Research-on-Solving-Partial-Differential-Equations-of-Solid-Mechanics-Based-on-Physics-Informed-Neural Network
This is the part code of my master thesis, including Data-driven, DEM (Deep Energy Method), and CENN (Deep Energy method with subdomains).
The detail is: 1.Data-driven: familiar to the AD(Automatic Differientiation) in Pytorch 2.DEM:Deep Learning Method with the application to the benchmark of the solid mechanics. 3.CENN:Conservative energy method based on neural networks with subdomains (paper:https://arxiv.org/abs/2110.01359 submitted to CMAME, in major revision)
@author: yizheng wang (王一铮), 447650327@qq.com or wang-yz19@mails.tsinghua.edu.cn
The code is revised from https://github.com/MinhNguyenIKM/dem_hyperelasticity
I will keep updating it, if you find any problem, please contact me without any hesitation by email. Thank you !
If it is helpful, please star me !
In future, I will expand PINN in solid mechanics. If you have any idea, we can do it together for great job!