erdc / podrbf_nirom
Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow water equations
☆18Updated 3 years ago
Alternatives and similar repositories for podrbf_nirom:
Users that are interested in podrbf_nirom are comparing it to the libraries listed below
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆64Updated last year
- Python tools for non-intrusive reduced order modeling☆18Updated 8 months ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆29Updated last year
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆34Updated 9 years ago
- POD and DMD decomposition of data from fluid dynamics. This work has been produced during my internship at the von Karman Institute for F…☆30Updated 4 years ago
- Standardized Non-Intrusive Reduced Order Modeling☆12Updated 2 years ago
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆21Updated 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…☆22Updated last year
- POD-PINN code and manuscript☆48Updated 4 months ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆23Updated last year
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆15Updated 3 years ago
- Deep Learning for Reduced Order Modelling☆93Updated 3 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆32Updated 8 months ago
- Numerical tool for Construction of Reduced-order models for fluid flows.☆30Updated 4 years ago
- Physics-guided neural network framework for elastic plates☆36Updated 2 years ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆25Updated last year
- ☆35Updated 2 years ago
- Uncertainty Quantification of RANS Data-Driven Turbulence Modeling☆58Updated 4 years ago
- ☆18Updated last year
- DNS data of flows over periodic hills with parameterized geometries, for data-driven turbulence modeling☆35Updated last year
- Frame-independent vector-cloud neural network for nonlocal constitutive modelling on arbitrary grids.☆11Updated 3 years ago
- parallel PINNs; RANS equations; spatiotemporal parallel; PINNs☆31Updated 11 months ago
- A solver for subsonic flow around airfoils based on physics-informed neural networks and mesh transformation☆26Updated last year
- Pythonic spectral proper orthogonal decomposition☆38Updated 2 years ago
- DAFI: Ensemble based data assimilation and field inversion, repository for internal development☆54Updated last year
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆19Updated last year
- ☆18Updated 4 years ago
- Multi-fidelity reduced-order surrogate modeling☆19Updated 3 months ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆30Updated 2 years ago