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Numerical Methods for Chemical Engineering
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Product Description
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.
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.
See all Editorial Reviews
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.
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.
See all Editorial Reviews
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Key Phrases - Statistically Improbable Phrases (SIPs):
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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!
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!
Concordance | Text Stats Browse Sample Pages:
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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