jcallaham / robust-flow-reconstruction
Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 2018)
☆14Updated 6 years ago
Alternatives and similar repositories for robust-flow-reconstruction:
Users that are interested in robust-flow-reconstruction are comparing it to the libraries listed below
- ☆12Updated 11 months ago
- Discontinuity Computing Using Physics-Informed Neural Network☆23Updated 11 months ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆23Updated last year
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆26Updated last year
- machine learning-accelerated computational fluid dynamics☆18Updated 3 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
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆24Updated last year
- POD-PINN code and manuscript☆49Updated 4 months ago
- The MegaFlow2D dataset package☆19Updated last year
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆29Updated last year
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆48Updated 2 months ago
- ☆26Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆13Updated 10 months ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆18Updated 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 last year
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆18Updated 2 years ago
- Python scripts to run resolution of the Reynolds-Averaged-Navier-Stokes equations over NACA 4 and 5 digits airfoils.☆22Updated 2 months ago
- Frame-independent vector-cloud neural network for nonlocal constitutive modelling on arbitrary grids.☆11Updated 3 years ago
- ☆9Updated last year
- This repository contains the simple source codes of "Convolutional neural network and long short-term memory based reduced order surrogat…☆13Updated 4 years ago
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆15Updated 3 years ago
- ☆12Updated last week
- Data preprocess method on Physics-informed neural networks☆13Updated last month
- Accelerating Physics Informed Neural Networks (PINNs) using Meshless Discretizations☆25Updated last year
- Variational Neural Networks for the Solution of Partial Differential Equations☆8Updated 5 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆35Updated 9 months ago
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- ☆28Updated 2 years ago
- ☆19Updated 4 years ago