摘要
The tokamak simulation code （TSC） is employed to simulate the complete evolution of a disruptive discharge in the experimental advanced superconducting tokamak. The multiplication factor of the anomalous transport coefficient was adjusted to model the major disruptive discharge with double-null divertor configuration based on shot 61 916. The real-time feed-back control system for the plasma displacement was employed. Modeling results of the evolution of the poloidal field coil currents, the plasma current, the major radius, the plasma configuration all show agreement with experimental measurements. Results from the simulation show that during disruption, heat flux about 8 MW m-2 flows to the upper divertor target plate and about 6 MW m-2 flows to the lower divertor target plate. Computations predict that different amounts of heat fluxes on the divertor target plate could result by adjusting the multiplication factor of the anomalous transport coefficient. This shows that TSC has high flexibility and predictability.
The tokamak simulation code （TSC） is employed to simulate the complete evolution of a disruptive discharge in the experimental advanced superconducting tokamak. The multiplication factor of the anomalous transport coefficient was adjusted to model the major disruptive discharge with double-null divertor configuration based on shot 61 916. The real-time feed-back control system for the plasma displacement was employed. Modeling results of the evolution of the poloidal field coil currents, the plasma current, the major radius, the plasma configuration all show agreement with experimental measurements. Results from the simulation show that during disruption, heat flux about 8 MW m-2 flows to the upper divertor target plate and about 6 MW m-2 flows to the lower divertor target plate. Computations predict that different amounts of heat fluxes on the divertor target plate could result by adjusting the multiplication factor of the anomalous transport coefficient. This shows that TSC has high flexibility and predictability.
基金
supported by National Natural Science Foundation of China(Grant Nos.11505290,51576208 and11575239)
the National Magnetic Confinement Fusion Science Program of China(No.2015GB102004)
