322 citations · 691 across the 10 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
math.NA2020★ 33 cited
Physics informed deep learning for computational elastodynamics without labeled data
Chengping Rao, Hao Sun, Yang Liu
Numerical methods such as finite element have been flourishing in the past decades for modeling solid mechanics problems via solving governing partial differential equations (PDEs)…
cs.CE2020★ 16 cited
Three-dimensional convolutional neural network (3D-CNN) for heterogeneous material homogenization
Chengping Rao, Yang Liu
Homogenization is a technique commonly used in multiscale computational science and engineering for predicting collective response of heterogeneous materials and extracting effecti…
physics.flu-dyn2020★ 322 cited
Physics-informed deep learning for incompressible laminar flows
Chengping Rao, Hao Sun, Yang Liu
Physics-informed deep learning has drawn tremendous interest in recent years to solve computational physics problems, whose basic concept is to embed physical laws to constrain/inf…