Convergence and Optimality of Adaptive Mixed Methods on Surfaces

In a 1988 article, Dziuk introduced a nodal finite element method for the Laplace-Beltrami equation on 2-surfaces approximated by a piecewise-linear triangulation, initiating a line of research into surface finite element methods (SFEM). Demlow and Dziuk built on the original results, introducing an adaptive method for problems on 2-surfaces, and Demlow later extended the a priori theory to 3-surfaces and higher order elements. In a separate line of research, the Finite Element Exterior Calculus (FEEC) framework has been developed over the last decade by Arnold, Falk and Winther and others as a way to exploit the observation that mixed variational problems can be posed on a Hilbert complex, and Galerkin-type mixed methods can be obtained by solving finite dimensional subproblems. In 2011, Holst and Stern merged these two lines of research by developing a framework for variational crimes in abstract Hilbert complexes, allowing for application of the FEEC framework to problems that violate the subcomplex assumption of Arnold, Falk and Winther. When applied to Euclidean hypersurfaces, this new framework recovers the original a priori results and extends the theory to problems posed on surfaces of arbitrary dimensions. In yet another seemingly distinct line of research, Holst, Mihalik and Szypowski developed a convergence theory for a specific class of adaptive problems in the FEEC framework. Here, we bring these ideas together, showing convergence and optimality of an adaptive finite element method for the mixed formulation of the Hodge Laplacian on hypersurfaces.Comment: 22 pages, no figures. arXiv admin note: substantial text overlap with arXiv:1306.188

Two-grid methods for semilinear interface problems

ABSTRACT. In this article we consider two-grid finite element methods for solving semilinear interface problems in d space dimensions, for d = 2 or d = 3. We first describe in some detail the target problem class with discontinuous diffusion coefficients, which includes problems containing sub-critical, critical, and supercritical nonlinearities. We then establish basic quasi-optimal a priori error estimate for Galerkin approximations. In the critical and subcritical cases, we follow our recent approach to controling the nonlinearity using only pointwise control of the continuous solution and a local Lipschitz property, rather than through pointwise control of the discrete solution; this eliminates the requirement that the discrete solution satisfy a discrete form of the maximum principle, hence eliminating the need for restrictive angle conditions in the underlying mesh. The supercritical case continues to require such mesh conditions in order to control the nonlinearity. We then design a two-grid algorithm consisting of a coarse grid solver for the original nonlinear problem, and a fine grid solver for a linearized problem. We analyze the quality of approximations generated by the algorithm, and show that the coarse grid may be taken to have much larger elements than the fin

CONVERGENCE AND OPTIMALITY OF ADAPTIVE METHODS IN THE FINITE ELEMENT EXTERIOR CALCULUS FRAMEWORK

ABSTRACT. Finite Element Exterior Calculus (FEEC) was developed by Arnold, Falk, Winther and others over the last decade to exploit the observation that mixed variational problems can be posed on a Hilbert Complex, and Galerkin-type mixed methods can then be obtained by solving finite-dimensional subcomplex problems. Stability and consistency of the resulting methods then follow directly from the framework by establishing the existence of operators connecting the Hilbert complex with its subcomplex, giving a essentially a “recipe ” for well-behaved methods. In 2012, Demlow and Hirani developed a posteriori error indicators for driving adaptive methods in the FEEC framework. While adaptive techniques have been used successfully with mixed methods for years, convergence theory for such techniques has not been fully developed. The main difficulty is lack of error orthogonality. In 2009, Chen, Holst, and Xu established convergence and optimality of an adaptive mixed finite element method for the Poisson equation (the Hodge-Laplace problem fork = n = 2) on simply connected polygonal domains in two dimensions. Their argument used a type of quasi-orthogonality result, exploiting the fact that the error was orthogonal to the divergence free subspace, while the part of the erro