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https://github.com/rahulgaur104/ideal-ballooning-solver

A simple eigenvalue solver + optimizer to calculate and reduce the growth rate of a pressure-driven instability in fusion devices
https://github.com/rahulgaur104/ideal-ballooning-solver

optimization-problem plasma-physics stability-analysis

Last synced: about 1 month ago
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A simple eigenvalue solver + optimizer to calculate and reduce the growth rate of a pressure-driven instability in fusion devices

Host: GitHub
URL: https://github.com/rahulgaur104/ideal-ballooning-solver
Owner: rahulgaur104
Created: 2022-08-10T17:15:07.000Z (over 2 years ago)
Default Branch: master
Last Pushed: 2023-12-02T22:28:56.000Z (about 1 year ago)
Last Synced: 2023-12-02T23:24:49.598Z (about 1 year ago)
Topics: optimization-problem, plasma-physics, stability-analysis
Language: Python
Homepage:
Size: 6.72 MB
Stars: 2
Watchers: 1
Forks: 0
Open Issues: 1
Metadata Files:
- Readme: README.md
- Citation: CITATION.cff

Awesome Lists containing this project

README

# ballopt: stellarator and tokamak stability optimizer

[![DOI](https://zenodo.org/badge/523432429.svg)](https://zenodo.org/badge/latestdoi/523432429)

This repository contains a set of Python scripts that, along with the SIMSOPT package can optimize or evaluate a tokamak or stellarator equilibrium against the infinite-n, ideal ballooning mode using an adjoint-based method.

The details of implementation of this method and the results are available in the paper [An adjoint-based method to optimize MHD equilibria against the infinite-n ideal ballooning mode](https://doi.org/10.1017/S0022377823000995)

## Dependencies

This optimizer is designed to run a cluster or supercomputer that uses SLURM. To run ballopt, you also need a Python version >= 3.8 and either

* a [SIMSOPT singularity image\_v0.13](https://simsopt.readthedocs.io/en/latest/containers.html#singularity-container) to run this optimizer
* or SIMSOPT Python environment and the VMEC2000 code from the [SIMSOPT GitHub page](https://github.com/hiddenSymmetries/simsopt) and make three one-line changes to the Simsopt\_submit.py (uncomment line 39) and ball\_submit.py (line 57) and slurm\_x0.sl (line 11) files.

## Instructions to reproduce the results in the adjoint-ballooning paper

The input files for the equilibria studied in the paper above are presented in this repository. You should be able to optimize any of the three equilibria with the following equilibrium names:

0. D3D
1. NCSX
2. HBERG

Depending on which equilibrium you want to optimize, run

python3 sims\_runner\_\.py

from your login node. After each iteration, the data are saved in the directory save\_n\_load.

Please do not hesitate to contact me at [email protected] if you need any help running or understanding this optimizer.

## Relevant papers
* [An adjoint-based method to optimize MHD equilibria against the infinite-n ideal ballooning mode](https://arxiv.org/abs/2302.07673)
* [SIMSOPT: A flexible framework for stellarator optimization](https://joss.theoj.org/papers/10.21105/joss.03525)
* [COBRA: An Optimized Code for Fast Analysis of Ideal Ballooning Stability of Three-Dimensional Magnetic Equilibria](https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.596.1387&rep=rep1&type=pdf)