Black-box optimization of massive material injection for disruption mitigation

An effective disruption mitigation system in a tokamak reactor should limit the exposure of the wall to localized heat losses and to the impact of high current runaway electron beams, and avoid excessive forces on the structure. Massive material injection (MMI) as a disruption mitigation scheme is characterized by a large number of parameters, such as when to inject material, in what form and composition, representing a multidimensional optimization problem. We have developed a numerical optimization framework and applied it on simulated disruptions with MMI, representative of ITER. The simulations use the disruption runaway modeling tool DREAM [M Hoppe et al 2021 CPC 268, 108098]. The optimization takes into account the maximum runaway current, the transported fraction of the heat loss and limits on the current quench timescale. With the material deposition profiles fixed, only at lower magnetic fluctuation levels during thermal quench do we find acceptable parameter regimes, while if the injected profiles are also part of the optimization, acceptable optima may be found for a larger range of magnetic perturbations. The global view of the objective function provided by the Bayesian approach is utilized to assess the robustness of the optima.