ikespand / awesome-machine-learning-fluid-mechanicsLinks
Curated list for ML in FM
☆212Updated last week
Alternatives and similar repositories for awesome-machine-learning-fluid-mechanics
Users that are interested in awesome-machine-learning-fluid-mechanics are comparing it to the libraries listed below
Sorting:
- Lecture material for machine learning applied to computational fluid mechanics☆412Updated 8 months ago
- A curated list of awesome Machine Learning projects in Fluid Dynamics☆103Updated 3 years ago
- Python script for Linear, Non-Linear Convection, Burger’s & Poisson Equation in 1D & 2D, 1D Diffusion Equation using Standard Wall Functi…☆226Updated last year
- Examples of how to use machine learning algorithms in computational fluid dynamics.☆259Updated 3 years ago
- Integrating the TensorFlow 1.15 C-API into OpenFOAM 5.0 for data-driven CFD algorithm development☆215Updated 2 years ago
- DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks☆281Updated last year
- A Computational Fluid Dynamics (CFD) course with Python☆95Updated last year
- flowTorch - a Python library for analysis and reduced-order modeling of fluid flows☆157Updated 6 months ago
- ☆192Updated 2 years ago
- In-situ data analyses and machine learning with OpenFOAM and Python☆179Updated last year
- Reduced order modelling techniques for OpenFOAM☆199Updated 2 weeks ago
- Python for Scientific Computing (FEniCS, PyTorch, VTK)☆125Updated last year
- A simple full-python 2D lattice-boltzmann code☆195Updated 2 years ago
- ☆75Updated 9 months ago
- Physics-informed neural networks for two-phase flow problems☆66Updated 4 months ago
- Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube proble…☆186Updated 2 years ago
- Data-driven Reynolds stress modeling with physics-informed machine learning☆94Updated 6 years ago
- Computational Fluid Dynamics based on PyTorch and the Lattice Boltzmann Method☆256Updated last week
- Physics informed neural network (PINN) for cavity flow governed by Navier-Stokes equation.☆150Updated 5 years ago
- Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).☆103Updated last year
- OpenFOAM and Machine Learning Hackathon☆77Updated 3 months ago
- A curated list of repositories related to fluid dynamics.☆121Updated 2 years ago
- Deep Learning for Reduced Order Modelling☆100Updated 3 years ago
- This repo contains some tutorial type programs showing some basic ways machine learning can be applied to CFD.☆297Updated 6 years ago
- An open-source Python platform of coupling deep reinforcement learning and OpenFOAM☆161Updated 6 months ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆209Updated 2 years ago
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆73Updated 2 years ago
- A large-scale benchmark for machine learning methods in fluid dynamics☆219Updated 9 months ago
- PINN (Physics-Informed Neural Networks) on Navier-Stokes Equations☆113Updated 2 years ago
- PINN in solving Navier–Stokes equation☆111Updated 5 years ago