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:
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- ☆21Updated 4 years ago
- Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.☆75Updated 2 months ago
- Publication of Python code used to train ModalPINN☆11Updated 3 years ago
- ☆54Updated 2 years ago
- ☆28Updated last year
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆17Updated 2 years ago
- Pseudospectral Kolmogorov Flow Solver☆40Updated last year
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆18Updated 2 years ago
- Sparse Identification of Nonlinear Dynamics for Boundary Value Problems☆13Updated 4 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
- ☆12Updated this week
- Generalized sparse regression for continuous and discrete data☆12Updated 3 weeks ago
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated last year
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 4 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆22Updated 11 months ago
- Update PDEKoopman code to Tensorflow 2☆23Updated 4 years ago
- Simple OOP Python Code to run some Pseudo-Spectral 2D Simulations of Turbulence☆69Updated 2 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- Using NVIDIA modulus for airfoil optimizations at different angles.☆23Updated 2 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
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆33Updated 3 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated 2 years ago
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- Solve the 1D forced Burgers equation with high order finite elements and finite difference schemes.☆26Updated 2 years ago
- Physics Informed Sparse Identification of Nonlinear Dynamics☆11Updated 9 months ago
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆19Updated 2 years ago
- Data-driven Identification of 2D Partial Differential Equations using Extracted Physical Features☆12Updated 4 years ago