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dc.contributor.authorVymazal, M
dc.contributor.authorMoxey, D
dc.contributor.authorSherwin, S
dc.contributor.authorCantwell, C
dc.contributor.authorKirby, R
dc.date.accessioned2019-05-30T13:00:52Z
dc.date.issued2019-05-30
dc.description.abstractWe combine continuous and discontinuous Galerkin methods in the setting of a model diffusion problem. Starting from a hybrid discontinuous formulation, we replace element interiors by more general subsets of the computational domain – groups of elements that support a piecewisepolynomial continuous expansion. This step allows us to identify a new weak formulation of Dirichlet boundary condition in the continuous framework. We show that the boundary condition leads to a stable discretization with a single parameter insensitive to mesh size and polynomial order of the expansion. The robustness of the approach is demonstrated on several numerical examples.en_GB
dc.description.sponsorshipEuropean Union Horizon 2020en_GB
dc.description.sponsorshipUS National Science Foundationen_GB
dc.identifier.citationVol. 394, pp. 732-744.en_GB
dc.identifier.doi10.1016/j.jcp.2019.05.021
dc.identifier.grantnumber671571en_GB
dc.identifier.grantnumberDMS-1521748en_GB
dc.identifier.urihttp://hdl.handle.net/10871/37305
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.urlNavier-Stokes equationsen_GB
dc.rights.embargoreasonUnder embargo until 30 May 2020 in compliance with publisher policy.en_GB
dc.rights© 2019 Elsevier Inc. All rights reserved.en_GB
dc.subjectHigh-orderen_GB
dc.titleOn weak Dirichlet boundary conditions for elliptic problems in the continuous Galerkin methoden_GB
dc.typeArticleen_GB
dc.date.available2019-05-30T13:00:52Z
dc.identifier.issn0021-9991
dc.descriptionThis is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.en_GB
dc.identifier.journalJournal of Computational Physicsen_GB
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/  en_GB
dcterms.dateAccepted2019-05-17
rioxxterms.versionAMen_GB
rioxxterms.licenseref.startdate2019-05-17
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-05-30T07:15:41Z
refterms.versionFCDAM
refterms.panelBen_GB


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© 2019 Elsevier Inc. All rights reserved.
Except where otherwise noted, this item's licence is described as © 2019 Elsevier Inc. All rights reserved.