2,450 research outputs found
Numerical comparison of different choices of interface weights in the BDDC method
summary:Balancing Domain Decomposition by Constraints (BDDC) belongs to the class of primal substructuring Domain Decomposition (DD) methods. DD methods are iterative methods successfully used in engineering to parallelize solution of large linear systems arising from discretization of second order elliptic problems. Substructuring DD methods represent an important class of DD methods. Their main idea is to divide the underlying domain into nonoverlapping subdomains and solve many relatively small, local problems on subdomains instead of one large problem on the whole domain. In primal methods, it has to be specified how to distribute interface residuals among subdomains and how to obtain global, interface values of solution from local values on adjacent subdomains. Usually a weighted average is used with some simple choice of weights. In our paper we present numerical comparison of three different choices of interface weights on test problem of 2D Poisson equation, with and without jumps in coefficients
Nonoverlapping domain decomposition preconditioners for discontinuous Galerkin approximations of Hamilton--Jacobi--Bellman equations
We analyse a class of nonoverlapping domain decomposition preconditioners for
nonsymmetric linear systems arising from discontinuous Galerkin finite element
approximation of fully nonlinear Hamilton--Jacobi--Bellman (HJB) partial
differential equations. These nonsymmetric linear systems are uniformly bounded
and coercive with respect to a related symmetric bilinear form, that is
associated to a matrix . In this work, we construct a
nonoverlapping domain decomposition preconditioner , that is based
on , and we then show that the effectiveness of the preconditioner
for solving the} nonsymmetric problems can be studied in terms of the condition
number . In particular, we establish the
bound , where
and are respectively the coarse and fine mesh sizes, and and
are respectively the coarse and fine mesh polynomial degrees. This represents
the first such result for this class of methods that explicitly accounts for
the dependence of the condition number on ; our analysis is founded upon an
original optimal order approximation result between fine and coarse
discontinuous finite element spaces. Numerical experiments demonstrate the
sharpness of this bound. Although the preconditioners are not robust with
respect to the polynomial degree, our bounds quantify the effect of the coarse
and fine space polynomial degrees. Furthermore, we show computationally that
these methods are effective in practical applications to nonsymmetric, fully
nonlinear HJB equations under -refinement for moderate polynomial degrees
Domain decomposition methods for compressed sensing
We present several domain decomposition algorithms for sequential and
parallel minimization of functionals formed by a discrepancy term with respect
to data and total variation constraints. The convergence properties of the
algorithms are analyzed. We provide several numerical experiments, showing the
successful application of the algorithms for the restoration 1D and 2D signals
in interpolation/inpainting problems respectively, and in a compressed sensing
problem, for recovering piecewise constant medical-type images from partial
Fourier ensembles.Comment: 4 page
A simple preconditioned domain decomposition method for electromagnetic scattering problems
We present a domain decomposition method (DDM) devoted to the iterative
solution of time-harmonic electromagnetic scattering problems, involving large
and resonant cavities. This DDM uses the electric field integral equation
(EFIE) for the solution of Maxwell problems in both interior and exterior
subdomains, and we propose a simple preconditioner for the global method, based
on the single layer operator restricted to the fictitious interface between the
two subdomains.Comment: 23 page
Domain decomposition algorithms and computation fluid dynamics
In the past several years, domain decomposition was a very popular topic, partly motivated by the potential of parallelization. While a large body of theory and algorithms were developed for model elliptic problems, they are only recently starting to be tested on realistic applications. The application of some of these methods to two model problems in computational fluid dynamics are investigated. Some examples are two dimensional convection-diffusion problems and the incompressible driven cavity flow problem. The construction and analysis of efficient preconditioners for the interface operator to be used in the iterative solution of the interface solution is described. For the convection-diffusion problems, the effect of the convection term and its discretization on the performance of some of the preconditioners is discussed. For the driven cavity problem, the effectiveness of a class of boundary probe preconditioners is discussed
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