{"title":"论数值均质化中边界共振误差的性质及其减小","authors":"Sean P. Carney, Milica Dussinger, Björn Engquist","doi":"10.1137/23m1594492","DOIUrl":null,"url":null,"abstract":"Multiscale Modeling &Simulation, Volume 22, Issue 2, Page 811-835, June 2024. <br/> Abstract. Numerical homogenization of multiscale equations typically requires taking an average of the solution to a microscale problem. Both the boundary conditions and domain size of the microscale problem play an important role in the accuracy of the homogenization procedure. In particular, imposing naive boundary conditions leads to an [math] error in the computation, where [math] is the characteristic size of the microscopic fluctuations in the heterogeneous media, and [math] is the size of the microscopic domain. This so-called boundary or “cell resonance” error can dominate discretization error and pollute the entire homogenization scheme. There exist several techniques in the literature to reduce the error. Most strategies involve modifying the form of the microscale cell problem. Below we present an alternative procedure based on the observation that the resonance error itself is an oscillatory function of domain size [math]. After rigorously characterizing the oscillatory behavior for one-dimensional and quasi-one-dimensional microscale domains, we present a novel strategy to reduce the resonance error. Rather than modifying the form of the cell problem, the original problem is solved for a sequence of domain sizes, and the results are averaged against kernels satisfying certain moment conditions and regularity properties. Numerical examples in one and two dimensions illustrate the utility of the approach.","PeriodicalId":501053,"journal":{"name":"Multiscale Modeling and Simulation","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On the Nature of the Boundary Resonance Error in Numerical Homogenization and Its Reduction\",\"authors\":\"Sean P. Carney, Milica Dussinger, Björn Engquist\",\"doi\":\"10.1137/23m1594492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiscale Modeling &Simulation, Volume 22, Issue 2, Page 811-835, June 2024. <br/> Abstract. Numerical homogenization of multiscale equations typically requires taking an average of the solution to a microscale problem. Both the boundary conditions and domain size of the microscale problem play an important role in the accuracy of the homogenization procedure. In particular, imposing naive boundary conditions leads to an [math] error in the computation, where [math] is the characteristic size of the microscopic fluctuations in the heterogeneous media, and [math] is the size of the microscopic domain. This so-called boundary or “cell resonance” error can dominate discretization error and pollute the entire homogenization scheme. There exist several techniques in the literature to reduce the error. Most strategies involve modifying the form of the microscale cell problem. Below we present an alternative procedure based on the observation that the resonance error itself is an oscillatory function of domain size [math]. After rigorously characterizing the oscillatory behavior for one-dimensional and quasi-one-dimensional microscale domains, we present a novel strategy to reduce the resonance error. Rather than modifying the form of the cell problem, the original problem is solved for a sequence of domain sizes, and the results are averaged against kernels satisfying certain moment conditions and regularity properties. Numerical examples in one and two dimensions illustrate the utility of the approach.\",\"PeriodicalId\":501053,\"journal\":{\"name\":\"Multiscale Modeling and Simulation\",\"volume\":\"34 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Multiscale Modeling and Simulation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1137/23m1594492\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Multiscale Modeling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1137/23m1594492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the Nature of the Boundary Resonance Error in Numerical Homogenization and Its Reduction
Multiscale Modeling &Simulation, Volume 22, Issue 2, Page 811-835, June 2024. Abstract. Numerical homogenization of multiscale equations typically requires taking an average of the solution to a microscale problem. Both the boundary conditions and domain size of the microscale problem play an important role in the accuracy of the homogenization procedure. In particular, imposing naive boundary conditions leads to an [math] error in the computation, where [math] is the characteristic size of the microscopic fluctuations in the heterogeneous media, and [math] is the size of the microscopic domain. This so-called boundary or “cell resonance” error can dominate discretization error and pollute the entire homogenization scheme. There exist several techniques in the literature to reduce the error. Most strategies involve modifying the form of the microscale cell problem. Below we present an alternative procedure based on the observation that the resonance error itself is an oscillatory function of domain size [math]. After rigorously characterizing the oscillatory behavior for one-dimensional and quasi-one-dimensional microscale domains, we present a novel strategy to reduce the resonance error. Rather than modifying the form of the cell problem, the original problem is solved for a sequence of domain sizes, and the results are averaged against kernels satisfying certain moment conditions and regularity properties. Numerical examples in one and two dimensions illustrate the utility of the approach.