MinhNguyenIKM / dem_hyperelasticityLinks
A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on the idea of minimum potential energy. The method is named "Deep Energy Method".
☆64Updated 2 weeks ago
Alternatives and similar repositories for dem_hyperelasticity
Users that are interested in dem_hyperelasticity are comparing it to the libraries listed below
Sorting:
- Physics-guided neural network framework for elastic plates☆39Updated 3 years ago
- Code for 'Physics-Informed Neural Networks for Shell Structures'☆38Updated 9 months ago
- Second and fourth-order adaptive phase field modeling of fracture using PHT-splines in the framework of IGA.☆50Updated 4 years ago
- ☆39Updated last year
- A deep energy method (DEM) to solve J2 elastoplasticity problems in 3D.☆20Updated 2 years ago
- ☆52Updated 2 years ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆56Updated last year
- Implementation of a ResUNet-based DeepONet for predicting stress distribution on variable input geometries subject to variable loads. A R…☆13Updated last year
- PINN program for computational mechanics☆111Updated last year
- This repository includes the implementation of the Physics Informed Neural Network and The Deep Energy Method on 1D, 2D boundary value an…☆15Updated 3 years ago
- Adaptive phase field modeling of fracture using deep energy minimization.☆32Updated 4 years ago
- Physics-informed neural networks for two-phase flow problems☆60Updated 3 weeks ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆38Updated this week
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆52Updated 3 years ago
- Soving heat transfer problems using PINN with tf2.0☆19Updated 3 years ago
- Physics Informed Neural Networks To Solve Problems In Solid Mechanics☆12Updated last year
- ☆19Updated last year
- Physics-informed neural networks for identifying material properties in solid mechanics☆19Updated last year
- Computational Homogenization calculation in macroscopic and microscopic structurures. The microscopic BVPs are solved by FFT method. The …☆18Updated 3 weeks ago
- Physics-informed radial basis network☆30Updated last year
- ☆38Updated 3 years ago
- Physics Informed Neural Networks (based on Raissi et al) extended to three dimensions on the heat diffusion equations☆18Updated 2 years ago
- ☆33Updated 3 years ago
- Code of the publication "Physics informed neural networks for continuum micromechanics" published in https://doi.org/10.1016/j.cma.2022.1…☆15Updated 2 years ago
- POD-PINN code and manuscript☆51Updated 6 months ago
- ☆21Updated 7 months ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆66Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Direct and Inverse Heat Conduction Problems☆13Updated 2 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 4 months ago
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 years ago