5 research outputs found
Discontinuous Galerkin approximations in computational mechanics: hybridization, exact geometry and degree adaptivity
Discontinuous Galerkin (DG) discretizations with exact representation of the geometry and local polynomial degree adaptivity are revisited. Hybridization techniques are employed to reduce the computational cost of DG approximations and devise the hybridizable discontinuous Galerkin (HDG) method. Exact geometry described by non-uniform rational B-splines (NURBS) is integrated into HDG using the framework of the NURBS-enhanced finite element method (NEFEM). Moreover, optimal convergence and superconvergence properties of HDG-Voigt formulation in presence of symmetric second-order tensors are exploited to construct inexpensive error indicators and drive degree adaptive procedures. Applications involving the numerical simulation of problems in electrostatics, linear elasticity and incompressible viscous flows are presented. Moreover, this is done for both high-order HDG approximations and the lowest-order framework of face-centered finite volumes (FCFV).Peer ReviewedPostprint (author's final draft
Local Fourier analysis of multigrid for hybridized and embedded discontinuous Galerkin methods
In this paper we present a geometric multigrid method with Jacobi and Vanka
relaxation for hybridized and embedded discontinuous Galerkin discretizations
of the Laplacian. We present a local Fourier analysis (LFA) of the two-grid
error-propagation operator and show that the multigrid method applied to an
embedded discontinuous Galerkin (EDG) discretization is almost as efficient as
when applied to a continuous Galerkin discretization. We furthermore show that
multigrid applied to an EDG discretization outperforms multigrid applied to a
hybridized discontinuous Galerkin (HDG) discretization. Numerical examples
verify our LFA predictions
Hybrid multigrid methods for high-order discontinuous Galerkin discretizations
The present work develops hybrid multigrid methods for high-order
discontinuous Galerkin discretizations of elliptic problems. Fast matrix-free
operator evaluation on tensor product elements is used to devise a
computationally efficient PDE solver. The multigrid hierarchy exploits all
possibilities of geometric, polynomial, and algebraic coarsening, targeting
engineering applications on complex geometries. Additionally, a transfer from
discontinuous to continuous function spaces is performed within the multigrid
hierarchy. This does not only further reduce the problem size of the
coarse-grid problem, but also leads to a discretization most suitable for
state-of-the-art algebraic multigrid methods applied as coarse-grid solver. The
relevant design choices regarding the selection of optimal multigrid coarsening
strategies among the various possibilities are discussed with the metric of
computational costs as the driving force for algorithmic selections. We find
that a transfer to a continuous function space at highest polynomial degree (or
on the finest mesh), followed by polynomial and geometric coarsening, shows the
best overall performance. The success of this particular multigrid strategy is
due to a significant reduction in iteration counts as compared to a transfer
from discontinuous to continuous function spaces at lowest polynomial degree
(or on the coarsest mesh). The coarsening strategy with transfer to a
continuous function space on the finest level leads to a multigrid algorithm
that is robust with respect to the penalty parameter of the SIPG method.
Detailed numerical investigations are conducted for a series of examples
ranging from academic test cases to more complex, practically relevant
geometries. Performance comparisons to state-of-the-art methods from the
literature demonstrate the versatility and computational efficiency of the
proposed multigrid algorithms