LEADER 04190nam 2200565Ia 450 001 9910953683803321 005 20251117063430.0 010 $a1-60876-419-2 035 $a(CKB)1000000000787696 035 $a(EBL)3018421 035 $a(SSID)ssj0000199131 035 $a(PQKBManifestationID)12056101 035 $a(PQKBTitleCode)TC0000199131 035 $a(PQKBWorkID)10184886 035 $a(PQKB)11057061 035 $a(MiAaPQ)EBC3018421 035 $a(Au-PeEL)EBL3018421 035 $a(CaPaEBR)ebr10660282 035 $a(OCoLC)923658307 035 $a(BIP)22844953 035 $a(EXLCZ)991000000000787696 100 $a20080725d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMathematical modelling approaches for optimization of chemical processes /$fGabriela Corsano ... [et al.] 205 $a1st ed. 210 $aHauppauge, N.Y. $cNova Science Publishers$dc2009 215 $a1 online resource (103 p.) 300 $aDescription based upon print version of record. 311 08$a1-60456-942-5 320 $aIncludes bibliographical references (p. [83]-85) and index. 327 $aIntro -- MATHEMATICAL MODELING APPROACHES FOR OPTIMIZATION OF CHEMICAL PROCESSES -- NOTICE TO THE READER -- CONTENTS -- PREFACE -- INTRODUCTION -- DEFINITIONS -- BATCH AND SEMI-CONTINUOUS UNITS -- SINGLE PRODUCT, MULTIPRODUCT AND MULTIPURPOSE BATCH PLANTS -- OPTIMIZATION MODEL DECISIONS: SYNTHESIS, DESIGN, OPERATION, SCHEDULING AND PLANNING -- MATHEMATICAL FORMULATIONS -- LITERATURE REVIEW -- WORK OUTLINE -- NLP SUPERSTRUCTURE MODELING FOR THE OPTIMAL SYNTHESIS, DESIGN AND OPERATION IN A BATCH PLANT -- 3.1. INTRODUCTION -- 3.2. MODEL FORMULATION -- 3.3. FERMENTATION PROCESS FOR ETHANOL PRODUCTION -- 3.4. EXAMPLE RESOLUTION -- 3.5. A COMPARISON WITH THE TRADITIONAL APPROACH -- 3.6. CONCLUSIONS AND OUTLOOK ON THE PROPOSED SUPERSTRUCTURE MODELING -- SYNTHESIS AND DESIGN OF MULTIPRODUCT/MULTIPURPOSE BATCH PLANTS: A HEURISTIC APPROACH FOR DETERMINING MIXED PRODUCT CAMPAIGNS -- 4.1. INTRODUCTION -- 4.2. MODEL ASSUMPTIONS -- 4.3. SOLUTION PROCEDURE -- 4.4. MATHEMATICAL MODELING -- 4.4.1. Relaxed Model -- 4.4.2. Multiproduct Campaign Model -- 4.5. STUDY CASE -- Sequential Multipurpose Plant: Torula Yeast, Brandy and Bakery Yeast Production Integrated to a Sugar Plant -- 4.5.1. B-T Sequence Campaign for Fermentation Stage and T-B for Semi-continuous Stages (B-T / T-B) -- 4.5.2. B-T Sequence Campaign for all the Stages -- 4.5.3. B-B-T Sequence Campaign for all the Stages -- 4.6. CONCLUSIONS AND OUTLOOK ON THE PROPOSED HEURISTIC APPROACH FOR MIXED PRODUCT CAMPAIGN MODEL -- PROCESS INTEGRATION:MATHEMATICAL MODELING FOR THE OPTIMAL SYNTHESIS, DESIGN, OPERATION AND PLANNING OF A MULTIPLANT COMPLEX -- 5.1. INTRODUCTION -- 5.2. MODEL FORMULATION -- 5.3. MULTIPLANT COMPLEX TO PRODUCE DERIVATIVES FROM SUGAR CANE -- 5.4. RESULTS AND ANALYSIS -- EXAMPLE -- 5.5. CONCLUSIONS AND OUTLOOK ON THE PROPOSED MULTIPLANT INTEGRATION MODEL. 327 $aGENERAL SUMMARY AND SUGGESTIONS FOR FURTHER READING -- REFERENCES -- INDEX. 330 $aMathematical modelling is a powerful tool for solving optimisation problems in chemical engineering. In this work several models are proposed aimed at helping to make decisions about different aspects of the processes lifecycle, from the synthesis and design steps up to the operation and scheduling. Using an example of the Sugar Cane industry, several models are formulated and solved in order to assess the trade-offs involved in optimisation decisions. Thus, the power and versatility of mathematical modelling in the area of chemical processes optimisation is analysed and evaluated. 606 $aChemical processes 606 $aMathematical optimization 615 0$aChemical processes. 615 0$aMathematical optimization. 676 $a660/.28 701 $aCorsano$b Gabriela$01872214 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910953683803321 996 $aMathematical modelling approaches for optimization of chemical processes$94481299 997 $aUNINA