Stochastic modelling in process technology /

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Bibliographic Details
Author / Creator:Dehling, Herold.
Edition:1st ed.
Imprint:Amsterdam ; Boston ; London : Elsevier, 2007.
Description:1 online resource (x, 279 pages) : illustrations.
Language:English
Series:Mathematics in science and engineering ; v. 211
Mathematics in science and engineering ; v. 211.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11198330
Hidden Bibliographic Details
Varying Form of Title:Stochastic modeling in process technology
Other authors / contributors:Gottschalk, Timo.
Hoffmann, Alex C.
ISBN:0080548970
9780080548975
0444520260
9780444520265
Notes:Includes bibliographical references (pages 263-274) and index.
Print version record.
Summary:There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computi.
Other form:Print version: Dehling, Herold. Stochastic modelling in process technology. Amsterdam ; London : Elsevier, 2007 9780444520265 0444520260

MARC

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245 1 0 |a Stochastic modelling in process technology /  |c Herold G. Dehling, Timo Gottschalk, Alex C. Hoffmann. 
246 3 |a Stochastic modeling in process technology 
250 |a 1st ed. 
260 |a Amsterdam ;  |a Boston ;  |a London :  |b Elsevier,  |c 2007. 
300 |a 1 online resource (x, 279 pages) :  |b illustrations. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Mathematics in science and engineering ;  |v v. 211 
504 |a Includes bibliographical references (pages 263-274) and index. 
588 0 |a Print version record. 
505 0 |a Front Cover; Stochastic Modelling in Process Technology; Copyright Page; Preface; Table of Contents; Chapter 1 Modeling in Process Technology; Chapter 2 Principles of Stochastic Process modeling; Chapter 3 Batch Fluidized Beds; Chapter 4 Continuous Systems and RTD; Chapter 5 RTD in Continuous Fluidized Beds; Chapter 6 Mixing and Reactions; Chapter 7 Particle Size Manipulation; Chapter 8 Multiphase Systems; Chapter 9 Diffusion Limits; Appendix A Equations for RTD in CSTR and DPF; Bibliography; Index; Mathematics in Science and Engineering. 
520 |a There is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling. The technique is based on computi. 
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650 0 |a Stochastic models.  |0 http://id.loc.gov/authorities/subjects/sh2005004376 
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650 7 |a TECHNOLOGY & ENGINEERING  |x Industrial Engineering.  |2 bisacsh 
650 7 |a TECHNOLOGY & ENGINEERING  |x Manufacturing.  |2 bisacsh 
650 7 |a Manufacturing processes  |x Mathematical models.  |2 fast  |0 (OCoLC)fst01008179 
650 7 |a Stochastic models.  |2 fast  |0 (OCoLC)fst01737780 
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