{"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":null,"pages":null},"PeriodicalIF":1.8000,"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.