Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation
☆44Jun 24, 2022Updated 4 years ago
Alternatives and similar repositories for Navier_Stokes_cylinder2D
Users that are interested in Navier_Stokes_cylinder2D are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆14Sep 1, 2022Updated 4 years ago
- Implementing physics informed neural networks (PINN) in PyTorch to solve turbulent flows using the Navier-Stokes equations☆29May 17, 2024Updated 2 years ago
- A pytorch implementaion of physics informed neural networks for two dimensional NS equation☆211Apr 7, 2024Updated 2 years ago
- PINNs for 2D Incompressible Navier-Stokes Equation☆64May 16, 2024Updated 2 years ago
- ☆15Mar 13, 2026Updated 6 months ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- PINN in solving Navier–Stokes equation☆138Jun 7, 2020Updated 6 years ago
- Bayesian PINN codes to solve 2D/3D Navier Stokes for wind fields☆12Dec 12, 2023Updated 2 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆100Apr 4, 2024Updated 2 years ago
- Implementation of PINNs for burger's and Navier-Stokes equation with PyTorch☆11May 23, 2024Updated 2 years ago
- ☆20Dec 22, 2025Updated 8 months ago
- Flow field reconstruction and prediction of the 2D cylinder flow using data-driven physics-informed neural network combined with long sho…☆46Nov 11, 2024Updated last year
- Physics Informed Neural Networks (PINNs) code to solve the 3D Poisson-Boltzmann equation.☆17Mar 31, 2025Updated last year
- ☆14Aug 22, 2025Updated last year
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆146Oct 24, 2025Updated 10 months ago
- GPUs on demand by Runpod - Special Offer Available • AdRun AI, ML, and HPC workloads on powerful cloud GPUs—without limits or wasted spend. Deploy GPUs in under a minute and pay by the second.
- ☆50May 18, 2022Updated 4 years ago
- The Simulations of Navier-Stokes Equation in 2D and 3D.☆39Jul 15, 2024Updated 2 years ago
- Applied project based on PINNs. The physical problem is sound propagation underwater&Helmholtz equation.☆17Oct 14, 2021Updated 4 years ago
- OpenFOAM implementation of turbulence models driven by machine learning predictions.☆51Jun 11, 2024Updated 2 years ago
- ☆13May 16, 2023Updated 3 years ago
- 本项目利用pytorch实现了一个简易的模块化DeepONet，凭此可以快速的实现一些简易的DeepONet。☆18Jul 2, 2025Updated last year
- Accompanyig code for "Training Physics-Informed Neural Networks: one learning to rule them all?"☆13Nov 15, 2022Updated 3 years ago
- Physics-informed neural network for solving fluid dynamics problems☆290Jan 28, 2021Updated 5 years ago
- ☆54Sep 13, 2022Updated 4 years ago
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- ☆19Nov 24, 2025Updated 9 months ago
- The lid-driven cavity is a popular problem within the field of computational fluid dynamics (CFD) for validating computational methods. I…☆16Dec 14, 2021Updated 4 years ago
- SE-PINN: Solving the Schrödinger Equation via Physics-Informed Machine Learning☆11Dec 17, 2025Updated 8 months ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆165Jul 16, 2020Updated 6 years ago
- Physics-informed neural networks to solve forward and inverse problems of 1D laminar flames☆23Mar 4, 2025Updated last year
- ☆208Mar 16, 2023Updated 3 years ago
- Laminar flow prediction using graph neural networks☆32Jan 17, 2025Updated last year
- Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction☆31Feb 27, 2026Updated 6 months ago
- some basic algorithms explored on the Yee Grid in FDTD☆14Sep 22, 2018Updated 7 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- An improved and generic PINNs for fluid dynamic analysis is proposed. This approach incorporates three key improvements: residual-based …☆34Aug 11, 2023Updated 3 years ago
- ☆11Jan 7, 2025Updated last year
- QCPINN: Quantum-Classical Physics-Informed Neural Networks☆25Dec 15, 2025Updated 8 months ago
- Codes for finite element method☆36Aug 15, 2026Updated 3 weeks ago
- PyTorch Implementation of Physics-informed Neural Networks☆720May 20, 2024Updated 2 years ago
- Basic implementation of physics-informed neural network with pytorch.☆102Sep 26, 2022Updated 3 years ago
- Code repository for "Learned Turbulence Modelling with Differentiable Fluid Solvers"☆46Sep 30, 2022Updated 3 years ago