Disruption prediction investigations using Machine Learning tools on DIII-D and Alcator C-Mod

• Published in: Plasma physics and controlled fusion Vol. 60; no. 8; pp. 84004 - 84016
• Main Authors: Rea, C, Granetz, R S, Montes, K, Tinguely, R A, Eidietis, N, Hanson, J M, Sammuli, B
• Format: Journal Article
• Language: English
• Published: United States IOP Publishing 18.06.2018; IOP Science
• Subjects: 70 PLASMA PHYSICS AND FUSION TECHNOLOGY; cross-device study; disruptions; Machine Learning; PARTICLE ACCELERATORS

Using data-driven methodology, we exploit the time series of relevant plasma parameters for a large set of disrupted and non-disrupted discharges to develop a classification algorithm for detecting disruptive phases in shots that eventually disrupt. Comparing the same methodology on different device...