arturs-berzins / sniROMLinks
Standardized Non-Intrusive Reduced Order Modeling
☆12Updated 2 years ago
Alternatives and similar repositories for sniROM
Users that are interested in sniROM are comparing it to the libraries listed below
Sorting:
- Python code to calculate proper orthogonal decomposition modes (aka principal components), which are then used to generate reduced order …☆37Updated 10 years ago
- Source code for POD-DL-ROM: enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decom…☆32Updated last year
- Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow …☆19Updated 4 years ago
- Python tools for non-intrusive reduced order modeling☆19Updated 3 months ago
- Source code for deep learning-based reduced order models for nonlinear time-dependent parametrized PDEs. Available on doi.org/10.1007/s10…☆25Updated last year
- Deep learning framework for model reduction of dynamical systems☆21Updated 4 years ago
- Proper Orthogonal Decomposition - Radial Basis Function (POD-RBF) Network☆67Updated last year
- ☆19Updated 7 years ago
- One-dimensional unsteady compressible reacting flow simulation framework, designed for simple prototyping and testing of novel reduced-or…☆28Updated last year
- Uncertainty Quantification of RANS Data-Driven Turbulence Modeling☆60Updated 4 years ago
- POD-PINN code and manuscript☆52Updated 8 months 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
- This repository contains the simple source codes of "Machine-learning-based reduced-order modeling for unsteady flows around bluff bodies…☆16Updated 4 years ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Updated 2 years ago
- Leaning Proper Orthogonal Decomposition coefficients using Deep Neural Networks.☆10Updated 5 years ago
- Numerical tool for Construction of Reduced-order models for fluid flows.☆30Updated 4 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…☆32Updated 4 years ago
- ☆21Updated 4 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆32Updated 3 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
- Physics-informed neural networks for highly compressible flows 🧠🌊☆27Updated last year
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆26Updated 3 years ago
- Deep Learning based method to try and learn the problem of inverse Navier Stokes and model the flow for an oscillating airfoil.☆21Updated 5 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆24Updated last year
- DNS data of flows over periodic hills with parameterized geometries, for data-driven turbulence modeling☆43Updated 2 years ago
- Finite Volume PINNs for Hyperbolic Conservation Laws & Compressible Flow☆18Updated 2 years ago
- Data-driven Identification of 2D Partial Differential Equations using Extracted Physical Features☆11Updated 4 years ago
- Data-driven Reynolds stress modeling with physics-informed machine learning☆92Updated 6 years ago
- Deep Learning of Vortex Induced Vibrations☆97Updated 5 years ago
- This code implements the Tensor Basis Neural Network (TBNN) as described in Ling et al. (Journal of Fluid Mechanics, 2016).☆40Updated 7 years ago