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Meshfree Methods for Partial Differential Equations II (Lecture Notes in Computational Science and Engineering Book 43) 🔍
Michael Griebel; Marc Alexander Schweitzer; International Workshop on Meshfree Methods for Partial Differential Equations Springer-Verlag Berlin and Heidelberg GmbH & Co. K, Lecture Notes in Computational Science and Engineering, Lecture Notes in Computational Science and Engineering, 1, 2005
English [en] · German [de] · PDF · 7.1MB · 2005 · 📘 Book (non-fiction) · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save
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The numerical treatment of partial differential equations with particle methods and meshfree discretization techniques is a very active research field both in the mathematics and engineering community. Due to their independence of a mesh, particle schemes and meshfree methods can deal with large geometric changes of the domain more easily than classical discretization techniques. Furthermore, meshfree methods offer a promising approach for the coupling of particle models to continuous models. This volume of LNCSE is a collection of the papers from the proceedings of the Second International Workshop on Meshfree Methods held in September 2003 in Bonn. The articles address the different meshfree methods (SPH, PUM, GFEM, EFGM, RKPM, etc.) and their application in applied mathematics, physics and engineering. The volume is intended to foster this new and exciting area of interdisciplinary research and to present recent advances and results in this field.
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lgli/Griebel M., Schweitzer M. (Editors) Meshfree Methods for Partial Differential Equations II (Springer, 2005)(306s).pdf
Alternative filename
lgrsnf/Griebel M., Schweitzer M. (Editors) Meshfree Methods for Partial Differential Equations II (Springer, 2005)(306s).pdf
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scihub/10.1007/b138605.pdf
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zlib/Mathematics/Numerical Analysis/Michael Griebel, Marc Alexander Schweitzer/Meshfree Methods for Partial Differential Equations II_645005.pdf
Alternative title
Python Scripting for Computational Science (Texts in Computational Science and Engineering) (v. 3)
Alternative title
Computational Partial Differential Equattions : Numerical Methods and Diffpack Programming
Alternative title
Scientific Computing with MATLAB (Texts in Computational Science and Engineering 2)
Alternative title
Introduction to scientific computing : problems and exercises solved by MATLAB
Alternative author
Langtangen, Hans P., Langtangen, Hans Petter
Alternative author
Quarteroni, Alfio, Saleri, Fausto
Alternative author
Alfio Quarteroni; Fausto Saleri
Alternative author
Hans Petter Langtangen
Alternative publisher
Springer Spektrum. in Springer-Verlag GmbH
Alternative publisher
Steinkopff. in Springer-Verlag GmbH
Alternative publisher
Springer London, Limited
Alternative edition
Texts in computational science and engineering,, 1, 2nd ed., Berlin, New York, Germany, 2003
Alternative edition
Texts in computational science and engineering -- 1, 2. ed., Berlin [etc.], Germany, 2003
Alternative edition
Texts in computational science and engineering : TCSE -- 3, Berlin [etc.], Germany, 2004
Alternative edition
Lecture Notes in Computational Science and Engineering, 43, Berlin, Heidelberg, 2005
Alternative edition
Texts in computational science and engineering,, 3, Berlin, New York, Germany, 2004
Alternative edition
Springer Nature (Textbooks & Major Reference Works), Berlin, Heidelberg, 2012
Alternative edition
Springer Nature (Textbooks & Major Reference Works), Berlin, Heidelberg, 2004
Alternative edition
Lecture notes in computational science and engineering -- 43, Germany, 2005
Alternative edition
Texts in computational science and engineering, 2nd ed, Berlin, 2002
Alternative edition
Texts in computational science and engineering, v. 2, London, 2003
Alternative edition
Texts in computational science and engineering, 2, Berlín, 2003
Alternative edition
1 edition, January 12, 2005
Alternative edition
1 edition, August 27, 2003
Alternative edition
Germany, Germany
Alternative edition
2nd, US, 2003
Alternative edition
2005, 2004
Alternative edition
2005, 2006
Alternative edition
1, 2004
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类型: 图书
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出版日期: 2004.09
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出版社: Springer
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页码: 726
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开本: $186.80
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价格: 9.1 x 6.3 x 1.3 inches
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丛书名: Texts in Computational Science and Engineering Ser
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出版日期: 2003
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页码: 855
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开本: USD 86.95
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价格: 23.500x15.500 cm
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出版日期: 2003.03
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页码: 881
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开本: $86.95
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价格: 9.6 x 6.4 x 1.5 inches
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出版日期: 2003.01
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出版社: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
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Includes bibliographical references (p. [715]-716) and index.
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Includes bibliographical references (p. [833]-842) and index.
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Alternative description
The second edition features lots of improvements and new material. The most significant additions include - finite difference methods and implementations for a 1D time-dependent heat equation (Chapter 1. 7. 6), - a solver for vibration of elastic structures (Chapter 5. 1. 6), - a step-by-step instruction of how to develop and test Diffpack programs for a physical application (Chapters 3. 6 and 3. 13), - construction of non-trivial grids using super elements (Chapters 3. 5. 4, 3. 6. 4, and 3. 13. 4), - additional material on local mesh refinements (Chapter 3. 7), - coupling of Diffpack with other types of software (Appendix B. 3) - high-level programming offinite difference solvers utilizing the new stencil (finite difference operator) concept in Diffpack (Appendix D. 8). Many of the examples, projects, and exercises from the first edition have been revised and improved. Some new exercises and projects have also been added. A hopefully very useful new feature is the compact overview of all the program examples in the book and the associated software files, presented in Chapter 1. 2. Errors have been corrected, many explanations have been extended, and the text has been upgraded to be compatible with Diffpack version 4. 0. The major difficulty when developing programs for numerical solution of partial differential equations is to debug and verify the implementation. This requires an interplay between understanding the mathematical model,the in­ volved numerics, and the programming tools.
Alternative description
The primary purpose of this book is to help scientists and engineers work­ ing intensively with computers to become more productive, have more fun, and increase the reliability of their investigations. Scripting in the Python programming language can be a key tool for reaching these goals [27,29]. The term scripting means different things to different people. By scripting I mean developing programs of an administering nature, mostly to organize your work, using languages where the abstraction level is higher and program­ ming is more convenient than in Fortran, C, C++, or Java. Perl, Python, Ruby, Scheme, and Tel are examples of languages supporting such high-level programming or scripting. To some extent Matlab and similar scientific com­ puting environments also fall into this category, but these environments are mainly used for computing and visualization with built-in tools, while script­ ing aims at gluing a range of different tools for computing, visualization, data analysis, file/directory management, user interfaces, and Internet communi­ cation. So, although Matlab is perhaps the scripting language of choiee in computational science today, my use of the term scripting goes beyond typi­ cal Matlab scripts. Python stands out as the language of choice for scripting in computational science because of its very elean syntax, rieh modulariza­ tion features, good support for numerical computing, and rapidly growing popularity. What Scripting is About.
Alternative description
'It is important to prove, is more but it important to improve.'This textbook is an introduction to Scientific Computing. We will illustrate several numerical methods for the computer solution of cer­ tain classes of mathematical problems that cannot be faced by paper and pencil. We will show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions by polynomials and construct accurate approximations for the solution of differential equations. With this aim, in Chapter 1 we will illustrate the rules of the game that computers adopt when storing and operating with real and complex numbers, vectors and matrices. In order to make our presentation concrete and appealing we will adopt the programming environment MATLAB ® 1 as a faithful companion. We will gradually discover its principal commands, statements and con­ structs. We will show how to execute all the algorithms that we intro­ duce throughout the book. This will enable us to furnish an immediate quantitative assessment of their theoretical properties such as stability, accuracy and complexity. We will solve several problems that will be raised through exercises and examples, often stemming from specific ap­ plications.
Alternative description
This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions by polynomials and construct accurate approximations for the solution of differential equations. To make the presentation concrete and appealing, the programming environment Matlab is adopted as a faithful companion. All the algorithms introduced throughout the book are shown, thus furnishing an immediate quantitative assessment of their theoretical properties such as stability, accuracy and complexity. The book also contains the solution to several problems raised through exercises and examples, often originating from specific applications. A specific section is devoted to subjects which were not addressed in the book and indicate the bibliographical references for a more comprehensive treatment of the material.
Alternative description
The goal of this book is to teach computational scientists and engineers how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in the easy-to-learn, very high-level language Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries. In short, scripting with Python makes you much more productive, increases the reliability of your scientific work and lets you have more fun - under Unix, Windows and MacIntosh.
Alternative description
<p>This text teaches finite element methods and basic finite difference methods from a computational point of view. It emphasizes developing flexible computer programs using the numerical library Diffpack, which is detailed for problems including model equations in applied mathematics, heat transfer, elasticity, and viscous fluid flow. This edition offers new applications and projects, and all program examples are available on the Internet.</p>
Alternative description
"This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions by polynomials and construct accurate approximations for the solution of differential equations."--Jacket.
Alternative description
As indicated by Chaubal et al. [CHA97], "complex fluid" is the term commonly used to describe a wide class of liquid-like materials, in which the relaxation time towards the equilibrium state occurs sufficiently slowly that significant changes in the microstructural configuration, and thus in the macroscopic properties, can be induced by the flow.
Alternative description
What can't be ignored
Nonlinear equations
Approximation of functions and data
Numerical differentiation and integration
Linear systems
Eigenvalues and eigenvectors
Ordinary differential equations
Numerical methods for boundary-value problems
Solutions of the exercises.
Alternative description
001-050_ebook.pdf......Page 1
051-100_ebook_okies.pdf......Page 48
101-150_ebook_okies.pdf......Page 97
151-200_ebook_okies.pdf......Page 146
201-250_ebook_okies.pdf......Page 194
251-311_ebook_okies.pdf......Page 243
Alternative description
"This volume consists of articles which address the different meshfree methods and their application in applied mathematics, physics and engineering."--Résumé de l'éditeur
Alternative description
In this book we will systematically use elementary mathematical concepts which the reader should know already, yet he or she might not recall them immediately.
Alternative description
Lecture Notes in Computational Science and Engineering
Erscheinungsdatum: 02.12.2004
date open sourced
2010-02-18
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