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Titlebook: Domain Decomposition Methods in Science and Engineering XIX; Yunqing Huang,Ralf Kornhuber,Jinchao Xu Conference proceedings 2011 Springer-

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Two-Level Methods for Blood Flow Simulationication area [6, 8]. In particular, the similar densities of blood and artery wall make the coupling between fluid and structure strong in both directions, so that partitioned or iterative procedures have difficulties due to the added-mass effect [4]. Instead of a partitioned procedure, we adopt a m
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A Parallel Scalable PETSc-Based Jacobi-Davidson Polynomial Eigensolver with Application in Quantum De problems, which commonly appear in many computational science and engineering PDE based applications. As other inner–outer algorithms like Newton type method, the bottleneck of the JD algorithm is to solve approximately the inner correction equation. In the previous work, [Hwang, Wei, Huang, and W
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Two-Level Multiplicative Domain Decomposition Algorithm for Recovering the Lamé Coefficient in Biolocribed in terms of the Lamé coefficient. In this paper, an all-at-once Lagrange-Newton-Krylov-Schwarz algorithm is developed to solve the inverse problem of recovering the Lamé coefficient in biological tissues. Specifically, we propose and study a multiplicative two-level domain decomposition preco
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Rufai Haruma Kilu,Mohammed-Amidu Sandaa posteriori error estimate has been developed including the residual type a posteriori error estimate [8], recovery type a posteriori error estimate [16], a posteriori error estimate based on hierarchic basis [5, 4], and so on. For the literature, the readers are referred to the books [1, 3, 12, 14
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Urban Terrorism in Contemporary Europening for the ASPJD algorithm, we further investigate the parallel performance of a PETSc based ASPJD eigensolver on the Blue Gene/P, and a QD quintic eigenvalue problem is used as an example to demonstrate its scalability by showing the excellent strong scaling up to 2,048 cores.
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A New a Posteriori Error Estimate for Adaptive Finite Element Methodsa posteriori error estimate has been developed including the residual type a posteriori error estimate [8], recovery type a posteriori error estimate [16], a posteriori error estimate based on hierarchic basis [5, 4], and so on. For the literature, the readers are referred to the books [1, 3, 12, 14
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