Catch stands for C++ Automated Test Cases in Headers and is a multi-paradigm automated test framework for C++ and Objective-C (and, maybe, C). It is implemented entirely in a set of header files, but
pybind11 is a lightweight header-only library that exposes C++ types in Python and vice versa, mainly to create Python bindings of existing C++ code.
SmartSim is a workflow library that makes it easier to use common Machine Learning (ML) libraries, like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and applications.
SmartRedis is a collection of Redis clients that support RedisAI capabilities and include additional features for high performance computing (HPC) applications.
This project aims at implementing the k-epsilon Lag Elliptic Blending turbulent model for OpenFOAM.
The SST-CND model is based on Menter's Shear-stress-transport model with a correction term for separated flow (especially separated shear layer) derived by machine learning method.
Progressive data-augmented k-omega SST model as proposed by Amarloo and Rincón (2023) for OpenFOAM. Developed by Fluid Physics & Turbulence research group at Aarhus University.
Sub-module for OpenFOAM that provides a solver for embedding SmartSim and its external dependencies (i.e. SmartRedis) into arbitrary OpenFOAM simulations.
ADflow is a flow solver developed by the MDO Lab at the University of Michigan. It solves the compressible Euler, laminar Navier–Stokes and Reynolds-averaged Navier–Stokes equations using structured multi-block and overset meshes.
JAX-CFD is an experimental research project for exploring the potential of machine learning, automatic differentiation and hardware accelerators (GPU/TPU) for computational fluid dynamics.
