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Pre-Publicación 2015-33

Mario Álvarez, Gabriel N. Gatica, Ricardo Ruiz-Baier:

A posteriori error analysis for a viscous flow-transport problem


In this paper we develop an a posteriori error analysis for an augmented mixed--primal finite element approximation of a stationary viscous flow and transport problem. The governing system corresponds to a scalar, nonlinear convection-diffusion equation coupled with a Stokes problem with variable viscosity, and it serves as a prototype model for sedimentation-consolidation processes and other phenomena where the transport of species concentration within a viscous fluid is of interest. The solvability of the continuous mixed--primal formulation along with a priori error estimates for a finite element scheme using Raviart-Thomas spaces of order k for the stress approximation, and continuous piecewise polynomials of degree \le k +1 for both velocity and concentration, have been recently established in [M. Alvarez et al., ESAIM: Math. Model. Numer. Anal. 49 (5) (2015) 1399--1427]. Here we derive two efficient and reliable residual-based a posteriori error estimators for that scheme: For the first estimator, and under suitable assumptions on the domain, we apply a Helmholtz decomposition and exploit local approximation properties of the Clement interpolant and Raviart-Thomas operator to show its reliability. On the other hand, its efficiency follows from inverse inequalities and the localization arguments based on triangle-bubble and edge-bubble functions. Secondly, an alternative error estimator is proposed, whose reliability can be proved without resorting to Helmholtz decompositions. Our theoretical results are then illustrated via some numerical examples, highlighting also the performance of the scheme and properties of the proposed error indicators.

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Esta prepublicacion dio origen a la(s) siguiente(s) publicación(es) definitiva(s):

Mario ÁLVAREZ, Gabriel N. GATICA, Ricardo RUIZ-BAIER: A posteriori error analysis for a viscous flow-transport problem. ESAIM: Mathematical Modelling and Numerical Analysis, vol. 50, 6, pp. 1789-1816, (2016).