imcs-compsim / pinns_for_comp_mechLinks
Implementation of Physics-Informed Neural Networks for Computational Mechanics based on the DeepXDE package.
☆49Updated this week
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:
- PINN program for computational mechanics☆127Updated last year
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆58Updated 4 years ago
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆79Updated 4 years ago
- A Backward Compatible -- Physics Informed Neural Network for Allen Cahn and Cahn Hilliard Equations☆33Updated 3 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆85Updated last year
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆30Updated 3 years ago
- POD-PINN code and manuscript☆55Updated last year
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆84Updated 2 months ago
- A kind of loss function based on Least Squares Weighted Residual method for computational solid mechanics☆57Updated last year
- A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on…☆69Updated 6 months ago
- Here I will try to implement the solution of PDEs using PINN on pytorch for educational purpose☆54Updated 3 years ago
- Physics-informed neural networks for two-phase flow problems☆70Updated last month
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 3 years ago
- PINN in solving Navier–Stokes equation☆115Updated 5 years ago
- Implementation of 'Physics-Informed Neural Networks for Shell Structures' (European Journal of Mechanics A)☆44Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆26Updated 10 months ago
- Examplary code for NN, MFNN, DynNet, PINNs and CNN☆51Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Competitive Physics Informed Networks☆31Updated last year
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆150Updated 5 years ago
- An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic di…☆31Updated 3 years ago
- physics-informed neural network for elastodynamics problem☆152Updated 3 years ago
- Physics Informed Neural Networks (based on Raissi et al) extended to three dimensions on the heat diffusion equations☆19Updated 3 years ago
- Implement PINN with high level APIs of TF2.0, including a solution of coupled PDEs with PINN☆27Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- ☆83Updated 11 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆92Updated 2 years ago