An a Posteriori Error Estimator for a New Stabilized Formulation of the Brinkman Problem
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Publication:5264849
DOI10.1007/978-3-319-10705-9_25zbMath1321.76036OpenAlexW2152120641MaRDI QIDQ5264849
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Publication date: 28 July 2015
Published in: Lecture Notes in Computational Science and Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-319-10705-9_25
Flows in porous media; filtration; seepage (76S05) Finite element methods applied to problems in fluid mechanics (76M10)
Related Items (6)
Numerical analysis of a stabilized scheme applied to incompressible elasticity problems with Dirichlet and with mixed boundary conditions ⋮ An A Posteriori Error Estimator for a Non Homogeneous Dirichlet Problem Considering a Dual Mixed Formulation ⋮ An a posteriori error analysis of a velocity-pseudostress formulation of the generalized Stokes problem ⋮ Stabilization and a posteriori error analysis of a mixed FEM for convection-diffusion problems with mixed boundary conditions ⋮ An adaptive virtual element method for incompressible flow ⋮ New a posteriori error estimator for an stabilized mixed method applied to incompressible fluid flows
Cites Work
- Analysis of a velocity-pressure-pseudostress formulation for the stationary Stokes equations
- A priori and a posteriori error analyses of a velocity-pseudostress formulation for a class of quasi-Newtonian Stokes flows
- On stabilized mixed methods for generalized Stokes problem based on the velocity-pseudostress formulation: a priori error estimates
- Well-posedness of the fundamental boundary value problems for constrained anisotropic elastic materials
- Analysis of a pseudostress-based mixed finite element method for the Brinkman model of porous media flow
- Mixed finite element methods for incompressible flow: Stationary Stokes equations
- Pseudostress-Based Mixed Finite Element Methods for the Stokes Problem in ℝnwith Dirichlet Boundary Conditions. I: A Priori Error Analysis
- Least-Squares Methods for Incompressible Newtonian Fluid Flow: Linear Stationary Problems
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