erdc / pynirom
Python tools for non-intrusive reduced order modeling
☆18Updated 8 months ago
Alternatives and similar repositories for pynirom:
Users that are interested in pynirom are comparing it to the libraries listed below
- Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow …☆18Updated 3 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
- 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
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- POD-PINN code and manuscript☆48Updated 4 months ago
- Standardized Non-Intrusive Reduced Order Modeling☆12Updated 2 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆64Updated 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
- Multi-fidelity reduced-order surrogate modeling☆19Updated 3 months ago
- This is the source code for our paper "Towards high-accuracy deep learning inference of compressible turbulent flows over aerofoils"☆29Updated last year
- XPINN code written in TensorFlow 2☆27Updated 2 years ago
- ☆35Updated 2 years ago
- Theory-guided physics-informed neural networks for boundary layer problems with singular perturbation☆15Updated 2 years ago
- Physics-guided neural network framework for elastic plates☆36Updated 2 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
- ☆18Updated last year
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆25Updated 3 years ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆25Updated last year
- Deep Learning for Reduced Order Modelling☆93Updated 3 years ago
- Tensoflow 2 implementation of physics informed deep learning.☆27Updated 4 years ago
- Numerical tool for Construction of Reduced-order models for fluid flows.☆30Updated 4 years ago
- Data-driven Identification of 2D Partial Differential Equations using Extracted Physical Features☆11Updated 3 years ago
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆21Updated 4 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆23Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆22Updated 2 months ago
- ITHACA-SEM - In real Time Highly Advanced Computational Applications for Spectral Element Methods☆19Updated 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☆23Updated 11 months ago
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆32Updated 8 months ago