Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB

Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB
Author :
Publisher : Springer
Total Pages : 416
Release :
ISBN-10 : 9783319067902
ISBN-13 : 3319067907
Rating : 4/5 (02 Downloads)

Book Synopsis Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB by : Alain Vande Wouwer

Download or read book Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB written by Alain Vande Wouwer and published by Springer. This book was released on 2014-06-07 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB shows the reader how to exploit a fuller array of numerical methods for the analysis of complex scientific and engineering systems than is conventionally employed. The book is dedicated to numerical simulation of distributed parameter systems described by mixed systems of algebraic equations, ordinary differential equations (ODEs) and partial differential equations (PDEs). Special attention is paid to the numerical method of lines (MOL), a popular approach to the solution of time-dependent PDEs, which proceeds in two basic steps: spatial discretization and time integration. Besides conventional finite-difference and element techniques, more advanced spatial-approximation methods are examined in some detail, including nonoscillatory schemes and adaptive-grid approaches. A MOL toolbox has been developed within MATLAB®/OCTAVE/SCILAB. In addition to a set of spatial approximations and time integrators, this toolbox includes a collection of application examples, in specific areas, which can serve as templates for developing new programs. Simulation of ODE/PDE Models with MATLAB®, OCTAVE and SCILAB provides a practical introduction to some advanced computational techniques for dynamic system simulation, supported by many worked examples in the text, and a collection of codes available for download from the book’s page at www.springer.com. This text is suitable for self-study by practicing scientists and engineers and as a final-year undergraduate course or at the graduate level.


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