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dc.contributor.authorRamalho Queiroz Pacheco, Douglas
dc.contributor.authorSteinbach, Olaf
dc.date.accessioned2024-07-26T06:15:33Z
dc.date.available2024-07-26T06:15:33Z
dc.date.created2023-11-29T08:36:51Z
dc.date.issued2023
dc.identifier.citationComputational Methods in Applied Mathematics. 2023, .en_US
dc.identifier.issn1609-4840
dc.identifier.urihttps://hdl.handle.net/11250/3143303
dc.description.abstractReconstructing the pressure from given flow velocities is a task arising in various applications, and the standard approach uses the Navier–Stokes equations to derive a Poisson problem for the pressure p. That method, however, artificially increases the regularity requirements on both solution and data. In this context, we propose and analyze two alternative techniques to determine p∈L2(Ω) . The first is an ultra-weak variational formulation applying integration by parts to shift all derivatives to the test functions. We present conforming finite element discretizations and prove optimal convergence of the resulting Galerkin–Petrov method. The second approach is a least-squares method for the original gradient equation, reformulated and solved as an artificial Stokes system. To simplify the incorporation of the given velocity within the right-hand side, we assume in the derivations that the velocity field is solenoidal. Yet this assumption is not restrictive, as we can use non-divergence-free approximations and even compressible velocities. Numerical experiments confirm the optimal a priori error estimates for both methods considered.en_US
dc.language.isoengen_US
dc.publisherDe Gruyteren_US
dc.titleOptimal Pressure Recovery Using an Ultra-Weak Finite Element Method for the Pressure Poisson Equation and a Least-Squares Approach for the Gradient Equationen_US
dc.title.alternativeOptimal Pressure Recovery Using an Ultra-Weak Finite Element Method for the Pressure Poisson Equation and a Least-Squares Approach for the Gradient Equationen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2023 Walter de Gruyter GmbH, Berlin/Boston All Rights Reserveden_US
dc.source.pagenumber14en_US
dc.source.journalComputational Methods in Applied Mathematicsen_US
dc.identifier.doi10.1515/cmam-2021-0242
dc.identifier.cristin2204631
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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