Mixed Discontinuous Galerkin Method for Quasi-Newtonian Stokes Flows

Mixed Discontinuous Galerkin Method for Quasi-Newtonian Stokes Flows

Year:    2024

Author:    Yanxia Qian, Fei Wang, Wenjing Yan

Journal of Computational Mathematics, Vol. 42 (2024), Iss. 3 : pp. 885–910

Abstract

In this paper, we introduce and analyze an augmented mixed discontinuous Galerkin (MDG) method for a class of quasi-Newtonian Stokes flows. In the mixed formulation, the unknowns are strain rate, stress and velocity, which are approximated by a discontinuous piecewise polynomial triplet $\underline{\mathcal{P}}^S_{k+1}$-$\underline{\mathcal{P}}^S_{k+1}$-$\mathcal{P}_k$ for $k ≥ 0.$ Here, the discontinuous piecewise polynomial function spaces for the field of strain rate and the stress field are designed to be symmetric. In addition, the pressure is easily recovered through simple postprocessing. For the benefit of the analysis, we enrich the MDG scheme with the constitutive equation relating the stress and the strain rate, so that the well-posedness of the augmented formulation is obtained by a nonlinear functional analysis. For $k ≥ 0,$ we get the optimal convergence order for the stress in broken $\underline{H}$(div)-norm and velocity in $L^2$-norm. Furthermore, the error estimates of the strain rate and the stress in $\underline{L}^2$-norm, and the pressure in $L^2$-norm are optimal under certain conditions. Finally, several numerical examples are given to show the performance of the augmented MDG method and verify the theoretical results. Numerical evidence is provided to show that the orders of convergence are sharp.

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.2211-m2021-0255

Journal of Computational Mathematics, Vol. 42 (2024), Iss. 3 : pp. 885–910

Published online:    2024-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    26

Keywords:    Quasi-Newtonian flows Mixed discontinuous Galerkin method Symmetric strain rate Symmetric stress Optimal convergence orders.

Author Details

Yanxia Qian

Fei Wang

Wenjing Yan

  1. Local randomized neural networks with hybridized discontinuous Petrov–Galerkin methods for Stokes–Darcy flows

    Dang, Haoning

    Wang, Fei

    Physics of Fluids, Vol. 36 (2024), Iss. 8

    https://doi.org/10.1063/5.0218131 [Citations: 0]