Quantitative ultrasonic characterisation of surface-breaking cracks - Saini Abhishek (Nanyang Technological University, 2021)
Ultrasonic array-based quantitative defect characterisation offers information about defect type, shape, size, and orientation. This approach facilitates high-accuracy assessment of structural integrity in safety-critical systems. Given the nature of current defect characterisation techniques, researchers face a key challenge in imaging of complex-shaped surface-breaking cracks (SBCs). This thesis explores the potential of exploiting ultrasonic array-based techniques for quantitative characterisation of complex SBCs growing from inaccessible surfaces. In this research, a ray-based method called the Half-Skip Total Focusing Method (HSTFM), and a waveform-based method called the Reverse Time Migration (RTM) with its modification called Multi-Mode RTM (MMRTM), are developed. The HSTFM is a synthetic focusing delay-and-sum based post-processing technique. This method has previously been used to size SBCs initiating from a horizontal backwall. However, limited research was performed to optimise the method rigorously and quantitatively, ascertaining the crack sizing performance. Given that the HSTFM is limited to characterising simple SBCs, an elastic RTM method was developed for accurate reconstruction and sizing of complex shape defects. The RTM image is generated by cross-correlating the forward and backward wavefield, accounting for mode conversions and multiple scattering. Furthermore, additional information about the defect can be manifest by multiple image views of the same region through exploiting geometric features and wave mode conversions. Therefore, the MMRTM was developed to perform imaging by using decoupled elastodynamic extrapolation. The MMRTM decomposes the elastic source and receiver wavefield into longitudinal (L) and shear (S) wave vectors (called wavefield separation) and then performing inner-product imaging to obtain the multi-mode images (LL, LS, SL, and SS). This thesis demonstrates the defect characterisation capability of the proposed imaging techniques for both 2D and 3D geometric configurations.