Current Distribution Optimization by Using Genetic-Algorithm Based On-Off Method: Application to Pellet Injection System

IF 0.4 Q4 ENGINEERING, MULTIDISCIPLINARY Journal of Advanced Simulation in Science and Engineering Pub Date : 2020-01-01 DOI:10.15748/jasse.7.201
T. Yamaguchi, H. Ohtani, T. Takayama, A. Kamitani
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Abstract

. The current distribution in the electromagnet is optimized by using the genetic-algorithm based on-o ff method so as to maximize the acceleration performance of the Superconducting Linear Acceleration (SLA) system. In the SLA system, a pellet container is accelerated by the interaction between a shielding current density and an applied magnetic field. By using the equivalent-circuit model, the distribution of the shielding current density is approximated as a set of the multiple current loops. In contrast, the current distribution in the electromagnet is represented by means of the on-o ff method. As the method for optimizing the current distribution in the electromagnet, two types of genetic algorithms are adopted. The results of computations show that the pellet velocity for the optimized current distribution is 1.3 times as fast as that for the homogeneous current distribution.
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基于遗传算法的电流分布优化——在颗粒注射系统中的应用
. 为了使超导线性加速系统的加速性能最大化,采用基于遗传算法的开/关方法对电磁铁中的电流分布进行优化。在SLA系统中,球团容器被屏蔽电流密度和外加磁场之间的相互作用加速。利用等效电路模型,将屏蔽电流密度的分布近似为一组多电流环路。相反,电磁铁中的电流分布是用通/关方法表示的。作为优化电磁铁电流分布的方法,采用了两种遗传算法。计算结果表明,优化电流分布下的球团速度是均匀电流分布下球团速度的1.3倍。
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