Numerical Optimization of Electromagnet Current Distribution in Superconducting Linear Acceleration System

An enhancement of the acceleration performance of a superconducting linear accelerator when injecting pellets into a helical fusion reactor has been investigated numerically. For this purpose, a numerical code using the finite element method was developed to analyze both the time evolution of a shielding current density in a high-temperature superconductor film and the dynamic motion of the film. In the present study, to optimize the shape of double magnets, a multi-objective optimization problem is solved using the non-dominated sorting genetic Algorithm-II. The results of the computations show that the optimization of the inner electromagnet is more effective in improving the pellet velocity than that of the outer electromagnet. In addition, we found that the pellet speed and energy efficiency have a trade-off relation. Therefore, it is possible to determine the preferred solution for the design of an acceleration magnet, whether focusing on the pellet speed or the energy efficiency. In other words, this relationship can be used to choose whether to emphasize velocity or efficiency in the design of SLA systems.