Titlebook: Domain Decomposition Methods for the Numerical Solution of Partial Differential Equations; Tarek Poonithara Abraham Mathew Book 2008 Sprin

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Saddle Point Problems,formulation and .. Chap. 10.3 describes the .method for obtaining an approximate solution. Chap. 10.4 describes .. Chap. 10.5 describes .preconditioners and Krylov algorithms. Applications to Navier-Stokes equations, mixed formulations of elliptic equations, and to optimal control problems, are desc

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Non-Matching Grid Discretizations,the subdomains, without requirement to match with the grids adjacent to it, see Fig. 11.1. In this chapter, we describe several methods for the . of a self adjoint and coercive . on a non-matching grid:.Each non-matching grid discretization is based on a . of the underlying elliptic equation on its

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Heterogeneous Domain Decomposition Methods,eterogeneous character by equations of heterogeneous type. In applications, equations of heterogeneous type may sometimes be solved numerically at reduced computational cost, and this motivates their use [GL13, GA15, QU5, QU3, AS2, QU4, BO8, LE7, QU6]. Applications include the approximation of the B

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Variational Inequalities and Obstacle Problems,, an elliptic (or parabolic) equation or inequality is posed on a domain, however, the desired solution is constrained to lie above a specified function, referred to as an obstacle [CR2, GL, FR6, KI4]. Applications arise in elasticity theory [GL10, GL], heat conduction (Stefan problems) and mathemat

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Eigenvalue Problems,n algorithms which . approximate the . eigenvalue and corresponding eigenvector of a matrix, though most such methods can also be extended to simultaneously approximate several eigenvalues, and their associated eigenvectors, see [KR, KU2, BO10, BO11, BO12, BR10, MA9, LU5] and [LU6, KN2, BO13, KN3, C

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