akaptano / POD-Galerkin_MHDLinks
This codes calculates the dimensionalized POD and uses SINDy from the PySINDy python package to build a data-driven model for it. The code is used for NIMROD simulations of the HIT-SI experiment and this recent paper on data-driven reduced-order modeling for plasmas: https://arxiv.org/abs/2004.10389. The code relies on the PySINDy package https:…
☆21Updated 4 years ago
Alternatives and similar repositories for POD-Galerkin_MHD
Users that are interested in POD-Galerkin_MHD are comparing it to the libraries listed below
Sorting:
- ☆28Updated last year
- Update PDEKoopman code to Tensorflow 2☆23Updated 4 years ago
- ☆54Updated 2 years ago
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆75Updated 3 weeks ago
- ☆21Updated 5 years ago
- Control of 2D Rayleigh Benard Convection using Deep Reinforcement Learning with Tensorforce and Shenfun.☆20Updated 2 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆33Updated 3 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- Python scripts to run resolution of the Reynolds-Averaged-Navier-Stokes equations over NACA 4 and 5 digits airfoils.☆24Updated 10 months ago
- ☆12Updated last week
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 years ago
- Generalized sparse regression for continuous and discrete data☆12Updated 3 weeks ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Updated 2 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution …☆23Updated 4 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- KTH-FlowAI / Towards-extraction-of-orthogonal-and-parsimonious-non-linear-modes-from-turbulent-flows☆11Updated 2 years ago
- Pseudospectral Kolmogorov Flow Solver☆41Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 4 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆24Updated last year
- Code for the paper "Generative AI for fast and accurate statistical computation of fluids"☆44Updated 3 months ago
- POD-PINN code and manuscript☆54Updated last year
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆20Updated 3 years ago
- Simple OOP Python Code to run some Pseudo-Spectral 2D Simulations of Turbulence☆69Updated 2 years ago
- Solve the advection diffusion equations looped into an optimization problem with JAX/autodiff☆12Updated 6 months ago
- Yet another PINN implementation☆20Updated last year
- XPINN code written in TensorFlow 2☆28Updated 2 years ago