Deep learning-based reconstruction of the structure of heterogeneous composites from their temperature fields

Inverse problems involving transport phenomena are ubiquitous in engineering practice, but their solution is often challenging. In this work, we build a data-driven deep learning model to predict the heterogeneous distribution of circle-shaped fillers in two-dimensional thermal composites using the...

Full description

Bibliographic Details
Main Authors: Haiyi Wu, Hongwei Zhang, Guoqing Hu, Rui Qiao
Format: Article
Published: AIP Publishing LLC 2020-04-01
Series:AIP Advances
Online Access: