Optimization of the flow distribution in a gyrotron cavity using evolutionary CFD simulations driven by a genetic algorithm

The steadily increasing performance requested to gyrotrons, to comply with their function of heating and current drive in fusion reactors, put a progressively increasing burden on the heat removal from the interaction cavity, where the heat flux can easily reach 20 MW/m2 on its inner surface. The cavity is actively cooled by subcooled water in forced flow in an annular region, and the water flow typically enters and exits through a single inlet and outlet. The high-speed flow entering from the inlet potentially drives an inhomogeneous flow azimuthally in the cavity region, but helps in locally bursting the heat removal due to the impinging effect of the cold-water flow. Here a new design of the water inlet in the cavity region is performed through a simplified genetic algorithm, in such a way that the flow homogeneity in the gyrotron cavity is maximized, without reducing the beneficial cooling due to the impact of the water jet on the cavity wall. The presence of multiple holes feeding the cavity, with their azimuthal location driven by the genetic algorithm, is analyzed through Computational Fluid Dynamics (CFD) simulations. Once the multi-inlet location is optimized, the dimension of the inlet holes is tuned to burst the heat transfer effect, reaching a high level of temperature and flow homogeneity in the cavity.