gymprecice / tutorials

Active-flow-control (AFC) environments developed using the Gym-preCICE adapter.

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

License: MIT Code style: black pre-Commit Check

Gym-preCICE Tutorials

This repository contains ready-to-run tutorial cases that use the Gym-preCICE adapter. These tutorials can be used as a foundation for creating similar control cases.

To define new control cases, you need to follow a simple file structure with three key components:

new-control-problem
├── <controller-script-name>.py
├── environment.py
└── physics-simulation-engine
    ├── gymprecice-config.json
    ├── precice-config.json
    ├── solver-1
    ├── solver-2
    ├── ...
    └── solver-n
  • physics-simulation-engine: is a directory containing PDE-based solver case(s), gymprecice-config.json file for the adapter configuration, and precice-config.xml file for configuring the preCICE coupling library.
  • environment.py: is a Python script defining a class inherited from Gym-preCICE adapter to expose the underlying behaviour of the physics-simulation-engine to the controller.
  • <controller-script-name>.py: is a Python script defining the controller algorithm that interacts with the environment. This may, for instance, be the Proximal Policy Optimisation (PPO) algorithm, the Soft-Actor-Critic (SAC) algorithm, or a simple sinusoidal signal control.

To run the control case, you need to switch to the root directory of the control case, here, new-control-problem, and run

python3 -u <controller-script-name>.py

By default, the output will be saved in a directory called gymprecice-run that is located in the root directory of the control case. However, it is possible to specify a different path for the result directory via gymprecice-config.json file.

Please refer to the tutorial cases and extract the relevant sections that you require for your new control cases.

Run a tutorial

To begin running the tutorial cases, it is necessary to have gymprecice installed beforehand.

To make sure you can successfully run the tutorials, you need to install some example-specific requirements:

  • The tutorials within closed-loop directory rely on OpenFOAM CFD solvers and OpenFOAM-preCICE adapter. Please follow the instructions here to install these dependencies.

  • The tutorials within open-loop directory, in addition to OpenFOAM CFD solvers and OpenFOAM-preCICE adapter, rely on deal.II solid solvers and deal.II-preCICE adapter. Please follow the instructions here to install these dependencies.

Please check out the Quickstart to follow running a control case step by step.

Further instructions

The tutorials and gymprecice were tested on specific version of preCICE, OpenFOAM and OpenFOAM-preCICE adapter on Ubuntu 20.04.6 LTS

  • preCICE was installed using
wget https://github.com/precice/precice/releases/download/v2.5.0/libprecice2_2.5.0_focal.deb
sudo apt install ./libprecice2_2.5.0_focal.deb
  • OpenFOAM was installed using
curl https://dl.openfoam.com/add-debian-repo.sh | sudo bash
sudo apt-get install openfoam2112-default

followed by adding source /usr/lib/openfoam/openfoam2112/etc/bashrc to the .bashrc file or .zshrc

  • OpenFOAM-preCICE adapter was installed locally (without sudo) using
wget https://github.com/precice/openfoam-adapter/releases/download/v1.1.0/openfoam-adapter_v1.1.0_OpenFOAMv1812-v2112-newer.tar.gz
tar -xzvf openfoam-adapter_v1.1.0_OpenFOAMv1812-v2112-newer.tar.gz
cd openfoam-adapter_v1.1.0_OpenFOAMv1812-v2112-newer
./Allwmake
cd ..

Citing Us

If you use Gym-preCICE, please cite the following paper:

@misc{shams2023gymprecice,
      title={Gym-preCICE: Reinforcement learning environments for active flow control},
      author={Shams, Mosayeb and Elsheikh, Ahmed H},
      journal={SoftwareX},
      volume={23},
      pages={101446},
      year={2023},
      issn={2352-7110},
      doi={https://doi.org/10.1016/j.softx.2023.101446},
      eprint={https://arxiv.org/abs/2305.02033},
}

Contributing

See the contributing guidelines CONTRIBUTING.md for information on submitting issues and pull requests.

The Team

Gym-preCICE and its tutorials are primarily developed and maintained by:

  • Mosayeb Shams (@mosayebshams) - Lead Developer (Heriot-Watt University)
  • Ahmed H. Elsheikh(@ahmed-h-elsheikh) - Co-developer and Supervisor (Heriot-Watt University)

Acknowledgements

This work was supported by the Engineering and Physical Sciences Research Council grants number EP/V048899/1 and EP/Y006143/1.

License

Gym-preCICE and its tutorials are MIT licensed.

About

Active-flow-control (AFC) environments developed using the Gym-preCICE adapter.

License:MIT License


Languages

Language:C++ 99.2%Language:Python 0.7%Language:Jupyter Notebook 0.0%Language:Shell 0.0%