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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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书目名称Domain Decomposition Methods in Science and Engineering XIX
编辑Yunqing Huang,Ralf Kornhuber,Jinchao Xu
视频video
丛书名称Lecture Notes in Computational Science and Engineering
图书封面Titlebook: Domain Decomposition Methods in Science and Engineering XIX;  Yunqing Huang,Ralf Kornhuber,Jinchao Xu Conference proceedings 2011 Springer-
描述These are the proceedings of the 19th international conference on domain decomposition methods in science and engineering. Domain decomposition methods are iterative methods for solving the often very large linear or nonlinear systems of algebraic equations that arise in various problems in mathematics, computational science, engineering and industry. They are designed for massively parallel computers and take the memory hierarchy of such systems into account. This is essential for approaching peak floating point performance. There is an increasingly well-developed theory which is having a direct impact on the development and improvement of these algorithms.
出版日期Conference proceedings 2011
关键词domain decomposition; finite elements; parallel computing; preconditioned conjugate gradients
版次1
doihttps://doi.org/10.1007/978-3-642-11304-8
isbn_softcover978-3-642-26569-3
isbn_ebook978-3-642-11304-8Series ISSN 1439-7358 Series E-ISSN 2197-7100
issn_series 1439-7358
copyrightSpringer-Verlag Berlin Heidelberg 2011
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978-3-642-26569-3Springer-Verlag Berlin Heidelberg 2011
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Lecture Notes in Computational Science and Engineeringhttp://image.papertrans.cn/e/image/282492.jpg
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Newton-Krylov-Schwarz Method for a Spherical Shallow Water Model*In this paper we study the application of Newton-Krylov-Schwarz method to fully implicit, fully coupled solution of a global shallow water model. In particular, we are interested in developing a scalable parallel solver when the shallow water equations (SWEs) are discretized on the cubed-sphere grid using a second-order finite volume method.
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Domain Decomposition and ,-Adaptive Finite Elementst of certain a posteriori error estimates for high order finite elements based on superconvergence [7–9].We wanted to create an environment where these estimates could be evaluated in terms of their ability to estimate global errors for a wide range of problems, and to be used as the basis for adaptive enrichment algorithms.
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