Ultrasonic inspection of austenitic welds is challenging due to their highly anisotropic and heterogeneous microstructure. The weld anisotropy causes a steering of the ultrasonic beam leading to a number of adverse effects upon ultrasonic array imagery, including defect mislocation and aberration of the defect response. A semi-analytical model to simulate degraded ultrasonic images due to propagation through an anisotropic austenitic weld is developed. Ray-tracing is performed using the A* path-finding algorithm and integrated into a semi-analytical beam-simulation and imaging routine to observe the impact of weld anisotropy on ultrasonic imaging. Representative anisotropy weld-maps are supplied by the MINA model of the welding process. A number of parametric studies are considered, including the magnitude and behaviour of defect mislocation and amplitude as the position of a fusion-face defect and the anisotropy distribution of a weld is varied, respectively. Furthermore, the use of the model to efficiently simulate and evaluate ultrasonic image degradation due to anisotropic austenitic welds during an inspection development process is discussed.
The ultrasonic inspection of austenitic steel welds is challenging due to the formation of highly anisotropic and heterogeneous structures post-welding. This is due to the intrinsic crystallographic structure of austenitic steel, driving the formation of dendritic grain structures on cooling. The anisotropy is manifested as both a 'steering' of the ultrasonic beam and the back-scatter of energy due to the macroscopic granular structure of the weld. However, the quantitative effects and relative impacts of these phenomena are not well-understood. A semi-analytical simulation framework has been developed to allow the study of anisotropic effects in austenitic stainless steel welds. Frequency-dependent scatterers are allocated to a weld-region to approximate the coarse grain-structures observed within austenitic welds and imaged using a simulated array. The simulated A-scans are compared against an equivalent experimental setup demonstrating excellent agreement of the Signal to Noise (S/N) ratio. Comparison of images of the simulated and experimental data generated using the Total Focusing Method (TFM) indicate a prominent layered effect in the simulated data. A superior grain allocation routine is required to improve upon this.
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