論文

2021年

Multi-Objective Optimization of Superconducting Linear Acceleration System for Pellet Injection by Using Finite Element Method

Plasma and Fusion Research
  • TAKAYAMA Teruou
  • ,
  • YAMAGUCHI Takazumi
  • ,
  • SAITOH Ayumu
  • ,
  • KAMITANI Atsushi
  • ,
  • NAKAMURA Hiroaki

16
開始ページ
2401025
終了ページ
2401025
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1585/pfr.16.2401025
出版者・発行元
一般社団法人 プラズマ・核融合学会

<p>The enhancement of the acceleration performance of a superconducting linear acceleration (SLA) system to inject the pellet container has been investigated numerically. To this end, a numerical code used in the finite element method has been developed for analyzing the shielding current density in a high-temperature superconducting film. In addition, the on/off method and the normalized Gaussian network (NGnet) method have been implemented in the code for the shape optimization of an acceleration coil, and the non-dominated sorting genetic algorithms-II have been used as the optimization method. The results of the computations show that the speed of the pellet container for the current profile of the optimized coil is significantly faster than that for the homogeneous current profile of the coil. However, for the on/off method, the current profile is scattered, whereas the coil shape becomes hollow for the NGnet method. Consequently, the NGnet method is an effective tool for improving the acceleration performance of the SLA system and for obtaining a coil shape that is easy to design.</p>

リンク情報
DOI
https://doi.org/10.1585/pfr.16.2401025
CiNii Articles
http://ci.nii.ac.jp/naid/130008000730
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000672705100004&DestApp=WOS_CPL
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104738276&origin=inward 本文へのリンクあり
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85104738276&origin=inward
ID情報
  • DOI : 10.1585/pfr.16.2401025
  • ISSN : 1880-6821
  • eISSN : 1880-6821
  • CiNii Articles ID : 130008000730
  • ORCIDのPut Code : 136553460
  • SCOPUS ID : 85104738276
  • Web of Science ID : WOS:000672705100004

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