Materials 4.2. Methods 4.3. Formation of polymeric magnetic nanocomposites 4.4. Characterization 5. Results and discussions 5.1. Unmodified magnetite nanoparticles (Fe3O4 NPs) 5.2. Oleic acid-modified (Fe3O4–OA) NPs 5.3. PGMA-modified NPs by grafting-from approach (Fe3O4-gf-PGMA NPs) 5.4. PGMA-modified NP by grafting-to approach (Fe3O4-gt-PGMA NPs) 5.5. Comparison between grafting-from and grafting-to Fe3O4-PGMA NPs 5.6. Magnetic epoxy nanocomposites (MENCs) 5.7. Fiber-reinforced epoxy nanocomposites 6. Conclusions and outlook 7. Appendix 8. List of figures, schemes and tables 9. References Versicherung Erklaerung List of publications