Shape Reconstruction of Defect in Anisotropic Solid Using Deep Learning

Abstract

In this study, the shape reconstruction method of a cavity is developed for 2-D pure antiplane anisotropic elastodynamics. Elastic wave scattering by a cavity is implemented by using the convolution quadrature time-domain boundary element method. Scattered waves obtained at receiver points are prepared and utilized for the deep learning. The created deep learning model estimates position and size of a cavity in 2-D pure antiplane anisotropic solids. Numerical example shows that deep learning can be useful for inverse analysis of a defect in anisotropic elastic materials.