https://github.com/abaillod/csx_combined_optimization

Single stage optimization approach of the Columbia Stellarator eXperiment
https://github.com/abaillod/csx_combined_optimization

coils optimization stellarator

Last synced: about 1 month ago
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Single stage optimization approach of the Columbia Stellarator eXperiment

• Host: GitHub
• URL: https://github.com/abaillod/csx_combined_optimization
• Owner: abaillod
• Created: 2023-10-18T17:11:42.000Z (about 1 year ago)
• Default Branch: master
• Last Pushed: 2024-07-29T15:41:15.000Z (5 months ago)
• Last Synced: 2024-07-29T21:12:39.951Z (5 months ago)
• Topics: coils, optimization, stellarator
• Language: Python
• Homepage:
• Size: 43.4 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# CSX combined optimization

This repository uses the [simsopt framework](https://github.com/hiddenSymmetries/simsopt) and the combined approach technique described by [R. Jorge et.al.](https://iopscience.iop.org/article/10.1088/1361-6587/acd957) 

to optimize tentative designs of the Columbia Stellarator eXperiment (CSX), which will eventually replace the existing [Columbia Nonneutral Torus (CNT)](http://sites.apam.columbia.edu/CNT/index.htm)

![bestview](https://github.com/abaillod/csx_combined_optimization/assets/45510759/74bc1225-0b45-42d6-8d0c-3010ae5ad3cc)

## Dependencies

 * simsopt, windowpane branch. commit ec271a44ca557efa9428dad39e994f883338e8b6

 * pystellplot. commit a37cbcd70cd37605f7c0c4d553337a7c09f40f72

 * everything in requirements.txt

## Installation

First, install simsopt and VMEC2000. You might also need to create a `runs` directory manually, by running

```

mkdir runs

```

## Running the code

The main script is `combined_csx_optimization.py`. It can be run locally by creating an input file in the `./inputs` directory - just copy-paste the `inputs/standard_input.py` file into a new

file, and set each input to the value you desire. Then, run the code locally (not recommended) with:

```

python combined_csx_optimization_with_windowpane_coils.py --input /path/to/input

```

To run the code on the Ginsburg cluster, simply use the sbatch script `run_combined_approach.sb` and do

```

sbatch run_combined_approach.sb

```

## Analysing the output

Outputs can be analyzed interactively using the `plot_combined_approach_results.ipynb` jupyter notebook, or all relevant figures can be generated by running 

```

python run_analysis.py /path/to/output/directory

```