50 research outputs found

    FETI-DP algorithms for 2D Biot model with discontinuous Galerkin discretization

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    Dual-Primal Finite Element Tearing and Interconnecting (FETI-DP) algorithms are developed for a 2D Biot model. The model is formulated with mixed-finite elements as a saddle-point problem. The displacement u\mathbf{u} and the Darcy flux flow z\mathbf{z} are represented with P1P_1 piecewise continuous elements and pore-pressure pp with P0P_0 piecewise constant elements, {\it i.e.}, overall three fields with a stabilizing term. We have tested the functionality of FETI-DP with Dirichlet preconditioners. Numerical experiments show a signature of scalability of the resulting parallel algorithm in the compressible elasticity with permeable Darcy flow as well as almost incompressible elasticity.Comment: Accepted to the 27th International Conference on Domain Decomposition Methods (DD27), 8 pages. arXiv admin note: text overlap with arXiv:2211.1502

    A Nonoverlapping Domain Decomposition Method for Incompressible Stokes Equations with Continuous Pressures

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    This is the publisher's version, also available electronically from http://epubs.siam.org/doi/abs/10.1137/120861503A nonoverlapping domain decomposition algorithm is proposed to solve the linear system arising from mixed finite element approximation of incompressible Stokes equations. A continuous finite element space for the pressure is used. In the proposed algorithm, Lagrange multipliers are used to enforce continuity of the velocity component across the subdomain boundary. The continuity of the pressure component is enforced in the primal form, i.e., neighboring subdomains share the same pressure degrees of freedom on the subdomain interface and no Lagrange multipliers are needed. After eliminating all velocity variables and the independent subdomain interior parts of the pressures, a symmetric positive semidefinite linear system for the subdomain boundary pressures and the Lagrange multipliers is formed and solved by a preconditioned conjugate gradient method. A lumped preconditioner is studied and the condition number bound of the preconditioned operator is proved to be independent of the number of subdomains for fixed subdomain problem size. Numerical experiments demonstrate the convergence rate of the proposed algorithm

    A FETI-DP TYPE DOMAIN DECOMPOSITION ALGORITHM FOR THREE-DIMENSIONAL INCOMPRESSIBLE STOKES EQUATIONS

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    The FETI-DP (dual-primal finite element tearing and interconnecting) algorithms, proposed by the authors in [SIAM J. Numer. Anal., 51 (2013), pp. 1235–1253] and [Internat. J. Numer. Methods Engrg., 94 (2013), pp. 128–149] for solving incompressible Stokes equations, are extended to three-dimensional problems. A new analysis of the condition number bound for using the Dirichlet preconditioner is given. The algorithm and analysis are valid for mixed finite elements with both continuous and discontinuous pressures. An advantage of this new analysis is that the numerous coarse level velocity components, required in the previous analysis to enforce the divergence-free subdomain boundary velocity conditions, are no longer needed. This greatly reduces the size of the coarse level problem in the algorithm, especially for three-dimensional problems. The coarse level velocity space can be chosen as simple as those coarse spaces for solving scalar elliptic problems corresponding to each velocity component. Both the Dirichlet and lumped preconditioners are analyzed using the same framework in this new analysis. Their condition number bounds are proved to be independent of the number of subdomains for fixed subdomain problem size. Numerical experiments in both two and three dimensions, using mixed finite elements with both continuous and discontinuous pressures, demonstrate the convergence rate of the algorithms

    Domain decomposition methods for coupled Stokes-Darcy flows

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    This thesis studies the numerical methods for coupled Stokes-Darcy problem. It consists of three major parts: First, a non-overlapping domain decomposition method is presented for Stokes-Darcy problem by partitioning the computational domain into multiple subdomains, upon which families of coupled local problems of lower complexity are formulated. The coupling is based on appropriate interface matching conditions. The global problem is reduced to an interface problem by eliminating the interior subdomain variables, which can be solved by an iterative procedure. FETI approach is used for floating Stokes subdomains. The condition number of the resulting algebraic system is analyzed and numerical tests on matching grids verifying the theoretical estimates are provided. Second, a multiscale flux basis algorithm is developed based on the domain decomposition with multiscale mortar mixed finite element method. The algorithm involves precomputing a multiscale flux basis, which consists of the flux (or velocity trace) response from each mortar degree of freedom. It is computed by each subdomain independently before the interface iteration begins. The subdomain solves required at each iteration are substituted by a linear combination of the multiscale basis. This may lead to a significant reduction in computational cost since the number of subdomain solves is fixed, depending only on the number of mortar degrees of freedom associated with a subdomain. Several numerical examples are carried out to demonstrate the efficiency of the multiscale flux basis implementation. Third, a multiscale flux basis implementation is presented for coupled Stokes-Darcy flows with stochastic permeability, with its log represented as a sum of local Karhunen-Lo\`{e}ve expansions. The problem is approximated by stochastic collocation on either a tensor product or a sparse grid, coupled with multiscale mortar mixed finite element method using non-overlapping domain decomposition for the spatial discretization. Two algorithms based on deterministic or stochastic multiscale flux basis are introduced. Some numerical tests are presented to illustrate the performances of these algorithms, with the stochastic multiscale flux basis showing a great advantage in computational cost among all

    Robust exact and inexact FETI-DP methods with applications to elasticity

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    Gebietszerlegungsverfahren sind parallele, iterative Lösungsverfahren für grosse Gleichungssysteme, die bei der Diskretisierung von partiellen Differentialgleichungen, etwa aus der Strukturmechanik, entstehen. In dieser Arbeit werden duale, iterative Substrukturierungsverfahren vom FETI-DP-Typ (Finite Element Tearing and Interconnecting Dual-Primal) entwickelt und auf elliptische partielle Differentialgleichungen zweiter Ordnung angewandt. Insbesondere wird versucht, robuste Verfahren für homogene und heterogene Elastizitaetsprobleme zu entwickeln. Ebenso werden neue, inexakte FETI-DP-Verfahren vorgestellt, die eine inexakte Lösung des Grobgitterproblems und/oder der Teilgebietsprobleme erlauben. Es wird gezeigt, dass die neuen Algorithmen unter bestimmten Voraussetzungen Abschätzungen der gleichen asymptotischen Güte wie das klassische, exakte FETI-DP-Verfahren erfüllen. Parallele Resultate unter Verwendung von algebraischen Mehrgitter für das Grobgitterproblem zeigen die verbesserte Skalierbarkeit der neuen Algorithmen.Domain decomposition methods are fast parallel solvers for large equation systems arising from the discretisation of partial differential equations, e.g. from structural mechanics. In this work, dual iterative substructuring methods of the FETI-DP (Finite Element Tearing and Interconnecting Dual-Primal) type are developed and applied to second order elliptic problems with emphasis on elasticity. An attempt is made to develop robust methods for homogeneous and heterogeneous problems. New inexact FETI-DP methods are also introduced that allow for inexact coarse problem solvers and/or inexact subdomain solvers. It is shown that under certain conditions the new algorithms fulfill the same asymptotic condition number estimate as the traditional, exact FETI-DP methods. Parallel results using algebraic multigrid for the FETI-DP coarse problem show the improved scalability of the new algorithms
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