LEADER 04213nam 2200637Ia 450 001 9910784595303321 005 20200520144314.0 010 $a1-281-11981-4 010 $a9786611119812 010 $a0-08-054897-0 035 $a(CKB)1000000000357914 035 $a(EBL)305660 035 $a(OCoLC)476083907 035 $a(SSID)ssj0000251558 035 $a(PQKBManifestationID)11188696 035 $a(PQKBTitleCode)TC0000251558 035 $a(PQKBWorkID)10189045 035 $a(PQKB)10016780 035 $a(Au-PeEL)EBL305660 035 $a(CaPaEBR)ebr10188662 035 $a(CaONFJC)MIL111981 035 $a(MiAaPQ)EBC305660 035 $a(EXLCZ)991000000000357914 100 $a20070604d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStochastic modelling in process technology$b[electronic resource] /$fHerold G. Dehling, Timo Gottschalk, Alex C. Hoffman 210 $aAmsterdam ;$aLondon $cElsevier$d2007 215 $a1 online resource (291 p.) 225 1 $aMathematics in science and engineering ;$vv. 211 300 $aDescription based upon print version of record. 311 $a0-444-52026-0 320 $aIncludes bibliographical references (p. 263-274) and index. 327 $aCover; Table of Contents; Preface; Chapter 1 Modeling in Process Technology; 1.1 Deterministic Modeling; 1.2 Stochastic modeling-an Example; Chapter 2 Principles of Stochastic Process modeling; 2.1 Stochastic Process Generalities; 2.2 Markov Processes; 2.3 Markov Chains; 2.4 Long-Term Behavior of Markov Chains; 2.5 Diffusion processes; 2.6 First Exit Times and RTD Curves; Chapter 3 Batch Fluidized Beds; 3.1 Flow Regimes; 3.2 Bubbling Beds; 3.3 Slugging Fluidized Beds; 3.4 Stochastic Model Incorporating Interfering Particles; Chapter 4 Continuous Systems and RTD; 4.1 Theory of Danckwerts 327 $a4.2 Subsequent Work4.3 Danckwerts' Law Revisited; 4.4 RTD for Complex Systems; Chapter 5 RTD in Continuous Fluidized Beds; 5.1 Types of beds considered here; 5.2 Bubbling bed; 5.3 Fluidized Bed Riser; Chapter 6 Mixing and Reactions; 6.1 Network-of-Zones Modeling; 6.2 Modeling of Chemical Reactions; Chapter 7 Particle Size Manipulation; 7.1 Physical Phenomena; 7.2 Principles of PBM; 7.3 PBM for High-Shear Granulation; 7.4 Analysis of a Grinding Process; Chapter 8 Multiphase Systems; 8.1 Multiphase System for Bubbling Bed; 8.2 Gulf Streaming in Fluidized beds 327 $a8.3 Extension of the Model to include Gulf Streaming8.4 Quantification of the Model Parameters; 8.5 Model Validation with Data; 8.6 Review of Too et al.; 8.7 Danckwerts' law for a Multiphase Systems; 8.8 The abstract Multiphase System; Chapter 9 Diffusion Limits; 9.1 Fokker-Planck equation; 9.2 Limit Process; Appendix A Equations for RTD in CSTR and DPF; A.1 Ideally Mixed Vessels (CSTRs) in Series; A.2 Plug Flow with Axial Dispersion; Bibliography; Index; Mathematics in Science and Engineering 330 $aThere is an ever increasing need for modelling complex processes reliably. Computational modelling techniques, such as CFD and MD may be used as tools to study specific systems, but their emergence has not decreased the need for generic, analytical process models. Multiphase and multicomponent systems, and high-intensity processes displaying a highly complex behaviour are becoming omnipresent in the processing industry. This book discusses an elegant, but little-known technique for formulating process models in process technology: stochastic process modelling.The technique is based on 410 0$aMathematics in science and engineering ;$vv. 211. 606 $aManufacturing processes$xMathematical models 606 $aStochastic models 615 0$aManufacturing processes$xMathematical models. 615 0$aStochastic models. 676 $a670.15118 700 $aDehling$b Herold$0307516 701 $aGottschalk$b Timo$0307517 701 $aHoffmann$b Alex C$0317940 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784595303321 996 $aStochastic modelling in process technology$9710376 997 $aUNINA