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Numerical Methods for Chemical Engineering
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    Matias, Jose O. A. Ebrahimpour, Misagh and Le Roux, Galo A. C. 2018. Development and Validation of a Reduced-Index Dynamic Model of an Industrial High-Purity Column. Industrial & Engineering Chemistry Research, Vol. 57, Issue. 5, p. 1531.

    Ridder, Bradley J. Majumder, Aniruddha and Nagy, Zoltan K. 2016. Parametric, Optimization-Based Study on the Feasibility of a Multisegment Antisolvent Crystallizer for in Situ Fines Removal and Matching of Target Size Distribution. Industrial & Engineering Chemistry Research, Vol. 55, Issue. 8, p. 2371.

    Coutu, S. Del Giudice, D. Rossi, L. and Barry, D. A. 2012. Modeling of facade leaching in urban catchments. Water Resources Research, Vol. 48, Issue. 12,

    Saithong, Treenut Painter, Kevin J. Millar, Andrew J. and Jaeger, Johannes 2010. Consistent Robustness Analysis (CRA) Identifies Biologically Relevant Properties of Regulatory Network Models. PLoS ONE, Vol. 5, Issue. 12, p. e15589.


Book 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

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