tumaer / JAXFLUIDSLinks
Differentiable Fluid Dynamics Package
☆499Updated 2 weeks ago
Alternatives and similar repositories for JAXFLUIDS
Users that are interested in JAXFLUIDS are comparing it to the libraries listed below
Sorting:
- XLB: Accelerated Lattice Boltzmann (XLB) for Physics-based ML☆428Updated last month
- Computational Fluid Dynamics in JAX☆910Updated this week
- Computational Fluid Dynamics based on PyTorch and the Lattice Boltzmann Method☆273Updated 3 weeks ago
- Additive manufacturing simulation with JAX.☆337Updated 6 months ago
- A flexible framework for solving PDEs with modern spectral methods.☆637Updated 3 weeks ago
- Differentiable Finite Element Method with JAX☆558Updated 2 months ago
- Data-driven model reduction library with an emphasis on large scale parallelism and linear subspace methods☆227Updated last month
- Spectral Navier Stokes (and similar) solvers in Python☆342Updated 2 years ago
- Curated list for ML in FM☆234Updated 4 months ago
- DAFoam: Discrete Adjoint with OpenFOAM for High-fidelity Multidisciplinary Design Optimization☆303Updated last week
- ☆397Updated 2 months ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆231Updated 2 years ago
- An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.☆90Updated 5 months ago
- High performance computational platform in Python for the spectral Galerkin method☆223Updated 3 weeks ago
- DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks☆305Updated last year
- Lecture material for machine learning applied to computational fluid mechanics☆427Updated 3 weeks ago
- Framework providing pythonic APIs, algorithms and utilities to be used with PhysicsNeMo core to physics inform model training as well as …☆302Updated last month
- flowTorch - a Python library for analysis and reduced-order modeling of fluid flows☆163Updated 3 weeks ago
- ADflow is a finite volume RANS solver tailored for gradient-based aerodynamic design optimization.☆290Updated last month
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆158Updated last year
- Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey☆292Updated 7 months ago
- Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs…☆508Updated last month
- A simple full-python 2D lattice-boltzmann code☆207Updated 2 years ago
- A code for fast, massively-parallel direct numerical simulations (DNS) of canonical flows☆255Updated 2 weeks ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆168Updated 9 months ago
- Deep learning for Engineers - Physics Informed Deep Learning☆358Updated 2 years ago
- Physics-Informed Neural networks for Advanced modeling☆690Updated last week
- ☆502Updated 9 months ago
- ☆117Updated 11 months ago
- ☆284Updated last year