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.
Numerical Methods for Chemical Engineering
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Book Description
Suitable for a first year graduate course, this textbook unites applications of numerical mathematics and scientific computing to the practise of chemical engineering. The methods are developed at a level of mathematics suitable for graduate engineering. MATLAB is integrated within each chapter and numerous examples in chemical engineering are provided.
About the Author
Kenneth J Beers has been Assistant Professor at MIT since the year 2000. He has taught extensively across the engineering discipline at both the undergraduate and graduate level. This book is a result of the sucessful course the author devised at MIT for numerical methods applied to chemical engineering.
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1 of 1 people found the following review helpful:
5.0 out of 5 stars
excellent intro to applied math, not just for chemical engineers,
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This review is from: Numerical Methods for Chemical Engineering: Applications in MATLAB (Hardcover)
This is extremely well written, combining both intuition and rigour. It has good accompanying matlab demos. It should be of interest to many people who use numerical methods (integration, optimization, eigen analysis, etc), not just chemical engineers.
4.0 out of 5 stars
Alot of extraneous info, but still very good,
By clustro "clustro" (clustro) - See all my reviews
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This review is from: Numerical Methods for Chemical Engineering: Applications in MATLAB (Hardcover)
Its a good book. There is a little too much focus on proof and derivation, but you can still just skim those parts and study the algorithms intently, and you will be just fine.
Very broad in scope; covers multiple linear equations, multiple nonlinear equations, optimization w/ gradient search and stochastic search, and monte-carlo methods. The section on stochastic differential equations is somewhat lacking though.
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Inside This Book
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matrix eigenvalue analysis, weak line search, statistics toolkit, multiresponse regression, dynamic concentration profiles, optimization toolkit, dogleg method, tubular chemical reactor, batch reactor data, protein expression data, kth experiment, following code computes, multiresponse data, composite data sets, nonlinear algebraic systems, posterior predictions, marginal posterior density, approximate posterior density, trust radius, important probability distributions, mole balance, drop tolerance, credible regions, descent criterion, quadratic expansion Key Phrases - Capitalized Phrases (CAPs): (learn more)
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matrix eigenvalue analysis, weak line search, statistics toolkit, multiresponse regression, dynamic concentration profiles, optimization toolkit, dogleg method, tubular chemical reactor, batch reactor data, protein expression data, kth experiment, following code computes, multiresponse data, composite data sets, nonlinear algebraic systems, posterior predictions, marginal posterior density, approximate posterior density, trust radius, important probability distributions, mole balance, drop tolerance, credible regions, descent criterion, quadratic expansion Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Trajectory of Newton, Problems Table New!
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Front Cover | Table of Contents | First Pages | Index | Surprise Me!
Citations (learn more)
This book cites 39
books:
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- Finite Elements for Analysis and Design: Computational Mathematics and Applications Series by J. E. Akin in Back Matter
- Linear Algebra: Supplementary Notes & Problems by E. L. Cohen in Back Matter
- Ordinary Differential Equations (Universitext) by Vladimir I. Arnold in Back Matter
- Linear Operator Theory in Engineering and Science (Applied Mathematical Sciences) by Arch W. Naylor in Back Matter
- Monte Carlo Methods in Bayesian Computation (Springer Series in Statistics) by Ming-Hui Chen in Back Matter
See all 39 books this book cites
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