https://github.com/djeada/computational-fluid-dynamics-cfd-resources
This repository is a comprehensive collection of advanced resources for Computational Fluid Dynamics (CFD). It includes in-depth notes, specialized scripts, and detailed tutorials covering various CFD tools like ParaView, Gmsh, and more. Aimed at both beginners and experienced practitioners, it serves as a platform for learning and exploration.
https://github.com/djeada/computational-fluid-dynamics-cfd-resources
Last synced: about 1 year ago
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This repository is a comprehensive collection of advanced resources for Computational Fluid Dynamics (CFD). It includes in-depth notes, specialized scripts, and detailed tutorials covering various CFD tools like ParaView, Gmsh, and more. Aimed at both beginners and experienced practitioners, it serves as a platform for learning and exploration.
- Host: GitHub
- URL: https://github.com/djeada/computational-fluid-dynamics-cfd-resources
- Owner: djeada
- License: mit
- Created: 2021-06-14T20:28:10.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2025-04-06T07:43:02.000Z (about 1 year ago)
- Last Synced: 2025-04-06T08:28:22.664Z (about 1 year ago)
- Language: Python
- Homepage:
- Size: 769 KB
- Stars: 7
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Computational Fluid Dynamics (CFD) Resources
This repo is a work in progress aimed at gathering useful open-source resources for CFD engineers in one place. It includes notes, scripts, and tutorials for tools like ParaView, Gmsh, and more. The idea is to make it easier to find and use solid, practical materials without digging through scattered sources.
## Features
- Detailed explanations of complex CFD topics, including turbulence modeling, mesh generation, and solver algorithms.
- Custom scripts to streamline CFD workflows, including pre-processing, simulation, and post-processing tasks.
- Step-by-step guides on using ParaView for data visualization, Gmsh for mesh generation, and other CFD tools.
Navigate to the respective folders for detailed READMEs on how to use the materials.
## How to Contribute
Got something useful to share? Found a mistake or a better way to do something? Contributions of all kinds are welcome—whether it’s fixing a typo, adding a script, or sharing your own CFD tips.
Here’s how to get started:
1. Fork this repo.
2. Create a new branch (`git checkout -b feature/YourAwesomeThing`).
3. Make your changes and commit them (`git commit -m 'Add YourAwesomeThing'`).
4. Push to your fork (`git push origin feature/YourAwesomeThing`).
5. Open a Pull Request—we'll take it from there.
Thanks for helping make this a better resource for the CFD community!
## License
This project is licensed under the [MIT License](LICENSE) - see the LICENSE file for details.
## References
### General Resources
- [DepositOnce - TU Berlin](https://depositonce.tu-berlin.de/)
- [CFD Python: 12 Steps to Navier-Stokes by Lorena Barba](https://lorenabarba.com/blog/cfd-python-12-steps-to-navier-stokes/)
- [National Committee for Fluid Mechanics Series on YouTube](https://youtube.com/playlist?list=PL0EC6527BE871ABA3)
- [The Art and Science of Meshing Airfoils](https://blog.gridpro.com/the-art-and-science-of-meshing-airfoils/)
- [Open Source CFD Course at Chalmers University](http://www.tfd.chalmers.se/~hani/kurser/OS_CFD/)
- [CFD General Principles by CFD Direct](https://doc.cfd.direct/notes/cfd-general-principles/)
- [Turbulence Modeling Resource](https://turbmodels.larc.nasa.gov/)
- [Wall-Modeled Large Eddy Simulation Resource](https://wmles.umd.edu/)
- [Airfoil Tools - Airfoil Design Database and Analysis Tool](http://www.airfoiltools.com/)
### Books
- **Anderson, John D.**
*Computational Fluid Dynamics: The Basics with Applications*
[Amazon Link](https://amzn.to/42iuJNV)
- **Versteeg, H. K.; Malalasekera, W.**
*An Introduction to Computational Fluid Dynamics: The Finite Volume Method*
[Amazon Link](https://amzn.to/3EbEMfG)
- **Ferziger, Joel H.; Peric, Milovan; Street, Robert L.**
*Computational Methods for Fluid Dynamics*
[Amazon Link](https://amzn.to/3FSZ9iq)
- **Patankar, Suhas V.**
*Numerical Heat Transfer and Fluid Flow*
[Amazon Link](https://amzn.to/42qd0o1)
- **Blazek, J.**
*Computational Fluid Dynamics: Principles and Applications*
[Amazon Link](https://amzn.to/4j7adqY)
- **Kutz, J. Nathan**
*Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control*
[Amazon Link](https://amzn.to/3RHJncw)
- **Brunton, Steven L.; Noack, Bernd R.**
*Machine Learning Control – Taming Nonlinear Dynamics and Turbulence*
[Amazon Link](https://amzn.to/4jeggJC)
- **Machine Learning for Fluid Dynamics**
*An overview of applying machine learning techniques to fluid dynamics*
[View Paper](https://arxiv.org/abs/1905.11075)
- **Machine Learning-Based CFD Simulations: A Review, Models, Open Threats, and Future Tactics**
*A comprehensive review of machine learning approaches in CFD simulations*
[View Article](https://link.springer.com/article/10.1007/s00521-022-07838-6)
### Academic Papers
- [Physics-Informed Neural Networks: A Deep Learning Framework for Solving Forward and Inverse Problems Involving Nonlinear Partial Differential Equations](https://www.brown.edu/research/projects/crunch/sites/brown.edu.research.projects.crunch/files/uploads/Physics-informed%20neural%20networks_A%20deep%20learning%20framwork%20fir%20solving%20forward%20and%20inverse%20probelms%20involving%20nonlinear%20partial%20differential%20equations.pdf)
- [Nature Reviews - GK](https://www.brown.edu/research/projects/crunch/sites/brown.edu.research.projects.crunch/files/uploads/Nature-REviews_GK.pdf)
- [CFD of the Future: Year 2025 and Beyond](https://www.researchgate.net/publication/339808378_CFD_of_the_Future_Year_2025_and_Beyond)
- [Machine Learning in CFD](https://www.tandfonline.com/doi/full/10.1080/10618562.2023.2175788)
### Code Repositories and Projects
- [NVIDIA Modulus Airfoil Optimization - Dr. Yang's LDC 2D](https://github.com/neo-fetch/nvidia-modulus-airfoil-optimisation/blob/master/Dr-Yang_ldc_2d.py)
- [Scientific Computing by Chasnov: Computational Fluid Dynamics](https://math.libretexts.org/Bookshelves/Scientific_Computing_Simulations_and_Modeling/Scientific_Computing_(Chasnov)/III%3A_Computational_Fluid_Dynamics/14%3A_The_Governing_Equations)
- [Machine Learning and Simulation by Ceyron](https://github.com/Ceyron/machine-learning-and-simulation)
- [Introductory Finite Elements - FEM Notes and Code](https://github.com/AppliedMechanics-EAFIT/Introductory-Finite-Elements)
- [Dolfin X FEM Tutorial](https://jsdokken.com/dolfinx-tutorial/fem.html)
- [David Penner's Interesting Projects](https://davidpenner74.wixsite.com/davidpenner/projects)
### Video Tutorials
- [MIT Lecture on CFD](https://www.youtube.com/@AeroCFD)
- [Numerical Methods by Hand on YouTube](https://youtube.com/playlist?list=PL5_Bm_WH1i3fAQP6G2_SaazjNIy3m8QbH&si=QrtwsLAQpWKeQKA8)
- [Computational Fluid Dynamics (CFD) - ME615 IIT Mandi](https://youtube.com/playlist?list=PLOUcBDsCNnMweTuft1qq25CQbyyKqZKvI&si=prjJr4J0GVZFWgLa)
- [Data-driven Methods for Science and Engineering Seminar](https://youtube.com/playlist?list=PLWL3MaEZQ5I0x5SoN-whc6wfxvZr4E5v9&si=sj8mXSdq_FynCsUz)
- [Many CFD and Numerical Analysis Lectures by Qiqi Wang](https://www.youtube.com/c/QiqiWangGG)
- [Gentle Introduction to Various Fluid Concepts](https://www.youtube.com/watch?v=zGuVWSKBc4Y&list=PLyYlZ2ZyWpnh6Xy8xsqIFQKPiMzVkUkdG)
- [Various Mechanics Problems Solved by Hand](https://youtube.com/playlist?list=PL7FF084F8C414D602&si=WVUmaxodRYiBP6ue)
- [More Problems Solved by Hand by Postcard Professor](https://www.youtube.com/c/PostcardProfessor/playlists)
- [Other Problems Solved by Hand](https://www.youtube.com/watch?v=PPt_FfoUqBQ&list=PLD45F0FD958B864AD)
- [Various Topics from Theoretical Mechanics and Numerical Methods](https://www.youtube.com/channel/UCcqQi9LT0ETkRoUu8eYaEkg)
- [The Perić Lectures on CFD](https://youtu.be/8a0j2DQiTVQ?si=UX6ThBBVHhmAX6qD)