[request_ebook] Numerical Methods for Chemical Engineering: Applications in MATLAB
Author: Kenneth J. Beers
Date: October 30, 2006
ISBN: 0521859719
Pages: 486
Language: English
Publisher: Cambridge University Press
Category: Technical
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Description
- Author: Kenneth J. Beers
- Publisher: Cambridge University Press
- Publish Date: October 30, 2006
- ISBN: 0521859719
- Pages: 486
Suitable for a first year graduate course, this textbook unites the applications of numerical mathematics and scientific computing to the practice of chemical engineering. Written in a pedagogic style, the book describes basic linear and nonlinear algebric systems all the way through to stochastic methods, Bayesian statistics and parameter estimation. These subjects are developed at a level of mathematics suitable for graduate engineering study without the exhaustive level of the theoretical mathematical detail. The implementation of numerical methods in MATLAB is integrated within each chapter and numerous examples in chemical engineering are provided, with a library of corresponding MATLAB programs. This book will provide the graduate student with essential tools required by industry and research alike. Supplementary material includes solutions to homework problems set in the text, MATLAB programs and tutorial, lecture slides, and complicated derivations for the more advanced reader. These are available online at www.cambridge.org/9780521859714.
• Numerous applications specific to chemical engineering and MATLAB integrated into each chapter, with an extensive library of example problems also located on the web • It avoids theoretically detailed mathematics • Contains numerous problems and homework exercises at the end of each chapter categorised according to difficulty with solutions available on the resource site
Contents
1. Linear algebra; 2. Nonlinear algebraic systems; 3. Matrix eigenvalue analysis; 4. Initial value problems; 5. Numerical optimization; 6. Boundary value problems; 7. Probability theory and stochastic simulation; 8. Bayesian statistics and parameter estimation; 9. Fourier analysis.
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