{"title":"四阶椭圆方程的自适应最小二乘混合有限元法","authors":"Gu Hai-ming, Lin Hongwei, Xie Bing","doi":"10.2174/1876389800901010001","DOIUrl":null,"url":null,"abstract":"A least-squares mixed finite element method for the numerical solution of second order elliptic equations is analyzed and developed in this paper.The quadratic nonconforming and Raviart-Thomas finite element spaces are used to approximate.The aposteriori error estimator which is needed in the adaptive refinement algorithm is proposed.The local evaluation of the least-squares functional serves as a posteriori error estimator.The posteriori errors are effectively estimated.","PeriodicalId":16928,"journal":{"name":"Journal of Qingdao University of Science and Technology","volume":"35 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Adaptive Least-Squares Mixed Finite Element Method for Fourth- Order Elliptic Equations\",\"authors\":\"Gu Hai-ming, Lin Hongwei, Xie Bing\",\"doi\":\"10.2174/1876389800901010001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A least-squares mixed finite element method for the numerical solution of second order elliptic equations is analyzed and developed in this paper.The quadratic nonconforming and Raviart-Thomas finite element spaces are used to approximate.The aposteriori error estimator which is needed in the adaptive refinement algorithm is proposed.The local evaluation of the least-squares functional serves as a posteriori error estimator.The posteriori errors are effectively estimated.\",\"PeriodicalId\":16928,\"journal\":{\"name\":\"Journal of Qingdao University of Science and Technology\",\"volume\":\"35 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Qingdao University of Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2174/1876389800901010001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Qingdao University of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1876389800901010001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Adaptive Least-Squares Mixed Finite Element Method for Fourth- Order Elliptic Equations
A least-squares mixed finite element method for the numerical solution of second order elliptic equations is analyzed and developed in this paper.The quadratic nonconforming and Raviart-Thomas finite element spaces are used to approximate.The aposteriori error estimator which is needed in the adaptive refinement algorithm is proposed.The local evaluation of the least-squares functional serves as a posteriori error estimator.The posteriori errors are effectively estimated.
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