Applications of Markov Chains in Chemical EngineeringElsevier, 1998 M08 26 - 604 páginas Markov chains make it possible to predict the future state of a system from its present state ignoring its past history. Surprisingly, despite the widespread use of Markov chains in many areas of science and technology, their applications in chemical engineering have been relatively meager. A possible reason for this phenomenon might be that books containing material on this subject have been written in such a way that the simplicity of Markov chains has been shadowed by the tedious mathematical derivations. Thus, the major objective of writing this book has been to try to change this situation. There are many advantages, detailed in Chapter 1, of using the discrete Markov-chain model in chemical engineering. Probably, the most important advantage is that physical models can be presented in a unified description via state vector and a one-step transition probability matrix. Consequently, a process is demonstrated solely by the probability of a system to occupy or not occupy a state. The book has been written in an easy and understandable form, where complex mathematical derivations are abandoned. The fundamentals of Markov chains are presented in Chapter 2 with examples from the bible, art and real life problems. An extremely wide collection is given of examples viz., reactions, reactors, reactions and reactors as well as combined processes, including their solution and a graphical presentation of it, all of which demonstrates the usefulness of applying Markov chains in chemical engineering. |
Contenido
| 1 | |
| 6 | |
| 11 | |
Chapter 3 Applications of Markov Chains in Chemical Reactions | 186 |
Chapter 4 Applications of Markov Chains in Chemical Reactors | 334 |
Chapter 5 Applications of Markov Chains in Chemical Processes | 498 |
Nomenclature | 590 |
| 599 | |
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Applications of Markov Chains in Chemical Engineering Abraham Tamir Sin vista previa disponible - 1998 |
Términos y frases comunes
applicable assumed behavior C1 to C4 Chemical Engineering chemical reaction Ci versus computed concentration of species conditional probability configuration considered corresponding defined demonstrating the effect depicted designated distribution Dmax Dmean effect of H enthalpy ergodic exact solution example flow system fluid element following matrix following probabilities following transition probability initial state vector interval introduced into reactor k1At k2At Markov chain solution Markov process mean residence molecules noted numerical solution observed obtained occupation probability one-step transition probability parameters particles perfectly mixed reactors plug flow reactor Poisson process prob{Sk probability of occupying probability of remaining pulse input Px(t random recycle reference flow response of C1 ſº solution is available species f step streams total number tracer transient response transition matrix transition probability matrix vector C(0 vector reads versus t demonstrating yields the following
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Página 2 - God separated the light from the darkness. God called the light Day, and the darkness he called Night.
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Página 2 - I rose in the morning to give my child suck, behold it was dead: but when I had considered it in the morning, behold it was not my son, which I did bear." And the other woman said: " Nay; but the living is my son, and the dead is thy son.
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Referencias a este libro
Handbook of Conveying and Handling of Particulate Solids Avi Levy,Haim Kalman Sin vista previa disponible - 2001 |