Shear Wave

Shear wave analysis focuses on understanding and measuring the propagation of shear waves through various materials, primarily to determine material properties like elasticity and stiffness. Current research employs diverse approaches, including physics-informed neural networks (like UNets), convolutional neural networks (CNNs) for image processing and velocity prediction, and Bayesian inference methods to quantify uncertainty in material parameter estimations. These techniques find applications in diverse fields, such as non-destructive testing of materials, medical imaging (elastography), and geophysics (subsurface imaging), offering improved accuracy and efficiency in characterizing material properties and identifying anomalies.