Chapter Summaries and Final Remarks

An important goal of this book has been to understand the fundamental concepts that constitute the foundations of AR theory. These concepts are by no means exhaustive, but we feel they provide a suitable introduction to the fundamentals of AR theory. Our approach has been instructional, rather than purely academic, to emphasize clarity at the expense of mathematical correctness. The foundational concepts of AR theory are often easy to grasp initially however, these concepts quickly build in complexity, and hasty treatment of the introductory material often results in confusion later on. We urge you to attempt solving as many AR problems as possible provided in this book, as well as apply these concepts to your own problems. 

In Chapter 1, we introduced the story of Sam, Alex, and Donald in order to describe a fundamental problem that is often encountered in design—how do we know when we are the bestl Problems in chemical reactor design (as well as many problems unrelated to chemical reactor design) may often be arranged according to a hierarchy of approaches, which we may not always be mindful of from the beginning. 

But commitment to an approach, in turn, influences the manner in which solutions are implemented later in the design process. These decisions may greatly shape our understanding of the problem, and also the quality of the recommendations that are generated. 

We believe that if designers begin to think about reactor problems in terms of reactor networks—as opposed to single reactors—then more effective designs may be achieved overall. Furthermore, reactive systems involving multiple reactors, termed reactor structures, are necessary when systems involving multiple reactions are involved, and so familiarity with this approach is valuable in achieving the best performance from complex reactive systems. 

even if this information is known and reactor networks are employed in a problem, how do we know if there are not better solutions in existence We must often have an understanding of a performance target with which designs may be benchmarked against, and AR theory is one such approach that can assist in finding these operating targets. 

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