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Discretization Methods and Iterative Solvers Based on Domain Decomposition, Barbara I. Wohlmuth


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Автор: Barbara I. Wohlmuth
Название:  Discretization Methods and Iterative Solvers Based on Domain Decomposition
ISBN: 9783540410836
Издательство: Springer
Классификация:


ISBN-10: 354041083X
Обложка/Формат: Paperback
Страницы: 199
Вес: 0.31 кг.
Дата издания: 27.02.2001
Серия: Lecture Notes in Computational Science and Engineering
Язык: English
Издание: Softcover reprint of
Иллюстрации: 25 tables, black and white; 5 illustrations, black and white; x, 199 p. 5 illus.
Размер: 234 x 156 x 12
Читательская аудитория: Postgraduate, research & scholarly
Основная тема: Mathematics
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Domain decomposition methods provide powerful and flexible tools for the numerical approximation of partial differential equations arising in the modeling of many interesting applications in science and engineering.


Dirichlet-Dirichlet Domain Decomposition Methods For Elliptic Problems: H And Hp Finite Element Discretizations

Автор: Korneev Vadim Glebiovich Et Al
Название: Dirichlet-Dirichlet Domain Decomposition Methods For Elliptic Problems: H And Hp Finite Element Discretizations
ISBN: 9814578452 ISBN-13(EAN): 9789814578455
Издательство: World Scientific Publishing
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Цена: 24552.00 р.
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Описание:

Domain decomposition (DD) methods provide powerful tools for constructing parallel numerical solution algorithms for large scale systems of algebraic equations arising from the discretization of partial differential equations. These methods are well-established and belong to a fast developing area. In this volume, the reader will find a brief historical overview, the basic results of the general theory of domain and space decomposition methods as well as the description and analysis of practical DD algorithms for parallel computing. It is typical to find in this volume that most of the presented DD solvers belong to the family of fast algorithms, where each component is efficient with respect to the arithmetical work. Readers will discover new analysis results for both the well-known basic DD solvers and some DD methods recently devised by the authors, e.g., for elliptic problems with varying chaotically piecewise constant orthotropism without restrictions on the finite aspect ratios.

The hp finite element discretizations, in particular, by spectral elements of elliptic equations are given significant attention in current research and applications. This volume is the first to feature all components of Dirichlet-Dirichlet-type DD solvers for hp discretizations devised as numerical procedures which result in DD solvers that are almost optimal with respect to the computational work. The most important DD solvers are presented in the matrix/vector form algorithms that are convenient for practical use.

Advances in Discretization Methods

Автор: Ventura
Название: Advances in Discretization Methods
ISBN: 3319412450 ISBN-13(EAN): 9783319412450
Издательство: Springer
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Цена: 20896.00 р.
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Описание: This book gathers selected contributions on emerging research work presented at the International Conference eXtended Discretization MethodS (X-DMS), held in Ferrara in September 2015. It highlights the most relevant advances made at the international level in the context of expanding classical discretization methods, like finite elements, to the numerical analysis of a variety of physical problems. The improvements are intended to achieve higher computational efficiency and to account for special features of the solution directly in the approximation space and/or in the discretization procedure. The methods described include, among others, partition of unity methods (meshfree, XFEM, GFEM), virtual element methods, fictitious domain methods, and special techniques for static and evolving interfaces. The uniting feature of all contributions is the direct link between computational methodologies and their application to different engineering areas.

The Method of Discretization in Time and Partial Differential Equations

Автор: K. Rektorys
Название: The Method of Discretization in Time and Partial Differential Equations
ISBN: 9027713421 ISBN-13(EAN): 9789027713421
Издательство: Springer
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Цена: 15372.00 р.
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Developments and Applications of Block Toeplitz Iterative Solvers

Автор: Xiao-Qing Jin
Название: Developments and Applications of Block Toeplitz Iterative Solvers
ISBN: 9048161061 ISBN-13(EAN): 9789048161065
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Toeplitz systems arise in a variety of applications in mathematics, scientific computing, and engineering, such as image processing, numerical differential equations and integral equations, time series analysis, and control theory. This title contains the advanced developments in the use of iterative methods to block Toeplitz systems.

Domain Decomposition Methods in Optimal Control of Partial Differential Equations

Автор: John E. Lagnese; G?nter Leugering
Название: Domain Decomposition Methods in Optimal Control of Partial Differential Equations
ISBN: 3034896107 ISBN-13(EAN): 9783034896108
Издательство: Springer
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Описание: While domain decomposition methods have a long history dating back well over one hundred years, it is only during the last decade that they have become a major tool in numerical analysis of partial differential equations.

Discretization Methods for Stable Initial Value Problems

Автор: E. Gekeler
Название: Discretization Methods for Stable Initial Value Problems
ISBN: 3540128808 ISBN-13(EAN): 9783540128809
Издательство: Springer
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Цена: 6288.00 р.
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Error Estimation and Adaptive Discretization Methods in Computational Fluid Dynamics

Автор: Timothy J. Barth; Herman Deconinck
Название: Error Estimation and Adaptive Discretization Methods in Computational Fluid Dynamics
ISBN: 3642078419 ISBN-13(EAN): 9783642078415
Издательство: Springer
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Цена: 23058.00 р.
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Описание: As computational fluid dynamics (CFD) is applied to ever more demanding fluid flow problems, the ability to compute numerical fluid flow solutions to a user specified tolerance as well as the ability to quantify the accuracy of an existing numerical solution are seen as essential ingredients in robust numerical simulation.


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