A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis
The files contain code and data associated with the paper titled "A Deep Learning Approach to Estimate Stress Distribution: A Fast and Accurate Surrogate of Finite Element Analysis". The paper is authored by Liang Liang, Minliang Liu, Caitlin Martin, and Wei Sun, and published at Journal of The Royal Society Interface, 2018.
The following repository contains further investigation of the method used in the mentioned above paper.
Copyright (c) 2018 by Georgia Tech Research Corporation and Imperial College London. All rights reserved.