dc.contributor.authorHeimsund, Bjorn-Ove
dc.contributor.authorTai, Xue Cheng
dc.contributor.authorWang, Junping
dc.date.accessioned2009-08-12T02:15:02Z
dc.date.available2009-08-12T02:15:02Z
dc.date.copyright2002en_US
dc.date.issued2002
dc.identifier.citationHeimsund, B. O., Tai, X. C., & Wang, J. (2002). Superconvergence for the gradient of finite element approximations by L2-projections. SIAM Journal on Numerical Analysis, 40(4), 1263-1280.en_US
dc.identifier.issn0036-1429en_US
dc.identifier.urihttp://hdl.handle.net/10220/6049
dc.description.abstractA gradient recovery technique is proposed and analyzed for finite element solutions which provides new gradient approximations with high order of accuracy. The recovery technique is based on the method of least-squares surface fitting in a finite-dimensional space corresponding to a coarse mesh. It is proved that the recovered gradient has a high order of superconvergence for appropriately chosen surface fitting spaces. The recovery technique is robust, efficient, and applicable to a wide class of problems such as the Stokes and elasticity equations.en_US
dc.format.extent18 p.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesSIAM Journal on Numerical Analysis.en_US
dc.rightsSIAM Journal on Numerical Analysis © copyright 2002 Siam Society for Industrial and Applied Mathematics. The journal's website is located at http://www.siam.org/journals/sinum.php.en_US
dc.subjectDRNTU::Science::Mathematics::Applied mathematics::Numerical analysis
dc.titleSuperconvergence for the gradient of finite element approximations by L2-projectionsen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.identifier.openurlhttp://sfxna09.hosted.exlibrisgroup.com:3410/ntu/sfxlcl3?sid=metalib:ELSEVIER_SCOPUS&id=doi:&genre=&isbn=&issn=&date=2002&volume=40&issue=4&spage=1263&epage=1280&aulast=Heimsund&aufirst=%20B%20%2DO&auinit=&title=SIAM%20Journal%20on%20Numerical%20Analysis&atitle=Superconvergence%20for%20the%20gradient%20of%20finite%20element%20approximations%20by%20L2%20projections&sici.
dc.identifier.doihttp://dx.doi.org/10.1137/S003614290037410X.
dc.description.versionPublished versionen_US


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