Volume 49, pp. 151-181, 2018.

A posteriori stopping criteria for space-time domain decomposition for the heat equation in mixed formulations

Sarah Ali Hassan, Caroline Japhet, and Martin Vohralík

Abstract

We propose and analyze a posteriori estimates for global-in-time, nonoverlapping domain decomposition methods for heterogeneous and anisotropic porous media diffusion problems. We consider mixed formulations with a lowest-order Raviart-Thomas-Nédélec discretization often used for such problems. Optimized Robin transmission conditions are employed on the space-time interface between subdomains, and different time grids are used to adapt to different time scales in the subdomains. Our estimators allow to distinguish the spatial discretization, the temporal discretization, and the domain decomposition error components. We design an adaptive space-time domain decomposition algorithm, wherein the iterations are stopped when the domain decomposition error does not affect significantly the global error. Overall, a guaranteed bound for the overall error is obtained at each iteration of the space-time domain decomposition algorithm, and simultaneously important savings in terms of the number of domain decomposition iterations can be achieved. Numerical results for two-dimensional problems with strong heterogeneities and local time-stepping are presented to illustrate the performance of our adaptive domain decomposition algorithm.

Full Text (PDF) [1.5 MB], BibTeX

Key words

mixed finite element method, global-in-time domain decomposition, nonconforming time grids, Robin interface conditions, a posteriori error estimate, stopping criteria

AMS subject classifications

65N15, 65N22, 65N55, 65F10, 76S05

Links to the cited ETNA articles

[7]Vol. 29 (2007-2008), pp. 178-192 M. Arioli and D. Loghin: Stopping criteria for mixed finite element problems
[46]Vol. 40 (2013), pp. 148-169 Florian Lemarié, Laurent Debreu, and Eric Blayo: Toward an optimized global-in-time Schwarz algorithm for diffusion equations with discontinuous and spatially variable coefficients. Part 1: the constant coefficients case

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