aaronbuhendwa / twophasePINNView external linksLinks
Physics-informed neural networks for two-phase flow problems
☆74Oct 2, 2025Updated 4 months ago
Alternatives and similar repositories for twophasePINN
Users that are interested in twophasePINN are comparing it to the libraries listed below
Sorting:
- Application of a Physics Informed Neural Network to a two phase flow in porous media problem☆27Oct 11, 2019Updated 6 years ago
- ☆17Apr 18, 2024Updated last year
- Physics-informed neural network for solving fluid dynamics problems☆264Jan 28, 2021Updated 5 years ago
- Physics Informed Neural Networks: a starting step for CFD specialists☆40May 12, 2022Updated 3 years ago
- Implementing physics informed neural networks (PINN) in PyTorch to solve turbulent flows using the Navier-Stokes equations☆27May 17, 2024Updated last year
- Prediction of Fluid Flow in Porous Media by Sparse Observations and Physics-Informed PointNet☆14Aug 24, 2024Updated last year
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆92Apr 4, 2024Updated last year
- Official code for AL-PINNS: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks☆12Jul 29, 2023Updated 2 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28May 8, 2023Updated 2 years ago
- ML-based Surrogate Models to enhance CFD solvers by solving the Pressure Poisson Equation☆10Jan 15, 2026Updated last month
- An improved and generic PINNs for fluid dynamic analysis is proposed. This approach incorporates three key improvements: residual-based …☆33Aug 11, 2023Updated 2 years ago
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆23Nov 29, 2022Updated 3 years ago
- PINNs-MPF is a comprehensive framework designed for simulating interface dynamics using Physics-Informed Neural Networks (PINNs). Leverag…☆20Apr 11, 2025Updated 10 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
- OpenFOAM simulations of transonic shock buffets at a NACA-0012 airfoil☆31May 30, 2023Updated 2 years ago
- Thoughts about ML committee for OpenFOAM☆43Jul 28, 2022Updated 3 years ago
- Blood Flow Modeling with Physics-Informed Neural Networks☆19Jan 10, 2023Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆27Apr 20, 2024Updated last year
- PF-PINNs: physics-informed neural networks framework for solving coupled Allen-Cahn and Cahn-Hilliard phase field equations☆28Feb 18, 2025Updated 11 months ago
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Sep 18, 2023Updated 2 years ago
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆160Jul 16, 2020Updated 5 years ago
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆52Jan 10, 2023Updated 3 years ago
- This project is divided in a two parts. In first study, Lame parameters are identified using tanh activation function. After that, six a…☆13Nov 17, 2022Updated 3 years ago
- Machine Learning enhanced CFD solvers: isothermal & thermal fluid flow☆18Feb 9, 2026Updated last week
- Multi-head attention network for airfoil flow field prediction☆17Sep 13, 2022Updated 3 years ago
- Using deep reinforcement learning for refining meshes in computational fluid dynamics☆30Aug 7, 2023Updated 2 years ago
- ☆93Nov 25, 2024Updated last year
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆21Nov 8, 2022Updated 3 years ago
- 油藏数值模拟☆12Apr 3, 2018Updated 7 years ago
- Numerical assessments of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh …☆10Dec 2, 2022Updated 3 years ago
- ☆25Oct 15, 2020Updated 5 years ago
- Competitive Physics Informed Networks☆32Sep 21, 2024Updated last year
- PINNs for 2D Incompressible Navier-Stokes Equation☆58May 16, 2024Updated last year
- Deep Learning based method to try and learn the problem of inverse Navier Stokes and model the flow for an oscillating airfoil.☆24Jun 7, 2020Updated 5 years ago
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆23May 9, 2021Updated 4 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆20Mar 23, 2023Updated 2 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆168May 15, 2024Updated last year
- PINN-COVID analyzes a plurality of epidemiological models through the lens of physics-informed neural networks (PINNs).☆23Oct 12, 2021Updated 4 years ago
- An automatic knowledge embedding framework for scientific machine learning☆23May 15, 2022Updated 3 years ago