Development of an interactive code for quick data analyses between STOR-M tokamak experimental plasma discharges

TL;DR

This paper presents a Python-based interactive code designed for rapid data analysis and visualization of experimental plasma discharges in the STOR-M tokamak, facilitating real-time insights during experiments.

Contribution

The paper introduces a novel Python tool for quick analysis and visualization of plasma data, enhancing real-time experimental decision-making in tokamak research.

Findings

Enables real-time visualization of magnetic surface reconstructions.

Facilitates quick analysis of probe fluctuation data during discharges.

Improves experimental efficiency in plasma studies.

Abstract

Saskatchewan Torus-Modified (STOR-M) is a small tokamak, well known for various fusion related basic experimental studies such as edge turbulent heating, different instabilities, AC (alternating current) tokamak operation, Ohmic H-mode triggering by the electrode biasing, fueling and momentum injection by Compact Torus (CT) injection, and effects of Resonance Magnetic Perturbations (RMP), among others. Some of those experiments require real time visualization of magnetic surface reconstructions either through EFIT or quick analyses and visualization of experimental data during experiments. Recently experimental studies of Geodesic Acoustic Mode (GAM) and zonal flows had been performed in STOR-M tokamak. The GAM experiments strongly require collection of fluctuations data from different Langmuir probes installed at different poloidal locations, but on the same magnetic surfaces. This is need of the adjustment of radial locations between discharges. It is therefore important to analyze and visualize the features of all probe data quickly during discharges. For this purpose, a Python code has been developed and used for quick analyze of data. This article will describe the development of the code using Python and its use in detail.