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Computational Partial Differential Equations [Hardcover]

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Item description for Computational Partial Differential Equations by Hans P. Langtangen...

The target audience of this book is students and researchers in computational sciences who need to develop computer codes for solving partial differential equations. The exposition is focused on numerics and software related to mathematical models in solid and fluid mechanics. The book teaches finite element methods, and basic finite difference methods from a computational point of view. The main emphasis regards development of flexible computer programs, using the numerical library Diffpack. The application of Diffpack is explained in detail for problems including model equations in applied mathematics, heat transfer, elasticity, and viscous fluid flow. Diffpack is a modern software development environment based on C++ and object-oriented programming. All the program examples, as well as a test version of Diffpack, are available for free over the Internet. The second edition contains several new applications and projects, improved explanations, correction of errors, and is up to date with Diffpack version 4.0.

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Item Specifications...

Pages   881
Est. Packaging Dimensions:   Length: 9.58" Width: 6.38" Height: 1.48"
Weight:   3.04 lbs.
Binding  Hardcover
Release Date   Mar 10, 2003
Publisher   Springer
ISBN  354043416X  
ISBN13  9783540434160  

Availability  56 units.
Availability accurate as of May 24, 2017 09:45.
Usually ships within one to two business days from La Vergne, TN.
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Product Categories

1Books > Special Features > Formats
2Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Computer Mathematics
3Books > Subjects > Computers & Internet > General
4Books > Subjects > Medicine > General
5Books > Subjects > Professional & Technical > Professional Science > Mathematics > Applied > Differential Equations
6Books > Subjects > Professional & Technical > Professional Science > Mathematics > Mathematical Analysis
7Books > Subjects > Professional & Technical > Professional Science > Mathematics > Number Systems
8Books > Subjects > Science > General
9Books > Subjects > Science > Mathematics > Applied > Differential Equations
10Books > Subjects > Science > Mathematics > General
11Books > Subjects > Science > Mathematics > Mathematical Analysis
12Books > Subjects > Science > Mathematics > Number Systems
13Books > Subjects > Science > Mathematics > Pure Mathematics > Calculus

Reviews - What do customers think about Computational Partial Differential Equations?

learn C++ via the book's examples  Jul 6, 2008
In a way, the book is a throwback to a time when most people learning Fortran were not computer programmers per se, but scientists and engineers who needed to solve some problem using computers. In Langtangen's book, the language of choice is C++. A good choice, given that this edition came out in 2003. C++ has one main advantage over Fortran, in its object oriented ability. The procedural aspect of Fortran has trouble scaling to very large code bodies. However, Langtangen is quick to point out that if you take the time to learn C++ via the book, the coding experience is easily transferred to other languages like Java or even Fortran.

He directs the book towards a student or professional in the sciences or engineering, who has to solve a slew of Partial Differential Equations (PDEs). Often, the equations and boundary conditions mean that numerical analysis is required; analytic solutions are rare. The PDEs might be non-linear, which is another source of complexity and possible instability.

Finite element methods take up a large chunk of the text. The discussion is not restricted to the simple case where the space is divided into an equally spaced grid. He considers cases where you might need variable spacing; with a high concentration of grid points in regions of key interest. For example, think of solving for an electromagnetic field or fluid flow field, around a boundary of high curvature.

For linear systems, there is a foray into solving large matrix equations, where the matrices are sparse. Enough theory is developed to make the algorithms plausible.

Be aware that learning C++ thru this book won't give you all that C++ can do. Specifically, the string manipulations are little needed here. True of most computationally intensive code. But if you are not professionally a programmer, then this relative lack should not be a problem.

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