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Stochastic modelling in process technology /

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 syste...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Dehling, Herold
Otros Autores: Gottschalk, Timo, Hoffmann, Alex C.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam ; Boston ; London : Elsevier, 2007.
Edición:1st ed.
Colección:Mathematics in science and engineering ; v. 211.
Temas:
Acceso en línea:Texto completo
Texto completo
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MARC

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100 1 |a Dehling, Herold. 
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. 
650 0 |a Manufacturing processes  |x Mathematical models. 
650 0 |a Stochastic models. 
650 6 |a Fabrication  |0 (CaQQLa)201-0011494  |x Mod�eles math�ematiques.  |0 (CaQQLa)201-0379082 
650 6 |a Mod�eles stochastiques.  |0 (CaQQLa)201-0427106 
650 7 |a TECHNOLOGY & ENGINEERING  |x Industrial Technology.  |2 bisacsh 
650 7 |a TECHNOLOGY & ENGINEERING  |x Technical & Manufacturing Industries & Trades.  |2 bisacsh 
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 
700 1 |a Gottschalk, Timo. 
700 1 |a Hoffmann, Alex C. 
776 0 8 |i Print version:  |a Dehling, Herold.  |t Stochastic modelling in process technology.  |d Amsterdam ; London : Elsevier, 2007  |z 9780444520265  |z 0444520260  |w (OCoLC)148739184 
830 0 |a Mathematics in science and engineering ;  |v v. 211. 
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