Electromagnetic design of MRI superconducting magnet based on novel hybrid optimization methods

IF 1.3 3区 物理与天体物理 Q4 PHYSICS, APPLIED
Yunhao Mei , Qingyun Liu , Huiyu Du , Yufu Zhou , Zhengrong Liu , Lei Mo , Bensheng Qiu , Qing Zhang
{"title":"Electromagnetic design of MRI superconducting magnet based on novel hybrid optimization methods","authors":"Yunhao Mei ,&nbsp;Qingyun Liu ,&nbsp;Huiyu Du ,&nbsp;Yufu Zhou ,&nbsp;Zhengrong Liu ,&nbsp;Lei Mo ,&nbsp;Bensheng Qiu ,&nbsp;Qing Zhang","doi":"10.1016/j.physc.2023.1354425","DOIUrl":null,"url":null,"abstract":"<div><p>This paper proposes a novel hybrid optimization algorithm that combines linear programming (LP), genetic algorithm (GA), and nonlinear programming (NLP) to achieve the optimal design of highly homogeneous superconducting magnets for MRI systems. Initially, the predetermined rectangular region is divided into an array of superconductor coils. Then, linear programming is utilized to minimize the consumption of superconducting conductors as the objective function and to obtain the nonzero current regions by considering the field peak-to-peak uniformity in the diameter of the spherical volume (DSV) and the range of the 5 Gauss stray field as constraints. Subsequently, the genetic algorithm is employed to convert the nonzero current regions into coils with rectangular cross-sections. Finally, the NLP is applied to adjust the position of each coil to obtain the magnet criteria. An illustrative example is provided: an actively shielded MRI superconducting magnet with a center field strength of 1.5 T. The effectiveness of this optimization method is demonstrated through the design, electromagnetic analysis, and stress analysis conducted on this example.</p></div>","PeriodicalId":20159,"journal":{"name":"Physica C-superconductivity and Its Applications","volume":"617 ","pages":"Article 1354425"},"PeriodicalIF":1.3000,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physica C-superconductivity and Its Applications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921453423002162","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSICS, APPLIED","Score":null,"Total":0}
引用次数: 0

Abstract

This paper proposes a novel hybrid optimization algorithm that combines linear programming (LP), genetic algorithm (GA), and nonlinear programming (NLP) to achieve the optimal design of highly homogeneous superconducting magnets for MRI systems. Initially, the predetermined rectangular region is divided into an array of superconductor coils. Then, linear programming is utilized to minimize the consumption of superconducting conductors as the objective function and to obtain the nonzero current regions by considering the field peak-to-peak uniformity in the diameter of the spherical volume (DSV) and the range of the 5 Gauss stray field as constraints. Subsequently, the genetic algorithm is employed to convert the nonzero current regions into coils with rectangular cross-sections. Finally, the NLP is applied to adjust the position of each coil to obtain the magnet criteria. An illustrative example is provided: an actively shielded MRI superconducting magnet with a center field strength of 1.5 T. The effectiveness of this optimization method is demonstrated through the design, electromagnetic analysis, and stress analysis conducted on this example.

基于新型混合优化方法的磁共振成像超导磁体电磁设计
本文提出了一种结合线性规划(LP)、遗传算法(GA)和非线性规划(NLP)的新型混合优化算法,以实现磁共振成像系统中高度均匀超导磁体的优化设计。首先,将预定的矩形区域划分为超导线圈阵列。然后,利用线性规划将超导导体的消耗量最小化作为目标函数,并将球形体积直径(DSV)中的磁场峰峰值均匀性和 5 高斯杂散磁场的范围作为约束条件,从而获得非零电流区域。随后,采用遗传算法将非零电流区域转换为矩形截面的线圈。最后,应用 NLP 调整每个线圈的位置,以获得磁体标准。本文提供了一个示例:中心场强为 1.5 T 的主动屏蔽磁共振成像超导磁体。通过对该示例进行设计、电磁分析和应力分析,证明了该优化方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
2.70
自引率
11.80%
发文量
102
审稿时长
66 days
期刊介绍: Physica C (Superconductivity and its Applications) publishes peer-reviewed papers on novel developments in the field of superconductivity. Topics include discovery of new superconducting materials and elucidation of their mechanisms, physics of vortex matter, enhancement of critical properties of superconductors, identification of novel properties and processing methods that improve their performance and promote new routes to applications of superconductivity. The main goal of the journal is to publish: 1. Papers that substantially increase the understanding of the fundamental aspects and mechanisms of superconductivity and vortex matter through theoretical and experimental methods. 2. Papers that report on novel physical properties and processing of materials that substantially enhance their critical performance. 3. Papers that promote new or improved routes to applications of superconductivity and/or superconducting materials, and proof-of-concept novel proto-type superconducting devices. The editors of the journal will select papers that are well written and based on thorough research that provide truly novel insights.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信