Halo current rotation scaling in post-disruption plasmas

Halo current (HC) rotation during disruptions can be potentially dangerous if resonant with the structures surrounding a tokamak plasma. We propose a drift-frequency-based scaling law for the rotation frequency of the asymmetric component of the HC as a function of toroidal field strength and plasma minor radius (frot ∝ 1/BT a2 ). This scaling law is consistent with results reported for many tokamaks and is motivated by the faster HC rotation observed in the HBT-EP tokamak. Projection of the rotation frequency to ITER and SPARC parameters suggest the asymmetric HC rotation will be on the order of 10 Hz and 60 Hz, respectively.

A methodological approach for the optimal design of the toroidal field coils of a Tokamak device using artificial intelligence

As prototypes of future commercial Tokamaks, DEMOs nuclear fusion power plants are expected to be able to produce cost-effective electrical power. In this view, an optimized design becomes crucial in the whole engineering workflow. Up to now, the design of one of the most critical components, the cross-section of each of the toroidal field coils inner leg winding pack, was performed using a sequential trial-and-error procedure. In this work, a novel comprehensive approach is proposed to include all the main design aspects into a unified tool taking advantage of Artificial Neural Networks (ANNs) for faster computation in finding optimal design configurations. This procedure overcomes several difficulties including dealing with both real-valued and discrete design variables, the significant CPU-time of magneto-structural analysis and also guarantees the optimality for the winding pack configuration. The proposed methodology was demonstrated for the 2019 ENEA DEMO configuration which includes 16 toroidal field coils, made-up of 6 3 double layers and a Wind & React manufacturing technique.