Adapting computational optimization concepts from aeronautics to nuclear fusion reactor design

Abstract

Abstract. Even on the most powerful supercomputers available today, computational nuclear fusion reactor divertor design is extremely CPU demanding, not least due to the large number of design variables and the hybrid micro-macro character of the flows. Therefore, automated design methods based on optimization can greatly assist current reactor design studies. Over the past decades, have proven their virtue in the field of aerodynamics. Applications include drag reduction for wing and wing-body configurations. Here we demonstrate that also for divertor design, these optimization methods have a large potential. Specifically, we apply the continuous adjoint method to the optimization of the divertor geometry in a 2D poloidal cross section of an axisymmetric tokamak device (as, e.g., JET and ITER), using a simplified model for the plasma edge. The design objective is to spread the target material heat load as much as possible by controlling the shape of the divertor, while maintaining the full helium ash removal capabilities of the vacuum pumping system.