imcs-compsim / pinns_for_comp_mechLinks
Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.
☆56Updated 2 weeks ago
Alternatives and similar repositories for pinns_for_comp_mech
Users that are interested in pinns_for_comp_mech are comparing it to the libraries listed below
Sorting:
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆59Updated 5 years ago
- PINN program for computational mechanics☆128Updated last year
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆83Updated 4 years ago
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆58Updated last year
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆89Updated last year
- physics-informed neural network for elastodynamics problem☆152Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆86Updated 4 months ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- ☆89Updated last year
- A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on…☆70Updated 7 months ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆75Updated 2 years ago
- PINN in solving Navier–Stokes equation☆120Updated 5 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆36Updated 3 years ago
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆57Updated 3 years ago
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆28Updated 2 years ago
- Physics Informed Neural Networks (based on Raissi et al) extended to three dimensions on the heat diffusion equations☆19Updated 3 years ago
- Physics-informed neural networks for two-phase flow problems☆72Updated 2 months ago
- ☆50Updated 3 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆37Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆201Updated 2 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆155Updated 5 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆27Updated 11 months ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆72Updated last year
- PINNs for 2D Incompressible Navier-Stokes Equation☆57Updated last year
- An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic di…☆31Updated 3 years ago
- Implementation of PINNs in TensorFlow 2☆81Updated 2 weeks ago
- This is the code of my master thesis.☆169Updated 8 months ago