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".
☆66Updated 2 months ago
Alternatives and similar repositories for dem_hyperelasticity
Users that are interested in dem_hyperelasticity are comparing it to the libraries listed below
Sorting:
- ☆42Updated last year
- A deep energy method (DEM) to solve J2 elastoplasticity problems in 3D.☆23Updated 2 years ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆39Updated 11 months ago
- ☆55Updated 2 years ago
- Physics-guided neural network framework for elastic plates☆45Updated 3 years ago
- Second and fourth-order adaptive phase field modeling of fracture using PHT-splines in the framework of IGA.☆50Updated 4 years ago
- PINN program for computational mechanics☆116Updated last year
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆56Updated last year
- Soving heat transfer problems using PINN with tf2.0☆19Updated 4 years ago
- Physics Informed Neural Networks To Solve Problems In Solid Mechanics☆12Updated last year
- Adaptive phase field modeling of fracture using deep energy minimization.☆34Updated 4 years ago
- ☆19Updated last year
- Multiscale modeling of inelastic materials with Thermodynamics-based Artificial Neural Networks (TANN)☆12Updated 11 months ago
- ☆40Updated 3 years ago
- 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
- Implementation of a ResUNet-based DeepONet for predicting stress distribution on variable input geometries subject to variable loads. A R…☆14Updated 2 years ago
- Physics-informed neural networks for two-phase flow problems☆64Updated 3 months ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆56Updated 3 years ago
- Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material proper…☆21Updated 2 years ago
- Computational Homogenization calculation in macroscopic and microscopic structurures. The microscopic BVPs are solved by FFT method. The …☆18Updated 2 months ago
- Physics-informed radial basis network☆31Updated last year
- Neural Network Approach for Elastoplastic Constitutive Modeling☆25Updated 2 years ago
- ☆73Updated 8 months ago
- Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.☆41Updated this week
- Thermodynamics-based Artificial Neural Networks☆27Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆67Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆87Updated 4 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆32Updated last year
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆80Updated 3 years ago