cfl-minds / gnn_laminar_flowLinks
Laminar flow prediction using graph neural networks
☆31Updated 10 months ago
Alternatives and similar repositories for gnn_laminar_flow
Users that are interested in gnn_laminar_flow are comparing it to the libraries listed below
Sorting:
- POD-PINN code and manuscript☆56Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆33Updated 2 years ago
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆16Updated 4 years ago
- ☆44Updated 3 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆57Updated 3 years ago
- In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the Neur…☆57Updated 11 months ago
- XPINN code written in TensorFlow 2☆28Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆88Updated 4 years ago
- Frame-independent vector-cloud neural network for nonlocal constitutive modelling on arbitrary grids.☆11Updated 4 years ago
- ☆27Updated 2 years ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆33Updated last year
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆53Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆69Updated 2 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
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆87Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆27Updated 10 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆35Updated 2 years ago
- Multi-head attention network for airfoil flow field prediction☆16Updated 3 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆43Updated 2 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆36Updated 3 years ago
- Physics-guided neural network framework for elastic plates☆48Updated 3 years ago
- ☆54Updated 3 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆26Updated last year
- Generative Adversarial Networks are used to super resolve turbulent flow fields from low resolution (RANS/LES) fields to high resolution …☆23Updated 4 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆93Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated 3 weeks ago
- Multi-fidelity reduced-order surrogate modeling☆28Updated 5 months ago