Investigation of plasma disruptions in the Compact Toroidal Hybrid (CTH) Device

Disruptions of fusion plasma pose a major challenge to realizing nuclear fusion as a source of energy. To combat this challenge, it is crucial to understand the conditions and mechanisms causing disruptions for different magnetic field configurations. The goal of this research is to investigate plasma disruptions using data from Auburn University's Compact Toroidal Hybrid (CTH) device. CTH can produce both stellarator-like and tokamak-like magnetic field configurations, which allows to investigate how three-dimensional magnetic field topology affects stability. In concert with MIT’s PSFC team, we are developing a set of routines in their disruption-Py framework adapted for use with CTH data. The goal is to process data into Machine Learning friendly formats, and use the CTH database to understand the different conditions leading to plasma disruptions. Here, we discuss implementation and development of CTH routines in disruption-Py and provide initial classification of CTH discharges using a ML model based on sparse regression.