Real-time estimation of the safe operating region and disruption proximity in tokamaks

A novel real-time capable algorithm for identifying the safe operating region around a tokamak operating point has been developed. The region is defined by a convex set of linear constraints, from which the proximity of a point to a disruptive boundary can be calculated. The disruptivity of points is calculated from an empirical machine learning predictor that generates the likelihood of disruption. While the likelihood generated by such empirical models can be compared to a threshold to trigger a disruption mitigation system, the safe operating region calculation enables active optimization of the operating point to maintain a safe margin from disruptive boundaries. The safe operating region identification algorithm is applied to historical data from DIII-D showing the evolution of disruptive boundaries and the potential impact of optimization of the operating point. Real-time relevant execution times are achieved by parallelizing many of the calculation steps and implementing the algorithm on a graphics processing unit (GPU).