Chemical Reactor Analysis and Design Fundamentals
Rawlings, J. B. and Ekerdt, J.G.
Nob Hill Pub.
This textbook, designed for undergraduate and graduate chemical engineering courses, presents several new and emerging topics not described in any other textbooks, and exploits the recent advances in computing software and hardware to streamline and reorganize many of the traditional topics.
Seamless integration of modern computing methods. The largest technological change of our generation is the explosion in computing and communications technology. This text takes full advantage of these advances to prepare students to use computational methods for solving reactor modeling problems. It contains 60 worked examples and 248 figures. We support Matlab and Octave–a compatible, freely available language–for all calculations presented in the text. Many of the 138 exercises develop student expertise in computational methods for solving reactor problems.
Parameter estimation. This text devotes an entire chapter to presenting the best optimization methods for estimating model parameters from data. These methods provide a solid foundation for both students and practicing engineers in up-to-date data analysis. Advances in computational software and hardware make this approach feasible for the first time at the undergraduate level.
Chemical reactor synthesis. This text introduces the student to some recent and surprising new results on a traditional topic: chemical reactor synthesis. How many CSTRs are required to achieve the conversion and yield achieved in a PFR if one allows separation? How many are required without separation? Do mixing limits really bound reactor performance limits? Answers to these practical questions are explored.
Stochastic simulation. The chemical engineering profession is positioning itself as the engineering discipline to embrace engineering at the molecular scale, and we need to teach our undergraduate students stochastic kinetic modeling in addition to the traditional continuum modeling approaches for material and energy balances. This text presents stochastic simulation methods and relevant biological examples to introduce undergraduate as well as graduate students to this exciting area.
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