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      A priori and a posteriori error bounds for the fully mixed FEM formulation of poroelasticity with stress-dependent permeability

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          Abstract

          We develop a family of mixed finite element methods for a model of nonlinear poroelasticity where, thanks to a rewriting of the constitutive equations, the permeability depends on the total poroelastic stress and on the fluid pressure and therefore we can use the Hellinger--Reissner principle with weakly imposed stress symmetry for Biot's equations. The problem is adequately structured into a coupled system consisting of one saddle-point formulation, one linearised perturbed saddle-point formulation, and two off-diagonal perturbations. This system's unique solvability requires assumptions on regularity and Lipschitz continuity of the inverse permeability, and the analysis follows fixed-point arguments and the Babu\v{s}ka--Brezzi theory. The discrete problem is shown uniquely solvable by applying similar fixed-point and saddle-point techniques as for the continuous case. The method is based on the classical PEERS\(_k\) elements, it is exactly momentum and mass conservative, and it is robust with respect to the nearly incompressible as well as vanishing storativity limits. We derive a priori error estimates, we also propose fully computable residual-based a posteriori error indicators, and show that they are reliable and efficient with respect to the natural norms, and robust in the limit of near incompressibility. These a posteriori error estimates are used to drive adaptive mesh refinement. The theoretical analysis is supported and illustrated by several numerical examples in 2D and 3D.

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          Author and article information

          Journal
          05 September 2024
          Article
          2409.03246
          800a91f1-7e7e-406c-9995-78a48c69f513

          http://creativecommons.org/licenses/by/4.0/

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          Custom metadata
          65N30, 65N15, 65J15, 76S05, 35Q74
          math.NA cs.NA

          Numerical & Computational mathematics
          Numerical & Computational mathematics

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