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Analysis of a semi-augmented mixed finite element method for double-diffusive natural convection in porous media

Numerical Analysis 2021-06-08 v1 Numerical Analysis

Abstract

In this paper we study a stationary double-diffusive natural convection problem in porous media given by a Navier-Stokes/Darcy type system, for describing the velocity and the pressure, coupled to a vector advection-diffusion equation describing the heat and substance concentration, of a viscous fluid in a porous media with physical boundary conditions. The model problem is rewritten in terms of a first-order system, without the pressure, based on the introduction of the strain tensor and a nonlinear pseudo-stress tensor in the fluid equations. After a variational approach, the resulting weak model is then augmented using appropriate redundant penalization terms for the fluid equations along with a standard primal formulation for the heat and substance concentration. Then, it is rewritten as an equivalent fixed-point problem. Well-posedness and uniqueness results for both the continuous and the discrete schemes are stated, as well as the respective convergence result under certain regularity assumptions combined with the Lax-Milgram theorem, and the Banach and Brouwer fixed-point theorems. In particular, Raviart-Thomas elements of order kk are used for approximating the pseudo-stress tensor, piecewise polynomials of degree k \leq k and k+1\leq k+1 are utilized for approximating the strain tensor and the velocity, respectively, and the heat and substance concentration are approximated by means of Lagrange finite elements of order k+1\leq k+1. Optimal a priori error estimates are derived and confirmed through some numerical examples that illustrate the performance of the proposed semi-augmented mixed-primal scheme.

Keywords

Cite

@article{arxiv.2106.02987,
  title  = {Analysis of a semi-augmented mixed finite element method for double-diffusive natural convection in porous media},
  author = {Mario Alvarez and Eligio Colmenares and Filánder A. Sequeira},
  journal= {arXiv preprint arXiv:2106.02987},
  year   = {2021}
}