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  3. Mathematical Modeling in Chemical Engineering
  • Cited by 42
Publisher:
Cambridge University Press
Online publication date:
June 2014
Print publication year:
2014
Online ISBN:
9781107279124
DOI:
https://doi.org/10.1017/CBO9781107279124
Subjects:
Mathematics, Computational Science, Engineering, Chemical Engineering
Information

Book description

A solid introduction to mathematical modeling for a range of chemical engineering applications, covering model formulation, simplification and validation. It explains how to describe a physical/chemical reality in mathematical language and how to select the type and degree of sophistication for a model. Model reduction and approximation methods are presented, including dimensional analysis, time constant analysis and asymptotic methods. An overview of solution methods for typical classes of models is given. As final steps in model building, parameter estimation and model validation and assessment are discussed. The reader is given hands-on experience of formulating new models, reducing the models and validating the models. The authors assume the knowledge of basic chemical engineering, in particular transport phenomena, as well as basic mathematics, statistics and programming. The accompanying problems, tutorials, and projects include model formulation at different levels, analysis, parameter estimation and numerical solution.

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Contents

Contents
References
Bibliography
Bird, R.B., Stewart, W.E., and Lightfoot, E.N., Transport Phenomena, 2nd edn. New York: Wiley, 2002.
Levenspiel, O., Chemical Reaction Engineering, 3rd edn. New York: Wiley, 1999.
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Draper, N.R. and Smith, H., Applied Regression Analysis, 3rd edn. New York: John Wiley & Sons, 1998.
Chatfield, C., Statistics for Technology, 3rd edn. London: Chapman and Hall, 1983.
Mendenhall, W. and Sincich, T., A Second Course in Statistics Regression Analysis, 6th edn. Upper Saddle River, NJ: Pearson Education International, 2003.
Devore, J. and Farnum, N., Applied Statistics for Engineers and Scientists, 2nd edn. Belmont, CA: Thomson, 2005.
Montgomery, D.C., Design and Analysis of Experiments, 7th edn. Hoboken, NJ: John Wiley & Sons, 2009.

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