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Tiêu đề Process Integration for Resource Conservation
Tác giả Dominic C. Y. Foo
Trường học Ohio University
Chuyên ngành Chemical Engineering
Thể loại book
Năm xuất bản 2012
Thành phố Boca Raton
Định dạng
Số trang 602
Dung lượng 20,07 MB

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Chemical Engineering “… this excellent book comes at just the right time to teach the next generation of process designers how to ‘save the planet’ more systematically and intelligently.” —Raymond R Tan, De La Salle University–Manila “This book collects all fundamental aspects of process integration to enable readers to address issues related to resource management I strongly recommend this book to everyone interested in the field of process integration.” —Santanu Bandyopadhyay, IIT Bombay “This book serves as good material for process integration … it [also] offers good knowledge of material recovery that helps people [acquire the] basics for doing further research or practical application.” —Cheng-Liang Chen, National Taiwan University “The chapters are written very well and cover all the topics in sufficient detail and clarity … a wonderful and relevant contribution to the field of process integration.” —T Majozi, University of Pretoria K12774 K12774_Cover.indd GREEN CHEMISTRY AND CHEMICAL ENGINEERING PROCESS INTEGRATION FOR RESOURCE CONSERVATION Water minimization Gas recovery Property integration Foo Process Integration for Resource Conservation presents stateof-the-art, cost-effective techniques, including pinch analysis and mathematical optimization, for numerous conservation problems Following the holistic philosophy of process integration, the author emphasizes the goal of setting performance targets ahead of detailed design He explains various industrial examples step by step and offers demo software and other materials online PROCESS INTEGRATION FOR RESOURCE CONSERVATION “… an excellent contribution that will benefit numerous researchers, students, and process engineers and will serve the cause of sustainability worldwide.” —Mahmoud El-Halwagi, Texas A&M University Dominic C Y Foo 6/8/12 3:32 PM PROCESS INTEGRATION FOR RESOURCE CONSERVATION GREEN CHEMISTRY AND CHEMICAL ENGINEERING Series Editor: Sunggyu Lee Ohio University, Athens, Ohio, USA Proton Exchange Membrane Fuel Cells: Contamination and Mitigation Strategies Hui Li, Shanna Knights, Zheng Shi, John W Van Zee, and Jiujun Zhang Proton Exchange Membrane Fuel Cells: Materials Properties and Performance David P Wilkinson, Jiujun Zhang, Rob Hui, Jeffrey Fergus, and Xianguo Li Solid Oxide Fuel Cells: Materials Properties and Performance Jeffrey Fergus, Rob Hui, Xianguo Li, David P Wilkinson, and Jiujun Zhang Efficiency and Sustainability in the Energy and Chemical Industries: Scientific Principles and Case Studies, Second Edition Krishnan Sankaranarayanan, Jakob de Swaan Arons, and Hedzer van der Kooi Nuclear Hydrogen Production Handbook Xing L Yan and Ryutaro Hino Magneto Luminous Chemical Vapor Deposition Hirotsugu Yasuda Carbon-Neutral Fuels and Energy Carriers Nazim Z Muradov and T Nejat Vezirogˇ lu Oxide Semiconductors for Solar Energy Conversion: Titanium Dioxide Janusz Nowotny Lithium-Ion Batteries: Advanced Materials and Technologies Xianxia Yuan, Hansan Liu, and Jiujun Zhang Process Integration for Resource Conservation Dominic C Y Foo GREEN CHEMISTRY AND CHEMICAL ENGINEERING PROCESS INTEGRATION FOR RESOURCE CONSERVATION Dominic C Y Foo CRC Press Taylor & Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742 © 2012 by Taylor & Francis Group, LLC CRC Press is an imprint of Taylor & Francis Group, an Informa business No claim to original U.S Government works Version Date: 20160307 International Standard Book Number-13: 978-1-4398-6049-6 (eBook - PDF) This book contains information obtained from authentic and highly regarded sources Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint Except as permitted under U.S Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers For permission to photocopy or use material electronically from this work, please access www.copyright.com (http:// www.copyright.com/) or contact the Copyright Clearance Center, Inc (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400 CCC is a not-for-profit organization that provides licenses and registration for a variety of users For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com Contents Series Preface xi Foreword xiii Preface xvii Acknowledgments xix Author xxiii How to Make Use of This Book xxv Introduction 1.1 Motivating Examples 1.2 Process Synthesis and Analysis 1.3 Process Integration: A Brief Overview 1.4 Strategies for Material Recovery and Types of RCNs 12 1.5 Problem Statements 14 1.6 Structure of the Book 19 References 19 Data Extraction for Resource Conservation 23 2.1 Segregation for Material Sources 23 2.2 Extraction of Limiting Data for Material Sink for Concentration-Based RCN 25 2.3 Data Extraction for Mass Exchange Processes 28 2.4 Data Extraction for Hydrogen-Consuming Units in Refinery 33 2.5 Data Extraction for Property Integration 36 2.6 Additional Readings 44 Problems 44 References 55 Part I  Insight-Based Pinch Analysis Techniques Graphical Targeting Techniques for Direct Reuse/Recycle 59 3.1 Material Recovery Pinch Diagram 59 3.2 Significance of the Pinch and Insights from MRPD .64 3.3 Targeting for Multiple Resources 71 3.4 Targeting for Threshold Problems 75 3.5 Targeting for Property Integration 78 3.6 Additional Readings 82 Problems 83 References 89 v vi Contents Algebraic Targeting Techniques for Direct Reuse/Recycle 91 4.1 Generic Procedure for Material Cascade Analysis Technique 91 4.2 Targeting for Multiple Fresh Resources 97 4.3 Targeting for Threshold Problems 101 4.4 Targeting for Property Integration with Inferior Property Operator Level 105 Problems 107 References 116 Process Changes for Resource Conservation Networks 119 5.1 Plus–Minus Principle 119 Problems 124 References 126 Algebraic Targeting Approach for Material Regeneration Networks 127 6.1 Types of Interception Units 127 6.2 Targeting for Single Pass Interception Unit 128 6.3 Modeling of Mass Exchange Operation as Interception Unit 141 6.4 Additional Readings 151 Problems 151 References 153 Network Design and Evolution Techniques 155 7.1 Procedure for Nearest Neighbor Algorithm 155 7.2 Design for Direct Material Reuse/Recycle and the Matching Matrix 157 7.3 Design for Material Regeneration Network 166 7.4 Network Evolution Techniques 172 7.4.1 Source Shift Algorithm 173 7.4.2 Material Path Analysis 175 7.5 Additional Readings 182 Problems 183 References 188 Targeting for Waste Treatment and Total Material Networks 191 8.1 Total Material Network 191 8.2 Generic Procedure for Waste Stream Identification 193 8.3 Waste Identification for Material Regeneration Network 196 8.4 Targeting for Minimum Waste Treatment Flowrate 200 8.5 Insights from the WTPD 206 8.6 Additional Readings 209 Problems 210 References 213 Contents vii Synthesis of Pretreatment Network 215 9.1 Basic Modeling of a Partitioning Interception Unit 215 9.2 Pretreatment Pinch Diagram 216 9.3 Insights on Design Principles from PPD 225 9.4 Pretreatment Network Design with Nearest Neighbor Algorithm 226 Problems 228 Reference 229 10 Synthesis of Inter-Plant Resource Conservation Networks 231 10.1 Types of IPRCN Problems 231 10.2 Generic Targeting Procedure for IPRCN 232 10.3 Design of IPRCN 256 10.4 IPRCN with Material Regeneration and Waste Treatment 260 10.5 Additional Readings 267 Problems 267 References 270 11 Synthesis of Batch Material Networks 271 11.1 Types of Batch Resource Consumption Units 271 11.2 Targeting Procedure for Direct Reuse/Recycle in a BMN without Mass Storage System 272 11.3 Targeting Procedure for Direct Reuse/Recycle in a BMN with Mass Storage System 276 11.4 Targeting for Batch Regeneration Network 283 11.5 Design of a BMN 289 11.6 Waste Treatment and Batch Total Network 291 11.7 Additional Readings 294 Problems 295 References 301 Part II  Mathematical Optimization Techniques 12 Synthesis of Resource Conservation Networks: A Superstructural Approach 305 12.1 Superstructural Model for Direct Reuse/Recycle Network 305 12.2 Incorporation of Process Constraints 311 12.3 Capital and Total Cost Estimations 313 12.4 Reducing Network Complexity 320 12.5 Superstructural Model for Material Regeneration Network 323 12.6 Superstructural Model for Inter-Plant Resource Conservation Networks 334 12.7 Additional Readings 346 Problems 349 References 354 viii Contents 13 Automated Targeting Model for Direct Reuse/Recycle Networks 357 13.1 Basic Framework and Mathematical Formulation of ATM 357 13.2 Incorporation of Process Constraints into ATM 364 13.3 ATM for Property Integration with Inferior Operator Level 366 13.4 ATM for Bilateral Problems 371 Problems 378 References 380 14 Automated Targeting Model for Material Regeneration and Pretreatment Networks 383 14.1 Types of Interception Units and Their Characteristics 383 14.2 ATM for RCN with Single Pass Interception Unit of Fixed Outlet Quality Type 384 14.3 ATM for RCN with Single Pass Interception Unit of Removal Ratio Type 393 14.4 Modeling for Partitioning Interception Unit(s) of Fixed Outlet Quality Type 399 14.5 Modeling for Partitioning Interception Unit(s) of Removal Ratio Type 401 14.6 ATM for RCN with Partitioning Interception Unit(s) 404 14.7 ATM for Pretreatment Networks 410 14.8 Additional Readings 417 Problems 417 References 422 15 Automated Targeting Model for Waste Treatment and Total Material Networks 423 15.1 ATM for Waste Treatment Network 423 15.2 ATM for TMN without Waste Recycling 434 15.2.1 TMN with Single Pass Interception Unit of Fixed Outlet Quality Type 434 15.2.2 TMN with Removal Ratio Type Single Pass Interception Unit 436 15.2.3 TMN with Partitioning Interception Unit 436 15.3 ATM for TMN with Waste Recycling 456 15.4 Additional Readings 464 Problems .464 References 467 16 Automated Targeting Model for Inter-Plant Resource Conservation Networks 469 16.1 ATM for Direct Integration Scheme—Direct Material Reuse/Recycle 469 16.2 ATM for Direct Integration Scheme: RCNs with Individual Interception Unit 479 Contents ix 16.3 ATM for IPRCNs with Centralized Utility Facility 490 16.4 Insights from ATM for IPRCN Synthesis 507 16.5 Further Reading 512 Problems 512 References 515 17 Automated Targeting Model for Batch Material Networks 517 17.1 Basic ATM Procedure for Batch Material Networks 517 17.2 ATM for Direct Reuse/Recycle Network 518 17.3 ATM for Batch Regeneration Network 536 17.4 ATM for Batch Total Network 549 17.5 Further Reading 563 Problems 563 References 566 Appendix: Case Studies and Examples 569 Index 573 Automated Targeting Model for Batch Material Networks @BIN (BSTG4); @BIN (BSTG5); ! Constraints for WTN ; ! Waste cascade; S1 = S0 ; S2 = S1 + TRD ; S3 = S2 − WW ; S4 = S3 + ( WWA1 + WWB1 − TR1 ) ; S5 = S4 + ( WWB2 + WWC1 − TR2 ) ; ! No net waste flow enters the first and the last levels; S0 = 0 ; S5 = 0 ; ! Flow balance(s) for treatment unit(s) ; TRD = TR1 + TR2 ; ! Flow constraints of treated wastewater source ; TR1 = ; J4 >= ; J5 >= ; J6 >= ; ! S1-S4 may take negative values ; @free (S1) ; @free (S2) ; @free (S3) ; @free (S4) ; END The following is the solution report generated by LINGO: Global optimal solution found Objective value: Extended solver steps: Total solver iterations: Variable TAC AOC SC OC FWA FWB FWC REA1 REB1 REB2 REC1 TR1 544886.9 79 Value 544886.9 538538.9 27480.56 101.6111 40.00000 0.000000 0.000000 0.000000 0.000000 41.66667 27.77778 2.777778 559 560 Process Integration for Resource Conservation TR2 CSTG1 CSTG2 CSTG3 CSTG4 CSTG5 D1A D0A STCA1 STAB1 D2A STCA2 STAB2 REGA D3A STCA3 STAB3 D4A STCA4 STAB4 WWA1 D5A STCA5 STAB5 E1A E2A E3A E4A E5A E6A D1B D0B STBC1 D2B STBC2 REGB D3B STBC3 D4B STBC4 WWB1 D5B STBC5 WWB2 E1B E2B E3B E4B E5B E6B D1C D0C D2C REGC D3C D4C 30.55556 0.000000 0.000000 0.000000 27480.56 0.000000 0.000000 40.00000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 30.55556 9.444444 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 41.66667 0.000000 41.66667 −33.33333 0.000000 0.000000 22.22222 0.000000 0.000000 0.000000 8.333333 0.000000 0.000000 3.333333 0.000000 0.000000 0.000000 0.000000 0.000000 27.77778 27.77778 −22.22222 0.000000 Automated Targeting Model for Batch Material Networks D5C WWC1 E1C E2C E3C E4C E5C E6C MSB1 MSA1 MSC1 MSB2 MSA2 MSC2 MSB3 MSA3 MSC3 MSB4 MSA4 MSC4 MSB5 MSA5 MSC5 STG1 STG2 STG3 STG4 STG5 BSTG1 BSTG2 BSTG3 BSTG4 BSTG5 M S1 S0 S2 TRD S3 WW S4 S5 J1 J2 J3 J4 J5 J6 0.000000 22.22222 0.000000 0.000000 2.222222 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 30.55556 0.000000 22.22222 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 30.55556 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 1000.000 0.000000 0.000000 33.33333 33.33333 −6.666667 40.00000 0.000000 0.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 The optimization result indicates that the batch total network has a TAC of $545,000 The revised cascade diagrams for all time intervals as well as that for the WTN are shown in Figure 17.14 (impurity load cascades are omitted for the former) As observed in Figure 17.14a, the results are quite similar to the case in Example 17.2 (see Figure 17.10), except that the wastewater flows are now emitted from the concentration levels where 561 562 Process Integration for Resource Conservation t=A k C (ppm) δ0,A = FFW,A = 40 20 100 200 400 –40 δ1,A = δ2,A = 40 δ3,A = δ4,A = t=B δ0,B = FFW,B = δ1,B = FREG,B= 41.67 = 30.56 25 +FWW,A,1 = 9.44 50 δ4,B = δ5,B = (a) –50 = 22.22 41.67 (FRE,B,2) +FWW,B,2 ∑y Fwy,k σ0 = k=1 CT = 20 FTRD = 33.33 k=2 CT = 50 k=3 100 k=4 9.44 (Fww,A,1) 800 8.33 + 22.22 (Fww,B,2 + Fww,C,1) 1,000,000 (b) k=5 = 8.33 50 FD +FWW,C,1 = 22.22 φ1 = σ2 = 33.33 k=2 σ5 = 27.78 (FRE,C,1) Load cascade (kg) k=1 σ4 = δ4,C = δ5,C = σ1 = σ3 = –6.67 δ2,C = 27.78 δ3,C = –22.22 FST,B,C,4 Waste cascade (ton) C (ppm) δ1,C = FREG,C= 27.78 δ2,B = 41.67 –75 δ3,B = –33.33 FST,A,B,4 1,000,000 δ5,A = t=C δ0,C = FFW,C = Fww = 40 FTR1 = 2.77 FTR2 = 30.55 k=3 k=4 k=5 φ2 = φ3 = φ4 = φ5 = φ6 = Figure 17.14 Result of ATM for Example 17.3: (a) water cascade for time intervals A–C (flow in tons) and (b) cascade diagram for WTN the sources exist, i.e., 200 ppm (time interval A—FWW,A,1 = 9.44 tons) and 400 ppm (time intervals B and C—FWW,B,2 = 8.33 tons; FWW,C,1 = 22.22 tons), respectively Similar to the earlier cases, we may make use of the insights in Figure 17.14a or the NNA to design the batch total network For this case, the network structure should take the same form as in Example 17.2 The wastewater flows emitted from the water network are sent to the WTN for end-of-pipe treatment before final discharge The ATM result in Figure 17.14b indicates that the wastewater sources at 400 ppm from time intervals B and C (FTR2 = 30.56 tons) are fully treated On the other hand, only 2.77 tons of wastewater source at 200 ppm (FTR1 from time interval A) is treated, while 6.67 tons (=9.44 – 2.77 tons) of this wastewater source will bypass the treatment unit In other words, only 33.33 tons (FTRD) of the total wastewater flow (FWW = 40 tons) will be treated prior to environmental discharge As mentioned earlier, a water Automated Targeting Model for Batch Material Networks 563 storage tank is needed to mix the treated and bypassed wastewater streams in order to meet the environmental discharge limit of 50 ppm This is similar to the case in Figure 11.9 Hence, the network structure of the batch total network takes the same form as that in Figure 11.10 17.5  Further Reading In this chapter, the ATM has been utilized to optimize for minimum water flows/storage size, as well as the minimum cost solution for a BMN In some cases, space requirement is a critical issue in the batch process plants For such cases, we may incorporate fuzzy optimization techniques within the ATM for trade-off analysis among the minimum flows of freshwater and regeneration, as well as the mass storage size This is reported in the work of Nun et al (2011) Apart from ATM, many other mathematical optimization approaches have also been recently developed Most of these models are based on superstructural approaches (similar to the basic framework in Chapter 12) These include the works of Almató et al (1999), Kim and Smith (2004), Li and Chang (2006); Ng et al (2008), Chen et al (2008, 2009, 2010), Majozi (2005, 2006), Cheng and Chang (2007), Gouws and Majozi (2008), and Majozi and Gouws (2009) A comparison for these techniques may be found in the review paper by Gouws et al (2010) A useful text book for this technique is also available (Majazi, 2010) Problems Water Minimization Problems 17.1 For the batch water network in Problem 11.2 (Kim and Smith, 2004), use ATM to determine the minimum freshwater and wastewater flows for a direct reuse/recycle scheme for the case in tasks: (a) without water storage and (b) with water storage system 17.2 Use ATM to determine the minimum freshwater and wastewater flows for the batch water network in Problem 11.3 (Chen and Lee, 2008), operated in repeated batch mode Also, determine the number and sizes of water storage tanks needed 17.3 Revisit Problem 11.4, where water is used extensively as a washing agent and reaction solvent in an agrochemical manufacturing plant (Majozi et al., 2006) Determine the minimum freshwater and wastewater flows 564 Process Integration for Resource Conservation for direct reuse/recycle scheme for repeated batch processes with a water storage tank Also determine the size of the water storage tank How is the solution different from the one obtained with the insightbased technique (Task (b) in Problem 11.4)? 17.4 Rework the water recovery problem for the batch polyvinyl chloride (PVC) resins manufacturing plant in Problem 11.5 (Chan et al., 2008) Determine the minimum TAC for the water network, assuming that the process has a cycle time of 14.78 h, and an annual operating time of 7982 h The unit costs of freshwater (CTFW) and wastewater (CTWW) are given as $1/ton each The capital cost for water storage tanks is given in Equation 17.24, while piping cost may be ignored The storage cost is annualized to a period of years, with an interest rate of 5% What is the storage size for this case and does it match with that determine using the insight-based approach in Problem 11.5? (note: beware of using a single water source that is available as a continuous stream; the parameter M in Equation 17.27 should take a much larger number; a licensed LINGO software is needed to solve this case, due to the large number of constraints and variables in the ATM) 17.5 Rework the water minimization problem in Example 17.3 (Wang and Smith, 1995) In this case, the treated effluent from the wastewater treatment unit may be recycled in the water network All process and economic data remain identical to that in Example 17.3 Determine the minimum TAC for the water network 17.6 Table 17.3 shows the limiting water data for a water minimization study in a fruit juice production plant (Almató et al., 1999; Li and Chang, 2006; Chen and Lee, 2010; Foo, 2010) Solve the following cases assuming that the plant is operated in repeated batch mode with a water storage system: Table 17.3 Limiting Water Data for Problem 17.4 SKj FSKj (tons) CSKj (ppm) T STT (h) T END (h) SK1 SK2 SK3 SK4 SK5 20 20 20 16 20 15 0.5 9.5 17 2.5 11.5 19 SRi FSRi (tons) CSRi (ppm) T STT (h) T END (h) SR1 SR2 SR3 SR4 SR5 20 20 20 16 14 20 25 10 2.5 11.5 17 10.5 4.5 13.5 19 14.5 Automated Targeting Model for Batch Material Networks 565 a Determine the minimum freshwater and wastewater flow targets for a direct reuse/recycle scheme, as well as the minimum size of the water storage tanks b Determine the minimum TAC target for a direct reuse/recycle scheme The unit costs of freshwater (CTFW) and wastewater (CTWW) are given as $1/ton each Capital cost for water storage tanks is given in Equation 17.24, while piping cost may be ignored The storage cost is annualized to a period of years, with an interest rate of 5% Assume an annual production of 420 batches c Determine the minimum TAC target for a water regeneration network In this case, a partitioning interception unit is used to regenerate process sources The unit has a recovery factor (RC)* of 0.8 and an outlet concentration of 5 ppm The unit cost for water regeneration (CTRW) is assumed to be $0.8/ton, which includes capital and operating costs Other cost parameters remain unchanged as in (b) Identify also the time intervals where the interception unit will be in operation d Determine the minimum TAC target for a batch total water network In this case, a single pass interception unit with outlet concentration of 5 ppm is used for source purification The purified source may be sent to the process sinks for further reuse/recycle, or for final waste discharge The environmental discharge limit is set to 5 ppm The unit cost for water regeneration (CTRW) is assumed to be $0.8/ton, which includes capital and operating costs (this includes the cost of wastewater treatment) Other cost parameters remain unchanged as in (b) Identify the minimum TAC target for this case Identify also the time intervals where the interception unit will be in operation Also identify when the storage tank will be used to store the regenerated water source for recovery at later time intervals e Synthesize the batch water network for case (d), either with the insights gained from the ATM or using the NNA (refer to Section 11.5 for detailed steps) Property Integration Problems 17.7 Revisit the property-based batch water network in Problem 11.6 (Ng et al., 2008), where pH is the main water stream quality to be considered for water recovery (see mixing rule in Equation 11.1) Two fresh resources are available for use without any flow constraint, i.e., acid and freshwater, with unit costs of $0.20/kg (CTAC) and $0.01/kg (CTFW), respectively The total annualized cost of a storage tank (including pumping and piping) is given as $15,000/year Limiting data are given in Table 11.22 Determine the minimum TAC target for this BMN, assuming an annual operating time (AOT) of 8760 h * Refer to Example 14.3 for calculation of a partitioning interception unit 566 Process Integration for Resource Conservation References Almató, M., Espuńa, A., and Puigjaner, L 1999 Optimisation of water use in batch process industries Computers and Chemical Engineering, 23,1427–1437 Chan, J H., Foo, D C Y., Kumaresan, S., Aziz, R A., and Hassan, M A A 2008 An integrated approach for water minimisation in a PVC manufacturing process Clean Technologies and Environmental Policy, 10(1), 67–79 Chen, C.-L., Chang, C.-Y., and Lee, J.-Y 2008 Continuous-time formulation for the synthesis of water-using networks in batch plants Industrial and Engineering Chemistry Research, 47, 7818–7832 Chen, C L and Lee, J Y 2008 A graphical technique for the design of water-using networks in batch processes Chemical Engineering Science, 63, 3740–3754 Chen, C L and Lee, J Y 2010 On the use of graphical analysis for the design of batch water networks Clean Technologies and Environmental Policy, 12, 117–123 Chen, C.-L., Lee, J.-Y., Ng, D K S., and Foo D C Y 2010 A unified model of property integration for batch and continuous processes AIChE J, 56, 1845–1858 Chen, C.-L., Lee, J.-Y., Tang, J.-W., and Ciou, Y.-J 2009 Synthesis of water-using network with central reusable storage in batch processes Computers and Chemical Engineering, 33, 267–276 Cheng, K F and Chang, C T 2007 Integrated water network designs for batch processes Industrial and Engineering Chemistry Research, 46,1241–1253 Foo, D C Y 2010 Automated targeting technique for batch process integration Industrial and Engineering Chemistry Research, 49(20), 9899–9916 Gouws, J F and Majozi, T 2008 Impact of multiple storage in wastewater minimisation for multi-contaminant batch plants: Towards zero effluent Industrial and Engineering Chemistry Research, 47, 369–379 Gouws, J., Majozi, T., Foo, D C Y., Chen, C L., and Lee, J.-Y 2010 Water minimisation techniques for batch processes Industrial and Engineering Chemistry Research, 49(19), 8877–8893 Kim, J.-K and Smith, R 2004 Automated design of discontinuous water systems Process Safety and Environmental Protection, 82(B3), 238–248 Li, B H and Chang, C T 2006 A mathematical programming model for discontinuous water-reuse system design Industrial and Engineering Chemistry Research, 45, 5027–5036 Majozi, T 2005 Wastewater minimization using central reusable storage in batch plants Computers and Chemical Engineering, 29, 1631–1646 Majozi, T 2006 Storage design for maximum wastewater reuse in multipurpose batch plants Industrial and Engineering Chemistry Research, 45, 5936–5943 Majozi, T., Brouckaert, C J., and Buckley, C A 2006 A graphical technique for wastewater minimization in batch processes Journal of Environmental Management, 78, 317–329 Majozi, T and Gouws, J 2009 A mathematical optimization approach for wastewater minimization in multiple contaminant batch plants Computers and Chemical Engineering, 33, 1826–1840 Majozi, T 2010 Batch Chemical Process Integration: Analysis, Synthesis and Optimi­ zation Springer Automated Targeting Model for Batch Material Networks 567 Ng, D K S., Foo, D C Y., Rabie, A., and El-Halwagi, M M 2008 Simultaneous synthesis of property-based water reuse/recycle and interception networks for batch processes AIChE Journal, 54(10), 2624–2632 Nun, S., Tan, R R., Razon, L F., Foo, D C Y., and Egashirad, R 2011 Fuzzy automated targeting for trade-off analysis in batch water networks Asia-Pacific Journal of Chemical Engineering, 6(3), 537–551 Wang, Y P and Smith, R 1995 Time pinch analysis Chemical Engineering Research and Design, 73, 905–914 This page intentionally left blank Appendix: Case Studies and Examples Throughout this book, various hypothetical and industrial examples have been utilized for methodology illustration, as well as problems for exercises A complete list of all examples and problems in this book is given here for better reference for the readers of specific interest An example is indicated as “E,” while a problem is indicated as “P.” Water Minimization Problems Wang and Smith (1994): P3.3, P6.2, P7.16, E8.1, E8.2, E8.3, E8.4, E10.1, P12.1, P13.7, E14.1, E14.2, P14.1, E15.1, E15.2, E15.4 Polley and Polley (2000): P3.4, P4.11, E6.1, E6.2, E7.1, E7.3, E7.4, P7.1, P7.13, P7.14, P8.1, E10.1, P12.2, P13.6 Savelski and Bagajewicz (2001): P4.4, P7.17 Wang and Smith (1995): P4.12 Jacob et al (2002): P4.3, P7.10 Sorin and Bédard (1999): P6.4, P7.12, P8.4, P12.7, P13.3, P14.3, P15.1 Gabriel and El-Halwagi (2005): P14.2 Zero fresh resource network: E3.5, P3.7, E4.3, P4.7, P7.9 Zero waste discharge network (Foo, 2008): E3.6, P3.7, E4.4, P4.7, P7.8, P13.2 Acrylonitrile (AN) production case study: E2.1, E2.2, E3.1, E3.2, E3.4, E4.1, E5.1, E6.3, P7.2, E13.1, E13.2, P13.5, P14.5 Tire-to-fuel process (El-Halwagi, 1997; Noureldin and El-Halwagi, 1999): P2.1, P3.1, P7.3, P13.1 Kraft pulping process (El-Halwagi, 1997): P2.2, P4.1, P6.6, P7.15, P8.3, P14.6, P15.2 Tricresyl phosphate process (El-Halwagi, 1997): P2.3, P4.2 Specialty chemical production process (Wang and Smith, 1995): P4.6, P6.3, P7.7, P8.2, P12.5 Bulk chemical production (Foo, 2012): P3.5, P7.6, P12.4, P13.4 Organic chemical production (Hall, 1997; Foo, 2008): P3.6, P7.11 569 570 Appendix: Case Studies and Examples Paper milling process (Foo et al., 2006b): P4.5, P12.8, P14.4 Textile plant (Ujang et al., 2002): P2.4, P3.2, P12.3 Palm oil mills (Chungsiriporn et al., 2006): P4.8, P7.4, P12.6 Steel plant (Tian et al., 2008): P4.9, P7.5 Kraft pulping process (Parthasarathy and Krishnagopalan, 2001): P4.10 Integrated pulp mill and bleached paper plant: P12.15 Utility Gas Recovery Problems Refinery hydrogen network (Hallale and Liu, 2001): E2.4, E3.3, P4.13, P7.20, P12.10, P13.8, E14.4, E15.3 Refinery hydrogen network (Alves and Towler, 2002): P2.6, P4.15, P7.21, P12.11, P13.9, P14.7, P15.3 Refinery hydrogen network (Foo and Manan, 2006): P4.16, P7.22, P8.5 Magnetic tape manufacturing process (El-Halwagi, 1997): P2.5, P3.8, P4.14, P7.18, P14.8 Oxygen-consuming process (Foo and Manan, 2006): P3.9, P7.19, P12.9 Property Integration Problems Metal degreasing process (Kazantzi and El-Halwagi, 2005): E2.5, E3.7, P4.17, E5.2, E7.2, P7.23, P13.10 Kraft papermaking process (Kazantzi and El-Halwagi, 2005): E2.6, E3.8, P3.10, E4.5, P7.24, P12.12, E13.3 Microelectronics manufacturing (Gabriel et al., 2003; El-Halwagi, 2006): P3.11, P7.25, P8.6, P12.13 Wafer fabrication process (Ng et al., 2009, 2010): P2.7, P4.19, P7.26, P8.7, P13.11, P14.9, P15.4 Palm oil mill (Ng et al., 2009): E13.4, P14.10, P15.5 Vinyl acetate manufacturing (El-Halwagi, 2006): P2.8, P3.10, P4.18 Paper recovery study (Wan Alwi et al., 2010): P3.12 Paper recovery study (Wan Alwi et al., 2010): P4.20 Appendix: Case Studies and Examples 571 Pre-Treatment Networks Tan et al (2010): Case and 2a: E9.1, E9.2, E14.5 Tan et al (2010): Case 2b: P9.1, P14.11 Tan et al (2010): Case 3: P9.2, P14.12 Inter-Plant Resource Conservation Networks Inter-plant water networks (Bandyopadhyay et al., 2010): E10.1, E10.3, E10.4, P12.14, E16.1, E16.2, P16.4, P16.5 Inter-plant water networks (Olesen and Polley, 1996): E10.2, P10.2, P12.18, P16.2 Inter-plant water networks in catalyst plant (Feng et al., 2006): P10.1 Inter-plant water networks in integrated pulp mill and a bleached paper plant (Lovelady et al., 2007; Chew et al., 2008): P12.15 Inter-plant water networks in integrated iron and steel mill (Chew and Foo, 2009): P16.1 Inter-plant water networks in eco-industrial park (Lovelady and El-Halwagi, 2009): P16.3 Inter-plant hydrogen networks (Chew et al., 2010a): P10.3, P12.16, P16.6 Inter-plant property-based water networks in wafer fabrication plants (Chew and Foo, 2009; Chew et al., 2010): P10.4, P12.17, E16.3, E16.4, P16.7, P16.8 Batch Material Networks Wang and Smith (2005): E11.1 through 11.5, P11.1, E17.1, E17.2, E17.3, P17.5 Kim and Smith (2004): P11.2, P17.1 Chen and Lee (2008): P11.3, P17.2 Majozi et al (2006): P11.4, P17.3 Chan et al (2008): P11.5, P17.4 Almató et al (1999): P17.6 Property network (Ng et al., 2008; Foo, 2010): P17.7 This page intentionally left blank Chemical Engineering “… this excellent book comes at just the right time to teach the next generation of process designers how to ‘save the planet’ more systematically and intelligently.” —Raymond R Tan, De La Salle University–Manila “This book collects all fundamental aspects of process integration to enable readers to address issues related to resource management I strongly recommend this book to everyone interested in the field of process integration.” —Santanu Bandyopadhyay, IIT Bombay “This book serves as good material for process integration … it [also] offers good knowledge of material recovery that helps people [acquire the] basics for doing further research or practical application.” —Cheng-Liang Chen, National Taiwan University “The chapters are written very well and cover all the topics in sufficient detail and clarity … a wonderful and relevant contribution to the field of process integration.” —T Majozi, University of Pretoria K12774 K12774_Cover.indd GREEN CHEMISTRY AND CHEMICAL ENGINEERING PROCESS INTEGRATION FOR RESOURCE CONSERVATION Water minimization Gas recovery Property integration Foo Process Integration for Resource Conservation presents stateof-the-art, cost-effective techniques, including pinch analysis and mathematical optimization, for numerous conservation problems Following the holistic philosophy of process integration, the author emphasizes the goal of setting performance targets ahead of detailed design He explains various industrial examples step by step and offers demo software and other materials online PROCESS INTEGRATION FOR RESOURCE CONSERVATION “… an excellent contribution that will benefit numerous researchers, students, and process engineers and will serve the cause of sustainability worldwide.” —Mahmoud El-Halwagi, Texas A&M University Dominic C Y Foo 6/8/12 3:32 PM ... Process Integration for Resource Conservation Plant A Plant B Process Interception Process Interception Process Process Treatment Process Pretreatment Interception Process Process Treatment Process. .. (Figure 1.14) 13 Introduction Process Process Process (a) (b) Process Process Interception Interception Process Process (d) (c) Figure 1.12 Strategies for in-plant resource conservation: (a) direct... e.g., process simulators, spreadsheets Limitations • Tedious solution for complex problems • Inaccuracy problems • Less insights for designers 12 Process Integration for Resource Conservation Process

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