A Systematic Approach to Adaptive Mesh Refinement for Computational Electrodynamics

IF 1.5 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal on Multiscale and Multiphysics Computational Techniques Pub Date : 2023-01-03 DOI:10.1109/JMMCT.2022.3233944
Dinshaw S. Balsara;Costas D. Sarris
{"title":"A Systematic Approach to Adaptive Mesh Refinement for Computational Electrodynamics","authors":"Dinshaw S. Balsara;Costas D. Sarris","doi":"10.1109/JMMCT.2022.3233944","DOIUrl":null,"url":null,"abstract":"There is a great need to solve CED problems on adaptive meshes; referred to here as AMR-CED. The problem was deemed to be susceptible to “long-term instability” and parameterized methods have been used to control the instability. In this paper, we present a new class of AMR-CED methods that are free of this instability because they are based on a more careful understanding of the constraints in Maxwell's equations and their preservation on a single control volume. The important building blocks of these new methods are: 1) Timestep sub-cycling of finer child meshes relative to parent meshes. 2) Restriction of fine mesh facial data to coarser meshes when the two meshes are synchronized in time. 3) Divergence constraint-preserving prolongation of the coarse mesh solution to newly built fine meshes or to the ghost zones of pre-existing fine meshes. 4) Electric and magnetic field intensity-correction strategy at fine-coarse interfaces. Using examples, we show that the resulting AMR-CED algorithm is free of “long-term instability”. Unlike previous methods, there are no adjustable parameters. The method is inherently stable because a strict algorithmic consistency is applied at all levels in the AMR mesh hierarchy. We also show that the method preserves order of accuracy, so that high order methods for AMR-CED are indeed possible.","PeriodicalId":52176,"journal":{"name":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","volume":"8 ","pages":"82-96"},"PeriodicalIF":1.5000,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal on Multiscale and Multiphysics Computational Techniques","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10005254/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

There is a great need to solve CED problems on adaptive meshes; referred to here as AMR-CED. The problem was deemed to be susceptible to “long-term instability” and parameterized methods have been used to control the instability. In this paper, we present a new class of AMR-CED methods that are free of this instability because they are based on a more careful understanding of the constraints in Maxwell's equations and their preservation on a single control volume. The important building blocks of these new methods are: 1) Timestep sub-cycling of finer child meshes relative to parent meshes. 2) Restriction of fine mesh facial data to coarser meshes when the two meshes are synchronized in time. 3) Divergence constraint-preserving prolongation of the coarse mesh solution to newly built fine meshes or to the ghost zones of pre-existing fine meshes. 4) Electric and magnetic field intensity-correction strategy at fine-coarse interfaces. Using examples, we show that the resulting AMR-CED algorithm is free of “long-term instability”. Unlike previous methods, there are no adjustable parameters. The method is inherently stable because a strict algorithmic consistency is applied at all levels in the AMR mesh hierarchy. We also show that the method preserves order of accuracy, so that high order methods for AMR-CED are indeed possible.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
计算电动力学自适应网格细化的系统方法
迫切需要在自适应网格上解决CED问题;这里称为AMR-CED。该问题被认为易受“长期不稳定性”的影响,并采用参数化方法来控制不稳定性。在本文中,我们提出了一类新的AMR-CED方法,它们没有这种不稳定性,因为它们基于对麦克斯韦方程中的约束的更仔细的理解以及它们在单个控制体积上的保存。这些新方法的重要组成部分是:1)子网格相对于父网格的时间步子循环。2)当两种网格及时同步时,细网格面部数据限制为粗网格。3)保持散度约束的粗网格解扩展到新建的细网格或已存在的细网格的幽灵区域。4)细粗界面电场和磁场强度校正策略。通过实例,我们证明了所得到的AMR-CED算法没有“长期不稳定性”。与以前的方法不同,没有可调参数。该方法具有固有的稳定性,因为在AMR网格层次结构的所有层次上都采用了严格的算法一致性。我们还证明了该方法保留了阶精度,因此AMR-CED的高阶方法确实是可能的。
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 去求助
来源期刊
CiteScore
4.30
自引率
0.00%
发文量
27
期刊最新文献
Application of the Born Approximation for Modeling EM Effects of Moving Materials in COMSOL Multiphysics All-Metallic Orbital Angular Momentum Beam Generator for Future High-Power Microwave Applications Statistical Characterization of Electromagnetic Fields Scattered by Poisson Point Process Distributed PEC Cylinders Modeling of Microwave Propagation Properties of Generalized Anisotropic Composite An ADI–SBTD Technique Free of CFL Stability Condition for Transient Analysis of Coaxial–TGVs in 3D Integration
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1