Computational and Data-Driven Fluid Dynamics

Software

Our group develops and maintains open-source software tools for computational fluid dynamics. All codes are freely available on GitHub.

MFC

Open-source multi-component, multi-phase flow solver
Fortran / OpenACC / CUDAGPU-acceleratedOpen source (MIT)

MFC is a fully documented open-source parallel simulation framework for multi-component, multi-phase, and bubbly flows. It solves the compressible multi-phase Navier–Stokes equations using high-order WENO shock-capturing schemes and supports a wide range of equations of state, surface tension models, and sub-grid bubble dynamics. MFC scales to thousands of GPU-accelerated cores on modern supercomputers (Summit, Frontier, Perlmutter) and is actively maintained by our group in collaboration with researchers at Georgia Tech and other universiites.

GitHubDocumentation
Key references
  1. Benjamin Wilfong, Henry A. Le Berre, Anand Radhakrishnan, Anish Gupta, Diego Vaca-Revelo, Dimitrios Adam, et al., “MFC 5.0: An exascale many-physics flow solver,” Computer Physics Communications, Art. No. 110055 (2026). doi:10.1016/j.cpc.2026.110055
  2. Spencer H. Bryngelson, Kevin Schmidmayer, Vedran Coralic, Jomela C. Meng, Kazuki Maeda, and Tim Colonius, “MFC: An open-source high-order multi-component, multi-phase, and multi-scale compressible flow solver,” Computer Physics Communications, vol. 266, Art. No. 107396 (2021). doi:10.1016/j.cpc.2020.107396
  3. Vedran Coralic, and Tim Colonius, “Finite-volume WENO scheme for viscous compressible multicomponent flows,” Journal of Computational Physics, vol. 274, 95-121 (2014). doi:10.1016/j.jcp.2014.06.003
  4. Eric Johnsen, and Tim Colonius, “Implementation of WENO Schemes in Compressible Multicomponent Flow Problems,” Journal of Computational Physics, vol. 219, no. 2, 715-732 (2006). doi:10.1016/j.jcp.2006.04.018

SPOD

Spectral proper orthogonal decomposition for large-scale flow data
MATLAB / PythonOpen source

Efficient MATLAB and Python implementations of spectral proper orthogonal decomposition (SPOD) for the analysis of stationary turbulent flows. The code handles large datasets via streaming algorithms and has been applied to turbulent jet, channel, and cavity flows.

GitHub
Key references
  1. Oliver T Schmidt, and Tim Colonius, “Guide to Spectral Proper Orthogonal Decomposition,” AIAA Journal, vol. 58, no. 3, 1023-1033 (2020). doi:10.2514/1.J058809
  2. Aaron Towne, Oliver T. Schmidt, and Tim Colonius, “Spectral proper orthogonal decomposition and its relationship to dynamic mode decomposition and resolvent analysis,” Journal of Fluid Mechanics, vol. 847, 821-867 (2018). doi:10.1017/jfm.2018.283

CS-SPOD

Cyclostationary spectral POD for flows with periodic statistics
MATLABOpen source (MIT)

A MATLAB implementation of cyclostationary spectral proper orthogonal decomposition (CS-SPOD), which extends SPOD to flows whose statistics vary periodically in time — such as periodically forced jets, turbomachinery, and vortex shedding. It identifies the optimal modal decomposition of these cyclostationary flows, reducing to standard SPOD in the statistically stationary limit.

GitHub
Key references
  1. Liam Heidt, Akhil Nekkanti, and Tim Colonius, “Cyclostationary analysis of forced turbulent jets,” in American Institute of Aeronautics and Astronautics, Art. No. 2023-3652 (2023). doi:10.2514/6.2023-3652

GasLab

Compressible flow teaching app — web GUI and Jupyter notebooks
Python / PyodideWeb GUI + JupyterOpen source

GasLab is an interactive tool for exploring compressible flow phenomena. It offers a web-based GUI that runs entirely in the browser with no installation (built with Panel and Pyodide, deployed via GitHub Pages), as well as Python/Jupyter notebooks for more detailed, scriptable analysis. Designed as a teaching tool for courses in gas dynamics and compressible aerodynamics.

GitHubDocumentation

IBLGF-AMR

Immersed boundary lattice Green's function solver with adaptive mesh refinement
C++17MPIOpen source (MIT)

An incompressible Navier–Stokes solver for unbounded domains using a mimetic finite-volume formulation with lattice Green's functions on adaptively refined meshes. Supports MPI parallelism, checkpoint/restart, and Docker-based builds. This repo is under construction; interfaces and documentation subject to rapid change.

GitHub
Key references
  1. Wei Hou, and Tim Colonius, “An adaptive lattice Green's function method for external flows with two unbounded and one homogeneous directions,” Journal of Computational Physics, vol. 519, Art. No. 113370 (2024). doi:10.1016/j.jcp.2024.113370
  2. K. Yu, B. Dorschner, and T. Colonius, “Multi-resolution lattice Green's function method for incompressible flows,” Journal of Computational Physics, vol. 459, Art. No. 110845 (2022). doi:10.1016/j.jcp.2021.110845
  3. Benedikt Dorschner, Ke Yu, Gianmarco Mengaldo, and Tim Colonius, “A fast multi-resolution lattice Green's function method for elliptic difference equations,” Journal of Computational Physics, vol. 407, Art. No. 109270 (2020). doi:10.1016/j.jcp.2020.109270
  4. Sebastian Liska, and Tim Colonius, “A fast immersed boundary method for external incompressible viscous flows using lattice Green's functions,” Journal of Computational Physics, vol. 331, 257-279 (2017). doi:10.1016/j.jcp.2016.11.034
  5. Sebastian Liska, and Tim Colonius, “A fast lattice Green's function method for solving viscous incompressible flows on unbounded domains,” Journal of Computational Physics, vol. 316, 360-384 (2016). doi:10.1016/j.jcp.2016.04.023
  6. Kunihiko Taira, and Tim Colonius, “The Immersed Boundary Method: A Projection Approach,” Journal of Computational Physics, vol. 225, no. 2, 2118-2137 (2007). doi:10.1016/j.jcp.2007.03.005