Tokamak Disruption Event Characterization and Forecasting Research and Expansion to Real-Time Application in KSTAR *

Disruption prediction and avoidance is critical for ITER and reactor-scale tokamaks to maintain steady plasma operation and to avoid device damage. Physics-based disruption event characterization and forecasting (DECAF) provides early disruption forecasts (on transport timescales) that can be used for disruption avoidance through means such as profile control. In KSTAR, significant new hardware and software for real-time data acquisition and analysis are being installed including magnetics, plasma velocity and T_e profiles, 2D internal T_e fluctuations, and magnetic pitch angle. Real-time data has been taken for the first four with excellent agreement with offline data. DECAF analysis results are shown for multiple tokamaks including KSTAR, MAST, NSTX, and AUG. An NTM locked mode forecaster in DECAF using a torque balance model has been developed for off-line and real-time use. A new ELM event module includes the ability to distinguish local and global MHD. Supporting research includes pre-programmed ECCD used to reduce triggerless 2/1 mode amplitudes by ~80% the triggered mode amplitudes by 30%. TRANSP predict-first analysis show plasmas at β_N > 3.5 with 100% non-inductive current drive. Ideal and resistive stability analyses using kinetic equilibrium reconstructions with MSE show sensitivity to local q and low shear regions. *US DOE grants DE-SC0020415, DE-SC0018623.