the-rccg / hw2d
Reference implementation for the Hasegawa-Wakatani model of plasma turbulence inside nuclear fusion reactors in two dimensions
☆23Updated 6 months ago
Alternatives and similar repositories for hw2d:
Users that are interested in hw2d are comparing it to the libraries listed below
- A library for dimensionality reduction on spatial-temporal PDE☆63Updated 10 months ago
- ☆49Updated last year
- A Python library for training neural ODEs.☆20Updated last week
- A Python library for solving any system of hyperbolic or parabolic Partial Differential Equations. The PDEs can have stiff source terms a…☆56Updated 5 years ago
- Automatic-Differentiation-Enabled Plasma Transport in JAX☆28Updated last week
- Scientific Machine Learning Tutorials☆36Updated 3 years ago
- Simple OOP Python Code to run some Pseudo-Spectral 2D Simulations of Turbulence☆65Updated last year
- Pseudospectral Kolmogorov Flow Solver☆37Updated last year
- This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The cod…☆18Updated 3 years ago
- ☆22Updated 7 months ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆144Updated last month
- ☆15Updated last month
- Python interface for libROM, library for reduced order models☆58Updated 2 weeks ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆29Updated 2 years ago
- Differentiable interface to FEniCS for JAX☆52Updated 3 years ago
- 1D-1V Vlasov-Poisson(-Fokker-Planck), Plasma Physics PDE Simulation Tool in NumPy and experiment management in MLFlow☆33Updated last year
- Model-Order Reduction Framework for Nek5000☆13Updated 3 months ago
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆17Updated last year
- ☆51Updated this week
- ☆28Updated last year
- A framework for the automated derivation and parallel execution of finite difference solvers on a range of computer architectures.☆80Updated 8 months ago
- [Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled T…☆59Updated 3 months ago
- The algorithmic differentation tool pyadjoint and add-ons.☆93Updated this week
- Intuitive scientific computing with dimension types for Jax, PyTorch, TensorFlow & NumPy☆82Updated this week
- A scalable reinforcement learning framework for CFD on HPC systems☆28Updated 4 months ago
- A python script to solve the Cahn-Hilliard equation using an implicit pseudospectral method☆37Updated 7 months ago
- Finite Volume Constrained Transport MHD simulation of the Orszag-Tang vortex☆17Updated last year
- ☆10Updated last year
- High-order multiphase/multi-physics flow solver☆25Updated 2 months ago
- Datasets and code for results presented in the ProbConserv paper☆53Updated 8 months ago