2026 Theses Doctoral

Avoidance and Mitigation of Disruptions due to Vertical Displacement Events in Tokamaks via Novel Real-Time Stability Assessment

Tobin, Matthew

Vertical stability in tokamak plasmas has long been studied through physics modeling and plasma control innovation, but vertical displacement events (VDEs) involving loss of vertical control and plasma disruption remain a major concern for future power-plant-scale tokamak devices. This thesis aims to evaluate and develop methods for forecasting loss of vertical control, demonstrate plasma control actuator response strategies for avoiding VDEs when vertical stability is marginal, and produce methods for detecting when vertical control is lost as early as possible to allow mitigation of VDE-related disruptions. For all of these goals, high accuracy, robustness, and real-time compatibility are essential criteria.

To this end, existing methods for achieving these aims are reviewed and built upon to develop novel approaches, including a new metric for vertical stability designed for real-time application (the vertical force gradient metric). This development involves innovations improving real-time compatibility of calculating requisite quantities, including the two-dimensional toroidal current density profile, the vertical force balance on the plasma, and the vertical instability growth rate. It also requires new strategies for connecting model- and simulation-based analyses to data from current, and future, physical devices, including a hybrid analytical and data-driven framework, adaptive procedures for detection and forecasting threshold determination, and fast calculation or approximation of germane physical quantities.

To demonstrate robustness and in order to build confidence in extrapolability to future devices, the developed methods are applied to historical data (thousands of shots across entire campaign years) to three tokamaks of varying aspect ratios, scales, and control capabilities: KSTAR, MAST-U, and NSTX. The developed forecasting and detection approaches are also implemented on two of these devices and used for VDE avoidance and mitigation in several scenarios. This work thus demonstrates a path to alleviating VDEs applicable to current and future tokamaks through high-accuracy, physics-based and hybrid data-driven forecasting and detection as well as reliable avoidance and mitigation.