Curated list of some open-source codes for turbulent flow simulations, including turbulent multiphase, turbulent reacting flows, turbulent convection and turbulent atmospheric physics.

Repository for an in-progress 3D, block structured, explicit/implicit, Navier-Stokes solver.

Uncertainty Quantification of RANS Data-Driven Turbulence Modeling

Computational Fluid Dynamics, Waves, Reactions, Plasmas

OpenFOAM implementation of turbulence models driven by machine learning predictions.

A Turbulent CFD solver on CPU and GPU using CUDA and Vulkan

🎲 Parameter estimation for Oceananigans using EnsembleKalmanProcesses

A toolbox for the construction and assessment of subgrid-scale models for large-eddy simulations

Using Machine Learning to Predict Extreme Events in Complex Systems

VERTEX-CFD: a multi-physics solver for fusion applications.

An extended k-epsilon model integrated with OpenFOAM for simulation of turbine wakes and power losses in wind farms

Predicting the pressure and velocity fields of a fluid using the RANS approach with Physics-Informed Neural Networks, specifically Physics Residual Adaptive Networks (PirateNET).

Density-based compressible transient solver using the flux difference splitting scheme of Bui, with shock sensor-based upwinding. Primarily designed for compressible LES.

SALSA extension of the Spalart-Allmaras turbulence model for OpenFOAM

Progressively data-augmented RANS models for secondary flow predition

Discovering explicit Reynolds-averaged turbulence closures for turbulent separated flows through deep learning-based symbolic regression with non-linear corrections

This repository contains various state-of-the-art deep learning models designed to mitigate turbulence effects in videos and images. These models enhance visual clarity and stability, making them suitable for applications in surveillance, remote sensing, and scientific imaging.

Modelling of geometry and simulation of Fluid flow using Star CCM+

Implementation of the "standard" Spalart-Allmaras turbulence model for OpenFOAM.

MATLAB code for order-of-magnitude analysis (OMA) and physics-informed symbolic regression (GPTIPS-2) to model turbulent pipe-flow friction/pressure drop using Nikuradse & Superpipe data, including custom constraints, fitness functions, and figure reproduction scripts.