Stars
Official repository for the interface reconstruction library (IRL)
Parallel solvers for sparse linear systems featuring multigrid methods.
Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" by S. A. McQuarrie, C. Huang, and K. E. Willcox.
Thermodynamics and Phase Equilibrium component of Chemical Engineering Design Library (ChEDL)
A general-purpose Python package for Koopman theory using deep learning.
Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-based symbolic regression.
A package for the sparse identification of nonlinear dynamical systems from data
Unstructured Compressible Navier Stokes 3D code (UCNS3D)
A collection of physics databases and implementation code for use with the Pele suite of of codes
Castro (Compressible Astrophysics): An adaptive mesh, astrophysical compressible (radiation-, magneto-) hydrodynamics simulation code for massively parallel CPU and GPU architectures.
A CFD open source code dedicated to multiphase compressible flows
The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control
A Python-embedded modeling language for convex optimization problems.
A pseudo-spectral collocation based multi-phase Optimal control problem solver
Trajectory Optimization Motion Planner for ROS
An interactive book about the Riemann problem for hyperbolic PDEs, using Jupyter notebooks.
WARNING: DEVELOPMENT HAS MOVED TO https://github.com/hopr-framework/hopr/!
A package for computing data-driven approximations to the Koopman operator.
Soure code for Deep Koopman with Control
neural networks to learn Koopman eigenfunctions
A library for Koopman Neural Operator with Pytorch.
ExaDG - High-Order Discontinuous Galerkin for the Exa-Scale
One-dimensional unsteady compressible reacting flow simulation framework, designed for simple prototyping and testing of novel reduced-order model methods.
Operator Inference for data-driven, non-intrusive model reduction of dynamical systems.