对流扩散问题的变分离散法比较

Constantin Bacuta, Cristina Bacuta, Daniel Hayes
{"title":"对流扩散问题的变分离散法比较","authors":"Constantin Bacuta, Cristina Bacuta, Daniel Hayes","doi":"arxiv-2402.10281","DOIUrl":null,"url":null,"abstract":"For a model convection-diffusion problem, we obtain new error estimates for a\ngeneral upwinding finite element discretization based on bubble modification of\nthe test space. The key analysis tool is based on finding representations of\nthe optimal norms on the trial spaces at the continuous and discrete levels. We\nanalyze and compare the standard linear discretization, the saddle point least\nsquare and upwinding Petrov-Galerkin methods. We conclude that the bubble\nupwinding Petrov-Galerkin method is the most performant discretization for the\none dimensional model. Our results for the model convection-diffusion problem\ncan be extended for creating new and efficient discretizations for the\nmultidimensional cases.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"147 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of variational discretizations for a convection-diffusion problem\",\"authors\":\"Constantin Bacuta, Cristina Bacuta, Daniel Hayes\",\"doi\":\"arxiv-2402.10281\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For a model convection-diffusion problem, we obtain new error estimates for a\\ngeneral upwinding finite element discretization based on bubble modification of\\nthe test space. The key analysis tool is based on finding representations of\\nthe optimal norms on the trial spaces at the continuous and discrete levels. We\\nanalyze and compare the standard linear discretization, the saddle point least\\nsquare and upwinding Petrov-Galerkin methods. We conclude that the bubble\\nupwinding Petrov-Galerkin method is the most performant discretization for the\\none dimensional model. Our results for the model convection-diffusion problem\\ncan be extended for creating new and efficient discretizations for the\\nmultidimensional cases.\",\"PeriodicalId\":501061,\"journal\":{\"name\":\"arXiv - CS - Numerical Analysis\",\"volume\":\"147 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Numerical Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2402.10281\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Numerical Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2402.10281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

对于一个模型对流扩散问题,我们基于对试验空间的气泡修正,获得了一般上卷有限元离散化的新误差估计。关键的分析工具是基于在连续和离散层面上找到试验空间的最优规范表示。我们分析并比较了标准线性离散化、鞍点最小平方和上卷 Petrov-Galerkin 方法。我们得出结论,对于一维模型,气泡上卷 Petrov-Galerkin 方法是性能最好的离散化方法。我们对模型对流-扩散问题的研究结果可以扩展到为多维情况创建新的高效离散方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of variational discretizations for a convection-diffusion problem
For a model convection-diffusion problem, we obtain new error estimates for a general upwinding finite element discretization based on bubble modification of the test space. The key analysis tool is based on finding representations of the optimal norms on the trial spaces at the continuous and discrete levels. We analyze and compare the standard linear discretization, the saddle point least square and upwinding Petrov-Galerkin methods. We conclude that the bubble upwinding Petrov-Galerkin method is the most performant discretization for the one dimensional model. Our results for the model convection-diffusion problem can be extended for creating new and efficient discretizations for the multidimensional cases.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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