Dr. Caucao-Paillán, Sergio

In this paper we complement the study of a new mixed finite element scheme, allowing conservation of momentum and thermal energy, for the Boussinesq model describing natural convection and derive a reliable and efficient residual-based a posteriori error estimator for the corresponding Galerkin scheme in two and three dimensions. More precisely, by extending standard techniques commonly used on Hilbert spaces to the case of Banach spaces, such as local estimates, suitable Helmholtz decompositions and the local approximation properties of the Clément and Raviart–Thomas operators, we derive the aforementioned a posteriori error estimator on arbitrary (convex or non-convex) polygonal and polyhedral regions. In turn, inverse inequalities, the localization technique based on bubble functions, and known results from previous works, are employed to prove the local efficiency of the proposed a posteriori error estimator. Finally, to illustrate the performance of the adaptive algorithm based on the proposed a posteriori error indicator and to corroborate the theoretical results, we provide some numerical examples.

In this paper we develop an a posteriori error analysis of a new momentum conservative mixed finite element method recently introduced for the steady-state Navier–Stokes problem in two and three dimensions. More precisely, by extending standard techniques commonly used on Hilbert spaces to the case of Banach spaces, such as local estimates, and suitable Helmholtz decompositions, we derive a reliable and efficient residual-based a posteriori error estimator for the corresponding mixed finite element scheme on arbitrary (convex or non-convex) polygonal and polyhedral regions. On the other hand, inverse inequalities, the localization technique based on bubble functions, among other tools, are employed to prove the efficiency of the proposed a posteriori error indicator. Finally, several numerical results confirming the properties of the estimator and illustrating the performance of the associated adaptive algorithm are reported.