Scien42 / NSFnetLinks
PINNs for 2D Incompressible Navier-Stokes Equation
☆53Updated last year
Alternatives and similar repositories for NSFnet
Users that are interested in NSFnet are comparing it to the libraries listed below
Sorting:
- PINN in solving Navier–Stokes equation☆113Updated 5 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆71Updated last year
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆31Updated 3 years ago
- ☆112Updated 8 months ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆84Updated last year
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆117Updated 2 years ago
- ☆77Updated 10 months ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆151Updated 5 years ago
- POD-PINN code and manuscript☆53Updated 11 months ago
- ☆41Updated 3 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 2 years ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆25Updated 8 months ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆91Updated 2 years ago
- Physics-informed neural networks for two-phase flow problems☆69Updated last week
- Implementation of PINNs in TensorFlow 2☆81Updated 2 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆27Updated 2 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆32Updated last year
- Examples implementing physics-informed neural networks (PINN) in Pytorch☆77Updated 4 years ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆57Updated 9 months ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆74Updated 2 years ago
- Original implementation of fast PINN optimization with RBA weights☆60Updated last month
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆30Updated 3 years ago
- A Physics-Informed Neural Network to solve 2D steady-state heat equations.☆159Updated last month
- MIONet: Learning multiple-input operators via tensor product☆38Updated 2 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆98Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated 3 weeks ago
- PDE Preserved Neural Network☆56Updated 4 months ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated last year