Artificial intelligence (AI) enhanced finite element multiscale modeling and structural uncertainty analysis of a functionally graded porous beam

Abstract

The local geometrical randomness of metal foams brings complexities to the performance prediction of porous structures. Although the relative density is commonly deemed as the key factor, the stochasticity of internal cell sizes and shapes has an apparent effect on the porous structural behavior but the corresponding measurement is challenging. To address this issue, this chapter is aimed to develop an assessment strategy for efficiently examining the foam properties by combining multiscale modeling and deep learning. The multiscale modeling is based on the finite element (FE) simulations employing representative volume elements (RVEs) with random cellular morphologies, mimicking the typical..