Progress on Disruption Event Characterization and Forecasting in Tokamaks and Supporting Physics Analysis
Disruption prediction and avoidance is critical in ITER and reactor-scale tokamaks to maintain steady plasma operation and to avoid damage to device components. The present status and results from the physics-based disruption event characterization and forecasting (DECAF) research effort are shown for multiple tokamak devices. Present analysis of KSTAR, MAST, and NSTX databases shows low disruptivity paths to high beta operation. The DECAF code applied to a database of ~104 plasmas with only 5 DECAF events predicts disruptions with 91.2% true positives and 8.7% false negatives. Increasing the number of events will improve the latter value. Automated analysis of rotating magnetohydrodynamic (MHD) modes now allows the identification of disruption event chains for several devices including coupling, bifurcation, locking, and potential triggering by other MHD activity. DECAF can now provide an early disruption forecast (on transport timescales) allowing the potential for disruption avoidance through profile control. Hardware to allow real-time evaluation of this activity on KSTAR is now being configured for installation in 2019.