Recent Advances Sustainable Process 12

Advances in Process Systems Engineering Vol. 3

RECENT ADVANCES IN SUSTAINABLE PROCESS DESIGN AND OPTIMIZATION

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Advances in Process Systems Engineering

Series Editor: Gade Pandu Rangaiah(National University of Singapore)

Vol. 1: Multi-Objective Optimization:Techniques and Applications in Chemical Engineeringed: Gade Pandu Rangaiah

Vol. 2: Stochastic Global Optimization:Techniques and Applications in Chemical Engineeringed: Gade Pandu Rangaiah

Vol. 3: Recent Advances in Sustainable Process Design and Optimizationeds: D. C. Y. Foo, M. M. El-Halwagi and R. R. Tan

KwangWei - Recent Advances in Sustainable.pmd 4/19/2012, 5:26 PM2

N E W J E R S E Y L O N D O N S I N G A P O R E B E I J I N G S H A N G H A I H O N G K O N G TA I P E I C H E N N A I

World Scientific

Advances in Process Systems Engineering Vol. 3

RECENT ADVANCES IN SUSTAINABLE PROCESS DESIGN AND OPTIMIZATION

editors

Dominic C Y FooUniversity of Nottingham Malaysia, Malaysia

Mahmoud M El-HalwagiTexas A&M University, USA

Raymond R TanDe La Salle University-Manila, Philippines

With CD-ROM

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Advances in Process Systems Engineering Vol. 3RECENT ADVANCES IN SUSTAINABLE PROCESS DESIGNAND OPTIMIZATION(With CD-ROM)

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PREFACE

Process engineers and designers of the 21st Century face challenges thatwere not considered particularly important a hundred years earlier, in theearly days of the nascent eld of chemical engineering. Nowadays, processindustries face the need to conserve material and energy resources thatwere, in the past, considered so abundant as to be practically unlimitedin supply. We now recognize that most of the resources modern industryrelies on fossil fuels, metal ores and water, for example are in limitedsupply. As a result, sustained economic growth in the long term is onlypossible through improved eciency in the use of these increasingly scarceresources. At the same time, increasing public concern about environmentalissues, as reected in ever more stringent environmental legislation, adds anew dimension to the design problems faced by process engineers. Pollutionat the local, regional and global scales present unique design constraintsthat previous generations of chemical engineers did not need to deal with.In particular, anthropogenic climate change as a result of human industrialactivity is now considered to be one of the most critical challenges facingmankind today. A multifaceted response involving energy conservation,carbon sequestration and utilization of renewables is likely to be neededto make any signicant reduction in the worlds greenhouse gas emissions.Such response requires the development and deployment of systematicand generally applicable design procedures that are aimed at the broadobjective of sustainability. Recently, signicant progress has been madein the development of such design procedures. The developed techniquesare rooted in fundamental engineering principles and utilize a variety ofgraphical, algebraic, and mathematical programming tools.

This handbook outlines some of the state-of-the-art responsesof the international process systems engineering community to thesecontemporary challenges. It deals with general environmental issues thatarise both from the industrial consumption of scarce material and energyresources, and the generation of potentially polluting industrial waste

v

vi Preface

streams. The emphasis is placed on an integrated, preventive, systems-based approach to these environmental challenges, rather than the moretraditional pollution control approach of waste treatment and securedisposal. This approach thus allows process engineers and designers tomake environmental improvements that enhance, rather than compromise,the economic viability of the process industries.

This volume is comprised of twenty-one chapters outlining state-of-the-art advances in sustainable process design methodology from renownedexperts and researchers from Africa, Asia, Europe and North America.Thus, it provides a broad cross-section of process systems engineeringwork done worldwide, using an array of approaches ranging from processintegration techniques, life cycle analysis, mathematical programming andmodeling, graph theory and heuristics. Many of the chapters also provideindustrial case studies that illustrate how these new techniques may applyto problems in the real world. Appendices and supplementary electronicles are also provided for those interested in delving deeper into some ofthese topics.

This book consists of chapters most of which may be read independentlyof each other, or with no particular sequence. However, the chaptersare classied into three broad areas, namely, process modeling, materialresource conservation and waste reduction, and energy conservation andeciency:

Synopses of Chapters in Section 1 (Process Modeling)

This section consists of four chapters. The rst two chapters by L. T.Fan and T. Zhang, are entitled Estimation of exergy dissipation andcost: the foundation for sustainability assessment in process design andLife cycle assessment (LCA) and describe a generic framework for thesystematic, quantitative analysis of sustainability in the process industries.Chapter 1 describes a rigorous thermodynamic framework for quantifyingprocess sustainability, while Chapter 2 provides a description of thekey concepts and computations that are entailed in LCA. Subsequentchapters focus on ecient resource use. The next two chapters deal withspecic applications. M. F. Chongs Chapter 3, entitled A TransportModel for Nanoltration and Reverse Osmosis Systems Using IrreversibleThermodynamics discusses key design principles for membrane-basedprocesses that are becoming increasingly crucial for many industry sectors.Finally, Chapter 4 by H. Lou et al., Process Modeling of Inibition ofFree Radical Polymerization Reactions describes an approach to control

Preface vii

undesirable reactions in chemical plants to ensure that process safety andproduct quality are maintained.

Synopses of Chapters in Section 2 (Material ResourceConservation and Waste Reduction)

This section consists of seven chapters in total. Chapter 5, by D. C.Y. Foo and entitled Resource Conservation through Pinch Analysis,describes insight-based pinch analysis techniques with emphasis on thetargeting and design of process networks for ecient utilization of scarceresources, such as fresh water and utility gases. Chapter 6 by X. Fenget al., entitled Optimal Water Network with Internal Water Mains andIts Industrial Application introduces the concept of internal water mainswhich result in simplied congurations for process water reuse networks.The next chapter, A. Chakrabortys Mathematical Models for OptimalResource Utilization in Process Industries, introduces a variant for wastestream reuse and describes an application in pharmaceutical processing.While the previous three chapters describe methodologies appropriate forcontinuous-ow process plants, the next two chapters entitled WastewaterMinimisation in Batch Chemical Plants: Single Contaminant Media, by T.Majozi, and Wastewater Minimisation in Batch Chemical Plants: MultipleContaminant Media, by T. Majozi and J. Gouwes, describe modelingtechniques for batch-wise operations of various degrees of complexity. Theoptimization models in Chapters 69 are dealt with in a deterministicmanner, but alternative approaches using heuristic algorithms have beenextensively described in literature (and also in Chapter 5). Chapter 10,Adaptive swarm-based simulated annealing for the synthesis of waternetworks by R. Tan, and Chapter 11, Optimal wastewater networkdesign by J. Jezowski et al., describe alternative solution methods foroptimization models using stochastic approaches, with the former onsimulated annealing/swarm intelligence hybrid technique and the latter onadaptive random search.

Synopses of Chapters in Section 3 (Energy Conservationand Eciency)

This nal section consists of ten chapters. Chapter 12 by M. S. Ba-Shammakh et al., is entitled Clean Energy and CO2 Capture, Transportand Storage and describes a methodology for designing clean fossil energy-based systems with carbon sequestration, which are widely considered as an

viii Preface

essential interim technology for transition to a low-carbon infrastructure.In contrast, Chapter 13, by P. Varbanov and entitled P-graph: anEcient Process Synthesis Tool. Application to Fuel Cell-Based EnergyGeneration, describes a graph theoretic approach to the design ofrenewable energy networks. Chapter 14 by R. Mahmud et al., entitled AProcess Integration Framework for the Optimal Design of Combined Heatand Power Systems in the Process Industries introduces a novel approachto enhancing industrial energy eciency through integrated generation ofthermal and electrical energy. The next chapter, J.-K. Kims Design ofLow Temperature Energy Systems, focuses on energy eciency throughheat integration of processes at sub-ambient temperatures.

Chapter 16 is contributed by C. L. Chen et al., and entitledIndirect Heat Integration of Batch Processes, which deals with the addedcomplications incurred by the time aspect in conducting heat integrationfor batch operations. Recent shifts in the process industries away fromlarge-scale production of commodity chemicals, towards the use of small,exible plants producing relatively small quantities of high-value goods,require such methodologies. Next, the contribution by J. J. Klemes et al.,entitled Energy Eciency and the Integration of Waste and RenewableEnergy Sources describes an approach to design energy networks makinguse of a range of biomass feedstocks. Chapter 18, by S. Bandyopadhyay,is entitled, A Novel Design Procedure for Solar Thermal Systems anddescribes a methodology for design solar thermal system using a designspace approach.

The nal three chapters provide a dierent perspective based onindustrial applications. Chapter 19 is C. L. Law and A. S. MujumdarsEnergy Saving in Drying Processes which provides a survey of currentdrying techniques for various applications. In Chapter 20, Two Birdswith One Stone Simultaneous Waste Heat Recovery and EmissionReduction in Gas/Oil Separation Plants, B. Noureldin describes anindustrial application of heat integration. Economic and carbon emissionsissues are encountered in a case study that is typical of those found intraditional process industries. The nal chapter of this handbook is A.Rossiters Energy Management for the Process Industries, which againprovides a practical perspective on reduction of industrial energy use, aswell as corresponding emissions and costs.

Together, these twenty-one chapters provide a framework of tools andtechniques for the quantitative analysis and design of clean, ecient andsustainable systems in the process industries.

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Preface ix

Acknowledgments

First and foremost, we wish to thank the authors who contributed theirinvaluable expertise in the form of chapters covering state-of-the artdevelopments in the eld of sustainable process design. The value ofthis book is based primarily on their inputs. In particular, we wish todedicate this work to the memory of our departed colleague, Prof. JacekM. Jezowski, who passed away earlier this year, and whose work appears inChapter 11 of this book. We are also grateful to the sta of World ScienticPublishing, who provided invaluable assistance throughout the long processof publication. Finally, we would like to thank our family members fortheir support throughout our professional careers. In particular, DominicFoo would like to thank his wife Cecilia Cheah for tremendous support,especially in taking care of their daughters Irene and Jessica Foo. MahmoudEl-Halwagi would like to acknowledge his parents, his wife Amal, and sonsOmar and Ali for their constant support and unlimited love. RaymondTan thanks his wife, Jenny, and daughters, Denise and Dana, for providinginspiration and for patiently tolerating hectic workdays.

Dominic C. Y. FooMahmoud El-Halwagi

Raymond R. Tan

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LIST OF CONTRIBUTORS

Professor L. T. Fan, Ph.D.; Tengyan Zhang, Ph.D.Institute for Systems Design and OptimizationDepartment of Chemical EngineeringKansas State University105 Durland, Manhattan, KS 66506-5102, USATel: +1 (785) 532-5584Fax: +1 (785) 532-7372Email: [email protected]: www.che.ksu.edu/faculty/fan

Mei Fong Chong, Ph.D.Department of Chemical and Environmental EngineeringThe University of Nottingham, Malaysia CampusBroga Road, 43500 Semenyih, Selangor, MalaysiaTel: +60 (3) 8924-8347Fax: +60 (3) 8924-8017Email: [email protected]:www.nottingham.edu.my/Engineering/Departments/Chemenv/people/meifong.chong

Professor Helen H. Lou, Ph.D.; Sanjeev Dusija; Xiang Li;John L. Gossage; Jack. R. HopperDepartment of Chemical EngineeringLamar UniversityBeaumont, TX 77710Tel: +1 (409) 880-8207Fax: +1 (409) 880-2197Email: [email protected]: http://dept.lamar.edu/chemicalengineering/www/Lou/index.htm

xi

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xii List of Contributors

HSE - Engineering and TechnologyFluor Corporation1 Floor Danie DriveSugar Land, TX 77478-3899Tel: 281-263-2468Email: Sanjeev.Dusija.uor.com

Dominic C. Y. Foo, Ph.D.Department of Chemical and Environmental EngineeringUniversity of Nottingham MalaysiaBroga Road, 43500 Semenyih, Selangor, MalaysiaTel: +60 (3) 8924-8130Fax: +60 (3) 8924-8017Email: [email protected]: www.geocities.com/foodominic

Professor Xiao Feng, Ph.D.; Jie Bai; Renjie Shen, Ph.D.College of Chemical EngineeringChina University of PetroleumBeijing 102249, P. R. ChinaTel: 86-10-89733991Fax: 86-10-89724721Email:xfeng.cup.edu.cnDepartment of Chemical EngineeringXian Jiaotong UniversityXi, 710049, P. R. ChinaTel: +86 (29) 8266-8980Fax: +86 (29) 8323-7910Email: [email protected]

Aninda Chakraborty, Ph.D.Linear Programming (LP) Developer & Renery AnalystPetroplus Rening & Marketing LtdCoryton Renery, The ManorwayStanford-Le-Hope, SS179LL, Essex, UKTel: +44(0)1375646091Email: [email protected]

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List of Contributors xiii

Chun Deng, Ph.D.China University of Petroleum-Beijing18 Fuxue Road, Changping, Beijing China 102249Tel: +86 10 8973 1979Fax: +86 10 8973 1979Email: [email protected]

Professor Thokozani Majozi, Ph.D.; Jacques Gouws, Ph.D.Department of Chemical EngineeringUniversity of PretoriaLynnwood Road, Pretoria, 0002, South AfricaTel: +27 (12) 420-4130Fax: +27 (12) 362-5173Email: [email protected]

Professor Raymond R. Tan, Ph.D.Chemical Engineering DepartmentDe La Salle University2401 Taft Avenue, 1004 Manila, PhilippinesTel: +63 (2) 536-0260Fax: +63 (2) 524-0563Email: [email protected]: www.dlsu.edu.ph/library/webbiography/fpub/raymond tan.asp

Professor Jacek M. Jezowski, Ph.D.;Grzegorz Poplewski, Ph.D.Faculty of ChemistryDepartment of Chemical and Process EngineeringRzeszow University of Technologyul. W Pola 2, 35- 959 Rzeszow, PolandTel: +48 (17) 854-1216Fax: +48 (17) 854-3655Email: [email protected]: http://gpoplewski.sd.prz.edu.pl/en/

He is deceased.

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xiv List of Contributors

Iyna Dzhygyrey, Ph.D.Department of Cybernetics of Chemical Technology Processes,National Technical University of Ukraine

Kyiv Polytechnic Institute,Peremogy av. 37, 03056 Kyiv, UkraineTel: +38 (044) 406-8212Fax: +38 (044) 236-4052Email: [email protected]: http://kxtp.kpi.ua/en/

Professor Ali Elkamel, Ph.D.; Professor Peter Douglas, Ph.D.;Eric Croiset, Ph.D.Chemical Engineering DepartmentUniversity of Waterloo200 University Avenue West WaterlooON, N2L 3G1 CanadaTel: +1 (785) 532-5584Fax: +1 (785) 532-7372Email: [email protected]; [email protected];[email protected]: http://chentserver.uwaterloo.ca/research/areas.html#5

Mohammed S. Ba-Shammakh, Ph.D.Chemical Engineering DepartmentKing Fahd University of Petroleum & MineralsP. O. Box 5050Dhahran, 31261, Saudi ArabiaTel: +966 (3) 860-7464Fax: +966 (3) 860-4234Email: [email protected]: http://faculty.kfupm.edu.sa/che/shammakh/

Petar Varbanov, Ph.D.University of PannoniaEgyetem u. 10, H-8200, Veszprem, HungaryTel: +36 (88) 421-664Fax: +36 (88) 624-025Email:[email protected]: http://eschains.dcs.uni-pannon.hu/index.php

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List of Contributors xv

Professor Mahmoud El-Halwagi, Ph.D.;Rubayat Mahmud, Ph.D.; Dustin Harell, Ph.D.Department of Chemical EngineeringTexas A&M University, College Station, Texas 77843-3122, USATel: +1 (979) 845-3484Fax: +1 (979) 845-6446Email: [email protected]: http://cheweb.tamu.edu/faculty/el-halwagi/

Jin-Kuk Kim, Ph.D.Department of Chemical Engineering College of EngineeringHanyang University222 Wangsimni-ro, Seongdong-gu, Seoul,Republic of Korea (South) 133-791Tel: +0082 2 2220 2331Fax: +0082 2 2220 4007Email: [email protected]

Professor Cheng-Liang Chen, Ph.D.; Ying-Jyuan Ciou, Ph.D.Department of Chemical EngineeringNational Taiwan UniversityTaipei 10617, Taiwan, ROCTel: +886 (2) 2363-6194Fax: +886 (2) 2362-3040Email: [email protected]: http://pse.che.ntu.edu.tw/en/index.html

Professor Dr. Habil Jir Klemes, D.Sc.EC Marie Curie Chair (EXC) INEMAGLOWCentre for Process Integration and Intensication CPI2

Research Institute of Chemical Technology and Process EngineeringFaculty of Information TechnologyUniversity of PannoniaEgyetem u 10, 8200 Veszprem HungaryTel: +36 (88) 421-664Fax: +36 (88) 624-025Email: [email protected]: http://cpi.uni-pannon.hu/index.php?section=11

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xvi List of Contributors

Simon J Perry; Igor Bulatov, Ph.D.Centre for Process IntegrationSchool of Chemical Engineering and Analytical ScienceThe Mill Sackville Street, The University of ManchesterManchester, M13 9PL, UKTel: +44 (0) 161-306-4391Fax: +44 (0) 161-236-7439Email: [email protected]; [email protected]: http://www.ceas.manchester.ac.uk/research/centres/

centreforprocessintegration/

Professor Santanu Bandyopadhyay, Ph.D.Department of Energy Science and Engineering,Indian Institute of Technology BombayPowai, Mumbai, 400076, IndiaTel: +91 (22) 2576-7894Fax: +91 (22) 2572-6875Email: [email protected]: http://www.me.iitb.ac.in/santanu/

Chung Lim Law, Ph.D.Department of Chemical and Environmental EngineeringUniversity of Nottingham (Malaysia Campus)Broga Road, 43500 Semenyih, Selangor, MalaysiaTel: +60 (3) 8924-8169Fax: +60 (3) 8924-8017Email: [email protected]: http://www.nottingham.edu.my/Faculties/Engineering/Chemical/

people/Pages/Chung Lim Law.aspx

Professor Arun S. Mujumdar, Ph.D.Department of Mechanical Engineering, andDirector, Mineral, Metal and Materials Technology Centre ( M3TC)National University of Singapore, 9 Engineering Drive 1Singapore 117576Tel: +65 6516 4623Fax: +65 6779-1459Email: [email protected]: http://serve.me.nus.edu.sg/arun/

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List of Contributors xvii

Mahmoud Bahy Noureldin, Ph.D.Consulting Services DepartmentSaudi AramcoDhahran, Saudi ArabiaTel: +966 (3) 873-6045Fax: +966 (3) 878-2896Email: [email protected]

Alan Rossiter, Ph.D., PERossiter and Associates4421 Darsey StBellaire, TX 77401, USATel: +1 (713) 660-9503Fax: +1 (713) 669-1987Email: [email protected]: www.rossiters.org/associates

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CONTENTS

Preface v

List of Contributors xi

Section 1: Process Modeling 1

1. Estimation of Exergy Dissipation and Cost: TheFoundation for Sustainability Assessment in Process Design 3

Authors: L. T. Fan & T. Zhang

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Thermodynamic Foundations . . . . . . . . . . . . . . . . . 4

2.1 Reference states . . . . . . . . . . . . . . . . . . . . . . 42.1.1 Standard state . . . . . . . . . . . . . . . . . . . 42.1.2 Dead state . . . . . . . . . . . . . . . . . . . . . 5

2.2 Balances of mass, energy, entropy-dissipation,and available energy . . . . . . . . . . . . . . . . . . . 112.2.1 Mass balance . . . . . . . . . . . . . . . . . . . 132.2.2 Energy balance . . . . . . . . . . . . . . . . . . 142.2.3 Entropy-dissipation balance . . . . . . . . . . . 162.2.4 Available energy balance . . . . . . . . . . . . . 17

2.3 First-law and second-law conservation (process)eciencies . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.4 Simple systems . . . . . . . . . . . . . . . . . . . . . . 222.4.1 Thermal mixing . . . . . . . . . . . . . . . . . . 22

2.4.1.1 Numerical illustration . . . . . . . . . 242.4.2 Biomass pyrolysis . . . . . . . . . . . . . . . . . 27

3 Economic Foundations . . . . . . . . . . . . . . . . . . . . . 343.1 Cost estimation . . . . . . . . . . . . . . . . . . . . . . 35

3.1.1 External cost . . . . . . . . . . . . . . . . . . . 353.1.2 Internal cost . . . . . . . . . . . . . . . . . . . . 37

xix

xx Contents

4 Sustainability Assessment . . . . . . . . . . . . . . . . . . . 394.1 Sustainability potential . . . . . . . . . . . . . . . . . . 39

4.1.1 Methodology . . . . . . . . . . . . . . . . . . . 404.1.1.1 Determination of alternative synthetic

routes . . . . . . . . . . . . . . . . . . 414.1.1.2 Hierarchical assessment of the

sustainability-potential of alternativesynthetic routes . . . . . . . . . . . . . 45

4.1.2 Applications . . . . . . . . . . . . . . . . . . . . 484.2 Sustainable Process Index . . . . . . . . . . . . . . . . 494.3 AIChE Sustainability Index (SI) . . . . . . . . . . . . . 514.4 Hierarchical thermodynamic metrics . . . . . . . . . . 53

4.4.1 Multi-scale system . . . . . . . . . . . . . . . . 544.4.2 Aggregation hierarchy . . . . . . . . . . . . . . 544.4.3 Spatial hierarchy . . . . . . . . . . . . . . . . . 56

5 Epilog . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

2. Life Cycle Assessment (LCA) 65

Authors: L. T. Fan & T. Zhang

1 Phases of Life Cycle Assessment (LCA) . . . . . . . . . . . 651.1 Phase 1: Goal and scope denition . . . . . . . . . . . 651.2 Phase 2: Inventory analysis . . . . . . . . . . . . . . . 661.3 Phase 3: Impact assessment . . . . . . . . . . . . . . . 691.4 Phase 4: Interpretation . . . . . . . . . . . . . . . . . . 74

2 Calculating Environmental Burdens and Impacts in LCA An Example . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

3 Thermodynamic Input-Output LCA (TIO-LCA) . . . . . . 754 Ecologically-Based Life Cycle Assessment (Eco-LCA) . . . . 76

3. Transport Model for Nanoltration and Reverse OsmosisSystem based on Irreversible Thermodynamic 79

Author: M. F. Chong1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 792 Transport Mechanistic and Irreversible Thermodynamics

based Transport Models for NF and RO membranes . . . . 803 Fundamental of Irreversible Thermodynamics

in Membrane System . . . . . . . . . . . . . . . . . . . . . . 81

Contents xxi

4 SpieglerKedem Model for Single Solute System . . . . . . . 855 SpieglerKedem Model for Multiple Solute Systems . . . . . 87

5.1 SpieglerKedem model for binary solutes system . . . 885.2 Extended SpieglerKedem model for multiple

solute systems . . . . . . . . . . . . . . . . . . . . . . . 895.3 SpieglerKedem model for multiple solutes system

in dierential equation form . . . . . . . . . . . . . . . 905.4 KedemKatchalsky model for binary solutes system

with one impermeable solute . . . . . . . . . . . . . . . 905.5 KedemKatchalsky model for nonelectrolyte, dilute,

multiple solute systems . . . . . . . . . . . . . . . . . . 915.5.1 Case study 1: Binary solutes system . . . . . . 915.5.2 Case study 2: Ternary solute system . . . . . . 93

6 Process Design for Membrane Systems . . . . . . . . . . . . 967 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

4. Analysis of a Novel Method for Inhibiting RunawayReaction via Process Modeling 107

Authors: H. H. Lou, S. Dusija, X. Li, J. L. Gossage &J. R. Hopper

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1072 Polymerization Reaction and Polymer Properties . . . . . . 109

2.1 Polymerization kinetics . . . . . . . . . . . . . . . . . . 1092.2 Polymer properties . . . . . . . . . . . . . . . . . . . . 1112.3 Polymer reactions in CSTR/batch reactors . . . . . . . 113

3 Case Study of Inhibition . . . . . . . . . . . . . . . . . . . . 1133.1 Reaction kinetics for vinyl acetate polymerization . . . 1153.2 Selection of inhibitor . . . . . . . . . . . . . . . . . . . 1153.3 Simulation of reaction runaway and inhibition

in batch process . . . . . . . . . . . . . . . . . . . . . . 1183.4 Simulation of reaction runaway and inhibition

for emergency shutdown of a CSTR . . . . . . . . . . . 1223.5 Eect on polymer properties for continuous

operations . . . . . . . . . . . . . . . . . . . . . . . . . 1244 Conclusions and Inference . . . . . . . . . . . . . . . . . . . 127

xxii Contents

Section 2: Material Resource Conservationand Waste Reduction 131

5. Resource Conservation through Pinch Analysis 133

Author: D. C. Y. Foo

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1332 Design Tools for Resource Conservation . . . . . . . . . . . 134

2.1 Targeting tools . . . . . . . . . . . . . . . . . . . . . . 1342.1.1 Material recovery pinch diagram (MRPD) . . . 1342.1.2 Material surplus composite curves (MSCC) . . 1362.1.3 Cascade analysis technique . . . . . . . . . . . . 137

2.2 Network Design Techniques . . . . . . . . . . . . . . . 1393 Examples of RCN . . . . . . . . . . . . . . . . . . . . . . . . 140

3.1 Water network synthesis . . . . . . . . . . . . . . . . . 1403.2 Gas network . . . . . . . . . . . . . . . . . . . . . . . . 1443.3 Property network . . . . . . . . . . . . . . . . . . . . . 149

4 Further Improvement . . . . . . . . . . . . . . . . . . . . . . 1555 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155

6. Optimal Water Network with Internal Water Mainsand Its Industrial Application 159

Authors: X. Feng, J. Bai, R. Shen & C. Deng

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1592 Use of Water Mains . . . . . . . . . . . . . . . . . . . . . . . 1603 Optimal Design of Water Network with Internal Water Mains 162

3.1 Superstructure of Water Network with Internal WaterMains . . . . . . . . . . . . . . . . . . . . . . . . . . . 162

3.2 Mathematical Modeling for the Water NetworkSuperstructure with Internal Water Mains . . . . . . . 1643.2.1 Determining the number of internal water mains 1643.2.2 Optimization on freshwater consumption . . . . 1643.2.3 Structure constraints . . . . . . . . . . . . . . . 1663.2.4 Solving the model . . . . . . . . . . . . . . . . . 168

4 Optimal Design of Water Network Involving WastewaterRegeneration Recycle with Internal Water Mains . . . . . . 1684.1 Superstructure of Water Networks Involving

Wastewater Regeneration Recycle with Internal WaterMains . . . . . . . . . . . . . . . . . . . . . . . . . . . 168

Contents xxiii

4.2 Mathematical Modeling for the Water NetworkSuperstructure Involving Wastewater RegenerationRecycle with Internal Water Mains . . . . . . . . . . . 1694.2.1 Minimizing the freshwater consumption . . . . 1694.2.2 Minimizing regenerated water owrate . . . . . 1714.2.3 Minimizing regeneration load . . . . . . . . . . 171

5 Industrial Applications . . . . . . . . . . . . . . . . . . . . . 1725.1 Optimizing Procedure . . . . . . . . . . . . . . . . . . 1725.2 Rules to Determine Limiting Water Data . . . . . . . . 1735.3 Adjustment Principles . . . . . . . . . . . . . . . . . . 174

6 Case Study I: A PVC and Sodium Hydroxide Plant . . . . . 1756.1 Current Water System . . . . . . . . . . . . . . . . . . 1756.2 Determining Contaminants and Limiting

Concentrations . . . . . . . . . . . . . . . . . . . . . . 1756.3 Optimizing Scheme with Water Reuse/Recycle . . . . 180

7 Case Study II: An Ammonia Plant . . . . . . . . . . . . . . 1847.1 Current Water System . . . . . . . . . . . . . . . . . . 1847.2 Determine Contaminants and Limiting Concentrations 1867.3 Optimizing Scheme with Water Regeneration

Reuse/Recycle . . . . . . . . . . . . . . . . . . . . . . . 188

7. Mathematical Models for Optimal Resource Utilizationin Process Industries 195

Author: A. Chakraborty

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1951.1 Mathematical modelling of the resource allocation

planning problem . . . . . . . . . . . . . . . . . . . . . 1981.2 Topological constraints . . . . . . . . . . . . . . . . . . 199

1.2.1 Uneconomical matches based on owrates An example of conditional matching . . . . . . 200

1.2.2 MINLP formulation with topological constraints 2001.2.3 MILP formulation with topological constraints . 202

2 Water Recycle Opportunities in Process Industries . . . . . 2042.1 Solution approaches . . . . . . . . . . . . . . . . . . . . 2062.2 Example A textile industry freshwater minimization

problem . . . . . . . . . . . . . . . . . . . . . . . . . . 2072.2.1 Graphical analysis . . . . . . . . . . . . . . . . 2072.2.2 Linear programming . . . . . . . . . . . . . . . 208

xxiv Contents

2.2.3 Interpretation of results based on heuristics . . 2092.2.4 Constraints based on heuristics An example

of stream prioritization . . . . . . . . . . . . . . 2102.2.5 The textile industry problem with topological

constraints . . . . . . . . . . . . . . . . . . . . . 2102.3 Computation performance of MILP model on

large-size problems An example from the pulp &paper industry . . . . . . . . . . . . . . . . . . . . . . 211

3 Optimal Solvent Recovery from Pharmaceutical Wastes . . 2133.1 Example Waste management in a typical

pharmaceutical company . . . . . . . . . . . . . . . . . 2153.1.1 Marketable product portfolio (sinks) . . . . . . 2153.1.2 Base case policy . . . . . . . . . . . . . . . . . . 2173.1.3 Comparison of base case policy with other

waste management policies . . . . . . . . . . . . 2173.1.4 Conditioning of wastes to marketable products 2193.1.5 Economic potential analysis . . . . . . . . . . . 221

4 Preconditioning of Resources Prior to Allocation Synthesis of Optimal Mixer-Separator Networks . . . . . . . 2214.1 Pruning of search space . . . . . . . . . . . . . . . . . 2234.2 Mathematical model for optimal resource allocation

with pre-conditioning . . . . . . . . . . . . . . . . . . . 2244.3 Illustrative example . . . . . . . . . . . . . . . . . . . . 225

5 Conclusions/Signicance . . . . . . . . . . . . . . . . . . . . 227

8. Wastewater Minimisation in Batch Chemical Plants:Single Contaminant Media 233Author: T. Majozi1 Background to Wastewater Minimisation in Batch Plants . 2342 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . 2353 Problem Superstructure . . . . . . . . . . . . . . . . . . . . 2364 Mathematical Model . . . . . . . . . . . . . . . . . . . . . . 238

4.1 Water reuse/recycle module . . . . . . . . . . . . . . . 2384.2 Sequencing/scheduling module . . . . . . . . . . . . . . 244

4.2.1 Sequencing in the absence of reusable waterstorage . . . . . . . . . . . . . . . . . . . . . . . 245

4.2.2 Sequencing in the presence of reusable waterstorage . . . . . . . . . . . . . . . . . . . . . . . 246

Contents xxv

4.3 Objective function . . . . . . . . . . . . . . . . . . . . 2495 First Case Study . . . . . . . . . . . . . . . . . . . . . . . . 249

5.1 Water reuse/recycle module . . . . . . . . . . . . . . . 2505.2 Sequencing/scheduling module . . . . . . . . . . . . . . 2515.3 Computational results . . . . . . . . . . . . . . . . . . 251

6 Second Case Study . . . . . . . . . . . . . . . . . . . . . . . 2546.1 Capacity constraints . . . . . . . . . . . . . . . . . . . 2576.2 Mass ratio constraints . . . . . . . . . . . . . . . . . . 2576.3 Computational results . . . . . . . . . . . . . . . . . . 257

7 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . 260

9. Wastewater Minimisation in Batch Chemical Plants:Multiple Contaminant Media 265Authors: T. Majozi & J. Gouws

1 Multiple Contaminant Wastewater MinimisationBackground . . . . . . . . . . . . . . . . . . . . . . . . . . . 265

2 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . 2663 Mathematical Formulation . . . . . . . . . . . . . . . . . . . 266

3.1 Mass balance constraints . . . . . . . . . . . . . . . . . 2673.1.1 Mass balance constraints without storage . . . . 2673.1.2 Mass balance constraints including central

storage . . . . . . . . . . . . . . . . . . . . . . . 2703.2 Sequencing and scheduling constraints . . . . . . . . . 272

3.2.1 Task scheduling constraints . . . . . . . . . . . 2733.2.2 Recycler/reuse sequencing constraints . . . . . 2743.2.3 Sequencing and scheduling constraints

associated with storage . . . . . . . . . . . . . . 2753.2.4 Feasibility and time horizon constraints . . . . . 277

3.3 Objective function . . . . . . . . . . . . . . . . . . . . 2774 Solution Procedure . . . . . . . . . . . . . . . . . . . . . . . 2785 Illustrative Examples . . . . . . . . . . . . . . . . . . . . . . 278

5.1 First illustrative example . . . . . . . . . . . . . . . . . 2795.1.1 Solution with no central storage vessel . . . . . 2805.1.2 Solution with central storage . . . . . . . . . . . 281

5.2 Second illustrative example . . . . . . . . . . . . . . . 2846 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 286

xxvi Contents

10. Adaptive Swarm-Based Simulated Annealingfor the Synthesis of Water Networks 291

Author: R. R. Tan

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 2912 Simulated Annealing . . . . . . . . . . . . . . . . . . . . . . 2933 Swarm Annealing I . . . . . . . . . . . . . . . . . . . . . . . 2944 Swarm Annealing II . . . . . . . . . . . . . . . . . . . . . . 2975 Algorithm Implementation and Testing . . . . . . . . . . . . 2986 Test Problems . . . . . . . . . . . . . . . . . . . . . . . . . . 299

6.1 Case 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 2996.2 Case 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . 303

7 Discussion of Results . . . . . . . . . . . . . . . . . . . . . . 3068 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307

11. Optimal Wastewater Network Design 311

Authors: J. M. Jezowski, G. Poplewski & I. Dzhygyrey1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 3112 WWTN Problem Formulation and Description . . . . . . . 3143 Literature Overview . . . . . . . . . . . . . . . . . . . . . . 3164 Hybrid Approach for WWTN . . . . . . . . . . . . . . . . . 322

4.1 Overview of the approach . . . . . . . . . . . . . . . . 3224.2 Targeting stage . . . . . . . . . . . . . . . . . . . . . . 3234.3 Structure development optimization stage . . . . . . . 3254.4 Final optimization stage . . . . . . . . . . . . . . . . . 3264.5 Example of application . . . . . . . . . . . . . . . . . . 327

5 Simultaneous Approach with the Use of StochasticOptimization Method . . . . . . . . . . . . . . . . . . . . . . 3305.1 Superstructure and optimization model . . . . . . . . . 3305.2 Overview of solution approach . . . . . . . . . . . . . . 3345.3 Examples of application . . . . . . . . . . . . . . . . . 336

Section 3: Energy Conservation and Eciency 349

12. Clean Energy and CO2 Capture, Transport and Storage 351

Authors: M. S. Ba-Shammakh, A. Elkamel, H. Hashim,P. Douglas & E. Croiset

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 351

Contents xxvii

2 Overview of Power Generation . . . . . . . . . . . . . . . . . 3522.1 Fossil fuel power plants . . . . . . . . . . . . . . . . . . 3532.2 Hydroelectric power plant . . . . . . . . . . . . . . . . 3532.3 Nuclear power plants . . . . . . . . . . . . . . . . . . . 3542.4 Renewable sources power plants . . . . . . . . . . . . . 354

3 CO2 Reduction Options . . . . . . . . . . . . . . . . . . . . 3553.1 Power plant eciency improvement . . . . . . . . . . . 355

3.1.1 Pulverized coal power plant (PC) . . . . . . . . 3573.1.2 Integrated gasication combined

cycle (IGCC) . . . . . . . . . . . . . . . . . . . 3573.1.3 Natural gas combined cycle (NGCC) . . . . . . 358

4 CO2 Capture and Sequestration . . . . . . . . . . . . . . . . 3584.1 CO2 capture . . . . . . . . . . . . . . . . . . . . . . . . 358

4.1.1 Chemical solvent absorption . . . . . . . . . . . 3584.1.2 Physical absorption . . . . . . . . . . . . . . . . 3604.1.3 Physical adsorption . . . . . . . . . . . . . . . . 3604.1.4 Cryogenic separation . . . . . . . . . . . . . . . 3604.1.5 Membrane separation . . . . . . . . . . . . . . . 3614.1.6 O2/CO2 combustion processes . . . . . . . . . . 3614.1.7 Chemical looping combustion . . . . . . . . . . 3614.1.8 Biological capture process . . . . . . . . . . . . 362

4.2 Sequestration . . . . . . . . . . . . . . . . . . . . . . . 3624.2.1 Geologic storage . . . . . . . . . . . . . . . . . . 363

4.2.1.1 Depleted oil and gas reservoirs . . . . 3634.2.1.2 Enhanced oil recovery . . . . . . . . . 3634.2.1.3 Deep saline formations . . . . . . . . . 363

4.2.2 Ocean storage . . . . . . . . . . . . . . . . . . . 3645 Optimization and Planning Models for Power Plants . . . . 3656 Superstructure Representation . . . . . . . . . . . . . . . . . 3687 Mathematical Model Development . . . . . . . . . . . . . . 3718 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . 3829 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 393

13. P-Graph: An Ecient Process Synthesis Tool.Application to Fuel Cell-Based Energy Generation 399

Author: P. Varbanov

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 3992 Basics of P-graph . . . . . . . . . . . . . . . . . . . . . . . . 400

xxviii Contents

2.1 The need for advanced process network optimisationtools . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400

2.2 Process representation with P-graph . . . . . . . . . . 4012.3 Advantages of the P-graph representation . . . . . . . 4022.4 Foundation of the P-graph framework: The axioms . . 4022.5 Algorithms for the network manipulation and

optimisation . . . . . . . . . . . . . . . . . . . . . . . . 4033 Engineering Context: FCCC Systems and Biomass

Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4053.1 Processing steps . . . . . . . . . . . . . . . . . . . . . . 4053.2 Eciency of FC and combined cycles . . . . . . . . . . 405

4 Modelling Procedures . . . . . . . . . . . . . . . . . . . . . . 4064.1 General synthesis procedure . . . . . . . . . . . . . . . 4064.2 Representation of the operating and capital costs . . . 4074.3 Optimisation objective . . . . . . . . . . . . . . . . . . 4074.4 Sensitivity analysis procedure . . . . . . . . . . . . . . 407

5 Applying P-Graph: Heat and Power Generation UsingFCCC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4085.1 Case study description . . . . . . . . . . . . . . . . . . 408

5.1.1 Materials and streams . . . . . . . . . . . . . . 4085.1.2 Candidate operating units . . . . . . . . . . . . 408

5.2 Results and Discussion . . . . . . . . . . . . . . . . . . 4116 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4187 Sources of Further Information . . . . . . . . . . . . . . . . 419

14. A Process Integration Framwork for the OptimalDesign of Combined Heat and Power Systemsin the Process Industries 423

Authors: R. Mahmud, D. Harell & M. El-Halwagi

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 4232 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . 4273 Overall Approach . . . . . . . . . . . . . . . . . . . . . . . . 429

3.1 Mass integration and heat integration approach . . . . 4304 Steam Header Balance . . . . . . . . . . . . . . . . . . . . . 4375 Energy Integration Approach . . . . . . . . . . . . . . . . . 4396 Extractable Work Method . . . . . . . . . . . . . . . . . . . 441

6.1 Case 1: Excess process steam without external fuel . . 4446.2 Case 2: Excess steam with external fuel . . . . . . . . 445

Contents xxix

7 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . 4468 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 456

15. Design and Optimisation of Low TemperatureEnergy Systems 463

Author: J.-K. Kim

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 4632 Design of Refrigeration Systems . . . . . . . . . . . . . . . . 465

2.1 Refrigeration cycle with pure refrigerant . . . . . . . . 4652.2 Heat-integrated cooling and refrigeration . . . . . . . . 4692.3 Refrigeration cycle with mixed refrigerants . . . . . . . 4712.4 Optimisation of refrigeration cycles . . . . . . . . . . . 4742.5 Case study . . . . . . . . . . . . . . . . . . . . . . . . . 475

3 Driver Selection, Design and Optimisation . . . . . . . . . . 4774 Total Site-wide Utility Systems . . . . . . . . . . . . . . . . 4795 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481

16. Indirect Heat Integration of Batch Processes 485

Authors: C.-L. Chen, Y.-J. Ciou & D. C. Y. Foo

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 4852 Characteristics of Streams in Batch Processes . . . . . . . . 4863 Operating Schemes of Batch Heat Integration . . . . . . . . 4874 Pinch Analysis Approach for Indirect Heat Integration . . . 489

4.1 Indirect integration with two-storage system . . . . . . 4904.2 Indirect integration with three-storage system . . . . . 497

5 Mathematic Programming Approach for Indirect HeatIntegration Scheme . . . . . . . . . . . . . . . . . . . . . . . 5005.1 Superstructure . . . . . . . . . . . . . . . . . . . . . . 5025.2 Formulation . . . . . . . . . . . . . . . . . . . . . . . . 5045.3 Example 2: Single product batch plant . . . . . . . . . 5075.4 Heat integration with two storage tanks . . . . . . . . 5115.5 Heat integration with three storage tanks . . . . . . . 513

6 Example 3: A Brewing Process . . . . . . . . . . . . . . . . 5177 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525

17. Energy Eciency and the Integration of Wasteand Renewable Energy Sources 531

Authors: J. J. Klemes, S. J. Perry & I. Bulatov

xxx Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 5312 Heat Integration . . . . . . . . . . . . . . . . . . . . . . . . 5343 Total Site Targeting . . . . . . . . . . . . . . . . . . . . . . 5424 Waste and Renewable Energy Sources . . . . . . . . . . . . 547

4.1 Heat pump . . . . . . . . . . . . . . . . . . . . . . . . 5474.2 Geothermal . . . . . . . . . . . . . . . . . . . . . . . . 5484.3 Biomass . . . . . . . . . . . . . . . . . . . . . . . . . . 5484.4 Solar energy . . . . . . . . . . . . . . . . . . . . . . . . 549

5 Locally Integrated Energy Sector Case Study . . . . . . . . 5506 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 556

18. A Novel Design Procedure for Solar Thermal Systems 561

Author: S. Bandyopadhyay

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 5612 Solar Thermal System Design . . . . . . . . . . . . . . . . . 5623 Mathematical Model . . . . . . . . . . . . . . . . . . . . . . 5634 Generation of Design Space . . . . . . . . . . . . . . . . . . 565

4.1 Establishment of design limit based on loadtemperature . . . . . . . . . . . . . . . . . . . . . . . . 567

4.2 Establishment of design limit based on maximumtemperature . . . . . . . . . . . . . . . . . . . . . . . . 568

4.3 Overall design space and its signicance . . . . . . . . 5695 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 572

19. Energy Saving in Drying Processes 577

Authors: C. L. Law & A. S. Mujumdar1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 5772 Why Conventional Dryers Have Low Energy Eciency . . . 5783 Classication . . . . . . . . . . . . . . . . . . . . . . . . . . 579

3.1 Direct ring . . . . . . . . . . . . . . . . . . . . . . . . 5793.2 Electric heating . . . . . . . . . . . . . . . . . . . . . . 5803.3 Heat recovery . . . . . . . . . . . . . . . . . . . . . . . 581

3.3.1 Heat pump . . . . . . . . . . . . . . . . . . . . 5813.3.2 Use of phase change material (PCM) . . . . . . 582

3.4 Control of dryer . . . . . . . . . . . . . . . . . . . . . . 5824 Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . 582

4.1 Direct ring . . . . . . . . . . . . . . . . . . . . . . . . 5834.1.1 Case study: Fluidized bed dryer . . . . . . . . . 583

Contents xxxi

4.2 Electric heating . . . . . . . . . . . . . . . . . . . . . . 5844.3 Heat recovery . . . . . . . . . . . . . . . . . . . . . . . 584

4.3.1 Case study: Spray dryer . . . . . . . . . . . . . 5844.3.2 Case study: Heat pump . . . . . . . . . . . . . 586

4.4 Control strategy . . . . . . . . . . . . . . . . . . . . . . 5864.4.1 Case study: Model predictive control . . . . . . 5864.4.2 Case study: Feedback controller . . . . . . . . . 5884.4.3 Case study: Model predictive control . . . . . . 588

5 General Guidelines for Energy Savings . . . . . . . . . . . . 5886 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 589

20. Two Birds with One Stone: Simultaneous Waste HeatRecovery and Emission Reduction in Gas/OilSeparation Plants 593

Author: M. B. Noureldin

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 5932 Oil-Gas Separation Plants . . . . . . . . . . . . . . . . . . . 595

2.1 Process description of a gas/oil separation plant(GOSP) . . . . . . . . . . . . . . . . . . . . . . . . . . 595

3 Heat Integration and Software Application in theGOSP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596

4 Results and Discussion of Heat Integration Application inthe GOSP . . . . . . . . . . . . . . . . . . . . . . . . . . . . 598

5 Summary of Comparison . . . . . . . . . . . . . . . . . . . . 6066 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 606

21. Energy Management for the Process Industries 609

Author: A. Rossiter

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 6092 Industry Response . . . . . . . . . . . . . . . . . . . . . . . 610

2.1 Best practices in operation and maintenance . . . . . . 6112.1.1 Electric supply . . . . . . . . . . . . . . . . . . 6112.1.2 Steam system maintenance . . . . . . . . . . . . 6122.1.3 Compressed air systems . . . . . . . . . . . . . 6132.1.4 Heat exchanger cleaning . . . . . . . . . . . . . 6142.1.5 Fired heaters . . . . . . . . . . . . . . . . . . . 6142.1.6 Process equipment . . . . . . . . . . . . . . . . 615

2.2 Identifying economic investment opportunities . . . . . 618

xxxii Contents

2.2.1 Employee contests . . . . . . . . . . . . . . . . 6182.2.2 Process reviews . . . . . . . . . . . . . . . . . . 6192.2.3 Pinch analysis . . . . . . . . . . . . . . . . . . . 6192.2.4 Steam system rebalancing . . . . . . . . . . . . 6212.2.5 By-product synergies . . . . . . . . . . . . . . . 624

2.3 Management systems to sustain progress . . . . . . . . 6263 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 627

Appendix 1: The Procedure for Determining the Datum LevelMaterials 629

Authors: L. T. Fan & Tengyan Zhang

Appendix 2: Estimation of the Specic Chemical Enthalpy,Entropy, and Exergy (Availability) 645


Appendix 3: Derivation of the Mass, Energy, Entropy-dissipation and Available Energy Balances foran Unsteady-state Open Flow System 661


Appendix 4: Estimation of Energy (Enthalpy) and Exergy(Availability) Contents in StructurallyComplicated Materials 675


Appendix 5: Reaction-Network Synthesis Via theGraph-Theoretic Method Based on P-graphs:Vinyl-Chloride Synthesis 711


Appendix 6: Application of Sustainability Potential:Manufacture of Vinyl Chloride (C2H3Cl) 725


Contents xxxiii

Appendix 7: Emergy and Exergy (Availability) 737


Appendix 8: 747

Authors: H. H. Lou, S. Dusija, X. Li,J. L. Gossage & J. R. Hopper

Appendix 9: Mathematical models via Lingo 8.0 773

Authors: X. Feng, J. Bai, R. Shen & C. Deng

Appendix 10: Brief Manual How to Code WWTNProblem in OPTY-STO Modeling System 787

Author: J. M. Jezowski, G. Poplewski &I. Dzhygyrey

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February 21, 2012 8:25 9in x 6in b933-ch01

Section 1

Process Modeling

1


2



ESTIMATION OF EXERGY DISSIPATION AND COST:THE FOUNDATION FOR SUSTAINABILITY

ASSESSMENT IN PROCESS DESIGN

L. T. FAN and TENGYAN ZHANGDepartment of Chemical Engineering,

Kansas State University,Manhattan, KS, 66506, USA

[email protected]

1. Introduction

Every human action or societal undertaking is, macroscopically speaking,an economic activity, intended to yield net prot, i.e., monetary increase,whereas every human action or societal undertaking leads to the entropyincrease, i.e., consumption of available energy (exergy dissipation).1 Thus,to maintain such an activity requires the trade-o between the increase innet prot and the decrease in available energy, or exergy. In other words,the notion of sustainability arises from the need to balance between theincrease in economic benet and the decrease in exergy, corresponding tothe increase in entropy.

Sustainability engineering can be regarded as an engineering disciplineto craft frameworks, or establish paradigms, for attaining sustainabilityin any human or social endeavor, i.e., economic activity; however, it isan emerging discipline of engineering. No discipline of engineering can beenduring without underlying theoretical principles or standing on the rmtheoretical foundation. Obviously, sustainability assessment constitutes theinitial phase of sustainability engineering. Any economic activity givesrise to unintended consequence or consequences, which are not directlytaken into accounts in evaluating the cost of this economic activity; such

All the appendices are available on the CD provided with the book and also posted onthe publishers website.

3

4 L. T. Fan and T. Zhang

consequences are termed externalities.2 More often than not, the eectsof externalities, such as the pollution of surrounding environment by themanufacture of consumer goods or power generation, are undesirable.It, therefore, is entirely logical that the second law of thermodynamicsand notion of externalities of macro-economics be deemed to be themain criteria, or cornerstones, of sustainability assessment. In processdesign, thermodynamic constraints in terms of entropy increases manifestthemselves in exergy dissipation,3,4 and economic constraints in terms ofexternalities manifest themselves in cost;2,5 it is worth reminding ourselvesthat There aint such a thing as a free lunch.

2. Thermodynamic Foundations

Reiterating what is pointed out in Sec. 1, thermodynamic constraints onany system or process in terms of entropy increase manifest themselvesin exergy dissipation by the process, which can be evaluated by resortingto the available energy balance. The available energy balance results fromthe combination of the rst and second laws of thermodynamics.3,4,612 Inreality, however, it also implicitly embodies the mass conservation law: theavailable energy balance entails the detailed accounting of each materialspecies involved in the process. This renders it possible to determine thetransformation of its inherent available energy pertinent to its chemicalchanges, which is termed chemical exergy. Note that all the thermodynamicproperties are measured relative to the same reference state that isspecically dened.

2.1. Reference states

In principle, any arbitrary state may be selected as a datum level to evaluatethermodynamic state properties of any material species. This arbitrarystate is generally referred to as the reference state, at which the values ofone or more state properties of matter are assumed to be zero. Nevertheless,while the values of the state functions vary according to the reference statesdesignated, the rst and second laws of thermodynamics remain valid.6,9

2.1.1. Standard stateIn the conventional treatment of thermodynamics, the standard state isdened in terms of the prevailing environmental temperature, T 0, theprevailing environmental pressure, P0, and all the pure elements.4,6,7,1315

Estimation of Exergy Dissipation and Cost 5

For convenience, T 0 and P 0 are specied, respectively, as

T 0 = 298.15K,

P 0 = 1 atm.

By denition, the concentration of any pure element i at the standard state,x0i , is an unity, i.e.,

x0i = 1; i = 1, 2, . . . , k, (k = number of elements).

The values of state properties, such as enthalpy and free energy, ofvarious substances at the standard state relative to this reference stateare available in most treaties on classical thermodynamics;16 for instance,enthalpy and free energy are called the standard enthalpy of formation andthe standard free energy of formation, respectively. While the values ofthese thermodynamic functions for any element are zero, those for most,but not all, of the compounds are negative. This renders it impossibleto consistently evaluate the thermodynamics eciency straightforwardly,especially when chemical reactions are involved in the process of concern.Thus, dening an appropriate reference state is of paramount importancefor the thermodynamic analysis.4,6,17,18 In fact, from a practical viewpoint,it would often be desirable for the reference state to be shifted from thatmentioned above to the so-called dead state.

2.1.2. Dead stateThe dead state is a natural extension of the notion of the standard state;therefore, it can be regarded as the extended standard state. The rationalebehind such an extension is that the pure elements seldom prevail underthe environmental conditions. Frequently, they are chemically active andreact spontaneously with the substances in the surrounding environments,thus releasing in the chemical form of latent energy or available energy. Infact, some elements even explosively react in the surrounding environments.For instance, iron (Fe) slowly undergoes oxidation in the environment,thereby eventually becoming one variety of rust, i.e., ferrous complex5Fe(SO4)32Fe(OH)3; with the slightest disturbance, hydrogen H2 anddust of carbon C may explosively react with oxygen O2 in the air, thusyielding water H2O (l) and carbon dioxide CO2, respectively. The foregoingarguments imply that it is indeed untenable to recognize or identify allthe pure elements as totally neutral and stable substances under theenvironmental conditions; hence, not all the pure elements are appropriate



to serve as the references for measuring various thermodynamic functions orthermal properties of other materials. To follow the paradigm of specifyingthe environmental temperature and pressure as the components of thestandard state, another set of reference substances, each corresponding toa single element, needs to be specied. This has given rise to the notionof the datum level materials. These materials in conjunction with theenvironmental temperature and pressure constitute the dead state;3,4,6,19

analogous to the standard state, the environmental temperature andpressure are usually taken to be 298.15K and 1 atm, respectively. Thedierences of the conventional standard state and the dead state areillustrated in Fig. 1.

Formally, the datum level materials are dened to be the compoundsor elements, which are not only thermodynamically stable but also exist

M (TM)

Q[TM]

P1

P2

Q0[T0]

A

Environment

(Reactor)

R1

R2

B(R1)0 B(R2)0 B(P2)0 B(P1)0

Environment( T0, P0, xi0=1)

(T0, P0, xi,0)

Fig. 1. Isolated overall system encompassing a steady-state open ow system (systemA), a heat source at temperature TM (system M), and the entire surroundings at theenvironmental temperature of T0 and the environmental pressure of P0. In the text,entering streams R1, R2, . . . are designated by subscript i; and exiting streams P1, P2, . . .are designated by subscript e.



in abundance in the environment; they are regarded as void of energy oravailable energy at the dead or extended standard state. In other words,each element has a natural tendency to be part of its datum level material.For instance, the aforementioned 5Fe(SO4)32Fe(OH)3, H2O (l), and CO2are the datum level materials for Fe, H, and C, respectively.4,6,8,9,19

According to Petit and Gaggioli,10 the dead state is the state that eachconstituent of the substance is in complete stable equilibrium with thecomponents in the environment. Note that subscript 0 stands for the deador extended standard state, instead superscript 0 stands for the standardstate; thus,

T0 = 298.15K,

P0 = 1 atm,

xi0 = environmental composition of the corresponding datum

level material i = 1, 2, . . . , k (k = number of elements).

In general, enthalpy of a substance, comprising physical, thermal andchemical enthalpy, and exergy, comprising physical, thermal and chemicalexergy, are measured relative to the dead state or extended standardstate.3,4,6,8,9,20 The enthalpy of formation and free-energy of formation ofthis substance at the dead state are invariably non-negative. As such, theenergy and available energy balances can be executed in a straightforwardmanner around any given system (process), or arbitrary segment of thesystem. This gives rise to the energy loss from and the available energyconsumption, i.e., exergy dissipation, of the process or segment of theprocess. Thus, dead-state-based thermodynamics renders it possible tocarry out the multi-scale thermodynamic analysis of a process necessaryfor the assessment of its sustainability on the uniformly consistent platformat any desired level of details. This is not the case with the standard-state-based thermodynamics: the standard enthalpy of formation and free-energy of formation of a substance are evaluated relative to the pureelements contained in it. Moreover, under the environmental conditions,many of these elements are neither the most stable nor abundant amongall the substances comprising the elements. The standard enthalpy offormation and free-energy of formation, therefore, can be positive ornegative depending on the substances.

Note that the systems energy (enthalpy) and available energy (exergy)depend on the extent of its deviation from the dead state. In other



words, any deviation (the physical, thermal and/or chemical deviations)of the systems state from the dead state, induced by physical, thermaland/or chemical processes, results in the systems energy and availableenergy. Thus, the partial molar enthalpy relative to the dead state, , thepartial molar entropy relative to the dead state, , and the partial molarexergy relative to the dead state, , can be estimated from the followingequations.6,8,9,21

24partial molarenthapyat T and P

35= 02

4partial molarchemicalenthapy

35+ T24partial molarthermalenthapy

35+ P24partial molarpressureenthapy

35

= 024partial molarchemicalenthapy

35+

TT0

cp dTtemperatureeect

+ P

P0

[V T

(V

T

)P

]dP,

pressureeect

(1)

24partial molarentropyat T and P

35= 02

4partial molarchemicalentropy

35+ T24partial molarthermalentropy

35+ P24partial molarpressureentropy

35

= 024partial molarchemicalentropy

35+ T

T0

cpT

dTtemperatureeect

+

( P

P0

(V

T

)P

dP

),

pressureeect

(2)

24partial molarexergyat T and P

35= 02

4partial molarchemicalexergy

35+ T24partial molarthermalexergy

35+ P24partial molarpressureexergy

35

= 024partial molarchemicalexergy

35+ T

T0

cp

(1 T0

T

)dT

temperatureeect

+ P

P0

[V (T T0)

(V

T

)P

]dP.

pressureeect

(3)

The values of the partial molar chemical enthalpy, 0, the partial molarchemical entropy, 0, and the partial molar chemical exergy, 0, of manymaterial species in the above expressions can be found in various sources.9,21



The evaluation of the energetical quantities, 0 and 0, demands thedetailed accounting of the ow of each material species participating inthe process, the outcome of which is the inherent coupling of the mass owand the energy ow. Naturally, the specic chemical enthalpy, the specicchemical entropy, and specic chemical exergy (or the specic chemicalavailability) are represented by 0, 0, and 0, respectively.

A unique datum level material with a specic concentration at the deadstate can be identied, i.e., determined, for each element (see Appendix 1).Naturally, 0, 0, and 0, of the element are specic. All such information,therefore, can be conveniently included in the periodic table. Each block ofthe resultant augmented periodic table will then contain six items. Theseare the symbol of an element, the molecular formula of its datum levelmaterial, the concentration of the datum level material at the dead state,0 of the element, 0 of the element; and 0 of the element. A set of datumlevel materials for 96 elements have been determined, thereby giving rise tothe so-called Thermodynamic Periodic Table (see Appendix 1). By resortingto this table, 0, 0, and 0 of any material species can be determined (seeAppendix 2).

The denition of implies that 0 of a combustible material, containingC, H, N and O, is essentially equal to the negative of the conventional heat ofcombustion of the higher heating value (H.H.V.). One reason is that both 0and H.H.V. are evaluated on the basis of the same set of reference materials,which are CO2 (g), O2 (g), N2 (g), and H2O (l) for elements C, H, N andO, respectively; the values of 0, 0 and 0 for a datum level (or reference)material are zero. Another reason is that the pressure has a negligibly smalleect on the specic chemical enthalpies around the conditions of

T0 = 298.15K,

P0 = 1 atm.

Note that CO2 (g), O2 (g), N2 (g), and H2O (l) are considered to be theproducts of complete combustion of a compound containing C, O, N, andH with excess oxygen. Clearly, the dierence between 0 and H.H.V. canbe substantial if a compound contains constituents other than C, O, N,and H. Also note that the standard heat of combustion, or H.H.V., canbe dened and measured only for combustible materials. In contrast, 0can be dened and theoretically speaking, measureable for all materials.For convenience, in place of 0, the values of H.H.V. are often adopted inevaluating the thermodynamic rst-law eciencies of processes, such as coal



gasication and biomass pyrolysis,22 which mainly involve the combustiblematerials.

The denition of as expressed in Eq. (1) tends to give rise to a non-negative value. Nevertheless, if a datum level material of some substanceis involved in a low-temperature or low-pressure process, for example, acryogenic process, the value of its may assume a small negative value.More often than not, however, this small negative value is compensatedby large positive values of of other material species involved in the sameprocess, thereby rendering the input to or output from the system to have anon-negative overall energy (enthalpy) content. The use of the conventionaldenition of the specic enthalpy, h, evaluated in reference to the pureelements at the standard state, tends to yield a negative energy contentmore often than the use of the denition of . As a result, dening , asshown in Eq. (1), will facilitate the evaluation of the rst-law eciency.

The partial molar exergy, , as dened by Eq. (3), is a measure of thepotential of a component in a mixture to do work. It is a state variableand is uniquely specied by the temperature, pressure and composition ofthe mixture; it is independent of the path or direction of the change of thestate of the mixture. The partial molar exergy, , comprises three terms,i.e., 0, T, and P. The partial molar chemical exergy, 0, is always non-negative. The partial molar thermal exergy, T, as indicated in Eq. (3), isalso a non-negative quantity, independent of the system temperature, whichmay be higher or lower than the datum level temperature, T0. The partialmolar pressure exergy, P, as given in Eq. (3), is the only term among 0,T, and P, which may not always remain non-negative; it is non-negativewhen P is larger than P0 or smaller than P0x0. Recall that P0 stands forthe datum level pressure, and x0 for the datum level concentration. Forcondensed matter, a solid or liquid substance, the pressure eect is usuallysuciently small so that P can often be neglected. For a gaseous substance,the absolute value of P is always less than or equal to that of 0, which isalways positive, i.e.,

PP0

[V (T T0)

(V

T

)P

]dP 0. (4)

Consequently, the value of is always non-negative. For instance, x0 ofCO2 (g) is 0.000302. When its pressure, P , is at P0x0, the value of P is4.8002kcalgmol1. This value is essentially the specic chemical exergy ofCO2 (g) because it is the datum level material of element C. Furthermore,



care must be taken when P is evaluated for a material whose pressure islower than P0x0, where x0 is the datum level concentration of the material.

For the material under such a condition, P may be decomposed intotwo terms, the rst for the range of pressure from P0 to P0x0 and thesecond from P0x0 to P whose value is less than P0x0. The rst term isalways positive. The available energy needed to bring the system pressurefrom P0x0 to P is considered to be stored in the material itself rather thanin the environment.4,7

A positive 0 for a material species implies that a supply of energyto the material species is required during its transition from its chemicalstate to its dead state; in contrast, a negative 0 implies that the materialspecies releases energy during its transitions from its chemical state to itsdead state. More specically, 0 for a gaseous datum level material is alwaysnegative; its magnitude is equal to the entropy change of a unit quantity ofthis material when its concentration at the chemical state is diluted to thatat the environmental (or dead) state through a variety of processes, e.g.,diusion. 0 for a liquid or solid datum level material is always zero sinceit is considered to be a pure phase. On the other hand, 0 for a materialspecies, which is not the datum level material, can be either positive ornegative. Its value of 0 can be determined by visualizing, or simulating,the transformation (or decomposition) of this material into its datumlevel material through a sequences of so-called reference reactions4,8 whichbrings the material from the chemical state to the dead state. Obviously,0 can be negative although it is not always the case; it can also bepositive.

The values of 0, 0, and 0 of 53 industrially important materialspecies have been computed; the results are tabulated in Table 1. Thethermodynamic data required for this computation have been obtainedfrom the three monographs.2325 It is worth noting that the values of 0, 0,and 0 of pure elements, other than H2 (g), O2 (g), N2 (g), C (s), Ca (s),S (s), Mg (s), Fe (s), Na (s), Si (s), and Ag (s) included in Table 1, arealso available in the aforementioned Thermodynamic Periodic Table (seeAppendix 1).

2.2. Balances of mass, energy, entropy-dissipation,and available energy

A system of concern in which a phenomenon or process occurs isthermodynamically dened or specied in terms of its mass, energy,



Table 1. Specic chemical enthalpy, entropy, and exergy of material species.

Material 0 (kcalgmol1) 0 (kcalgmol1K1) 0 (kcalgmol1)

H2 (g) 68.32 40.546103 56.23O2 (g) 0 -3.1067103 0.9263N2 (g) 0 -0.4937103 0.147CO2 (g) 0 -16.1103 4.8002CO (g) 67.636 6.1067103 65.815C (s) 94.052 -13.682103 98.131CH4 (g) 212.803 48.118103 198.457NO (g) 8.091 -17.904103 13.429NH3 (g) 91.44 36.824103 80.456Ca (s) 223.9 166.369103 174.44S (s) 122.52 -57.4856103 139.66SO2 (g) 51.58 -57.927103 68.85H2O (g) 10.39 28.452103 1.907H2S (g) 186.3 6.659103 187.921C2H4 (g) 337.28 0.040952 325.13C2H6 (g) 327.824 0.05275 357.19C6H5OH (l) 729.52 -53.57103 745.4914C6H5CH3 (l) 933.56 -15.76103 938.2603NO2 (g) 8.091 -0.0179 13.429HCN (g) 159.352 0.0147 154.96HCN (l) 153.352 -0.00654 155.36C6H6 (g) 809.95 -0.024 817.11CaO (s) 72.3 0.1394 30.74Mg (s) 205.06 -0.0029 205.93Fe (s) 205.32 0.3084 113.38CaCO3 (s) 29.552 0.0837 4.583MgCO3 (s) 37.11 -0.0883 63.4432SiO2Al2O3 (s) 77.58 0.00929 74.81Fe2O3 (s) 213.34 0.5465 50.4FeS2 (s) 407.96 0.1843 353.01SiO2 (s) 0 0 0H2O (l) 0 0 0air (g) 0 0 0C6H5OH (g) 746.17 -13.24103 750.12C6H5CH3 (g) 965.8 -0.01838 971.29C6H6 (l) 780.98 -0.020942 787.224C3H8 (g) 530.326 0.06246 511.708C4H8 (l) 612.81 0.071764 600.358C4H10 (l) 687.8 0.059807 669.951COS (g) 183.03 -0.050968 198.226NO (g) 21.6 0.001136 21.26NH4Cl (s) 124.96 -0.003037 125.866Na (s) 111.5 0.0857 85.98Na2CO3 (s) 46.79 0.08695 20.866Na2SO3 (s) 184.92 0.2683 104.913

(Continued)


Table 1. ( Continued )Material 0 (kcal gmol 1 ) 0 (kcal gmol 1 K 1) 0 (kcal gmol 1 )

Na2SO4 (s) 113.97 0.3488 9.9696Si (s) 217.7 0.0467 203.78NaOH (s) 43.36 0.067516 23.23NaCl (s) 76.76 0.06946 56.03Ag (s) 17.469 0.01627 12.619AgBr (s) 47.969 0.0257 40.312AgCl (s) 50.669 0.03779 40.403AgI (s) 45.169 0.0205 39.031

entropy-dissipation, and available energy balances.3,4,6 12,19,20 Naturally,the overall system encompasses work and heat sources, work and heatsinks, and the entire surroundings, i.e., environments, besides the systemitself. It is regarded that, except energy (enthalpy) and available energy(exergy) of the mass owing through this system, other forms of energy,such as potential energy and kinetic energy, are negligible. The changesin the enthalpy and exergy of the streams of mass, or simply streams,through the system are induced by the transfer of energy as heat or workbetween the system and the work and heat sources, work and heat sinks, orthe systems surroundings. For simplicity, the aforementioned four balanceswill be written around the system with multiple input and output streamsunder the steady-state open ow conditions; see Fig. 2(a).

2.2.1. Mass balanceBy taking into account both convective and diusional ows, the massbalance yields

iM i =

mass owrateinto the system

e

M e.

mass owrateout of the system

(5)

In terms of the molar ow rate, the above expression can be rewritten as

i

k(M w )k nk

i

=

e

k(M w )k nk

e

.

mass owrateinto the system

mass owrateout of the system

(6)


Ni

|Wi|

MiTi

|Qi|

Ne

|We|

C1

C2

L

B1

B2

MeTe

|Qe|

|Q0||(WX)0|

System(e.g., Process Plant)

T

Surroundings(T0, P0)

Isolated Overall System

Boundary

Fig. 2(a). Isolated overall system encompassing a steady-state open ow system (systemof concern), a heat source (M i ) at temperature Ti , a heat sink ( M e) at temperature Te ,a work source (N i ), a work sink (N e), and the entire surroundings at the environmentaltemperature of T0 and the environmental pressure of P0 : In the text, entering streamsB 1 , B 2 , . . . are designated by subscript i ; and exiting streams C1 , C2 , , L , the last beingthe leaking stream (leakage), are designated by subscript e; and the useful, discarded andleaking streams among the exiting streams are dierentiated by additional subscripts u,d, and l , respectively.

2.2.2. Energy balanceThe energy balance equation yields

i

k

fl k nk

i

+ [ |Wi | + |Qi | ]

rate of energy(enthalpy) contentsof material speciesowing into the system

rate ofwork suppliedto the system

rate ofheat suppliedto the system



=

{[e

(k

knk

)e

]+ [ |We| + |Qe| ]

[rate of energy(enthalpy) contentsof material speciesowing out of the system

] [rate of worksuppliedfrom the system

] [rate of heatsuppliedfrom the system

]

+ [ |Q0| + |(Wx)0| ]}.[

rate ofheat lossfrom the system

] [rate ofwork lossfrom the system

] (7)

Even under steady-state ow conditions, some parts of the system, suchas the surface of a rotating shaft of any pump, do the work againstthe surroundings, or continuously generate electric charges, which aredischarged to the surroundings. This leads to the work loss, |(Wx)0|, whichis transformed into thermal energy and is subsequently transferred to thesurroundings as heat. The term, |(Wx)0|, therefore, should be combinedwith the heat loss, |Q0|, thereby constituting the total heat loss to thesurroundings, |Q0w|; thus,

|Q0w| = |Q0| + |(Wx)0|.[rate of totalheat lossfrom the system

] [rate ofheat lossfrom the system

] [rate ofwork lossfrom the system

]

This renders it possible to rewrite Eq. (6) as{[i

(k

knk

)i

]+ [ |Wi| + |Qi| ]

}[rate of energy(enthalpy) contentsof material speciesowing into the system

] [rate ofwork suppliedto the system

] [rate ofheat suppliedto the system

]

=

{[e

(k

knk

)e

]+ [ |We| + |Qe| ]

[rate of energy(enthalpy) contentsof material speciesowing out of the system



]

+ |Q0w|}.

[rate oftotal heat lossfrom the system

] (8)


Note that the energy content of the isolated overall system remains invariantregardless of whether the analysis for a system of concern is under steady-state or unsteady-state ow conditions.

2.2.3. Entropy-dissipation balanceThe principle of entropy increase, which is a manifestation of the second lawof thermodynamics, states: The entropy of an isolated system increases orin the limit remains constant;13,26 consequently,

dSdt

iso 0.

The above equation can be rewritten as:26

(S)iso 0. (9)

In this expression, subscript iso stands for the isolated system. Theaforementioned overall system is one such system as previously indicated:it encompasses the system of concern and its surroundings. It is oftenconvenient to transform Eq. (9) into an equality by introducing a non-negative quantity, , dening the rate of entropy creation in the isolatedoverall system; this gives rise to

(S)iso . (10)

By considering all the quantities that lead to the change in entropy,we obtain

(S)iso = =

e

k k nk

e

rate ofentropy increasein the isolatedoverall system

rate ofentropy increasein the isolatedoverall system

rate ofentropy contentsof material speciesowing out of the system

+|Qe|Te

i

k k nk

i

rate of entropy increaseaccompanied by heat suppliedfrom the system

rate ofentropy contentof material speciesowing into the system

+|Qi |Ti

+|Q0w |

T0.

rate of entropy increaseaccompanied by heat suppliedto the system

rate of entropy increaseaccompanied by heat lossfrom the system

(11)


As indicated in connection with the energy balance, |Q0w| in the aboveexpression includes the work loss, |(Wx)0|, as well as the heat loss, |Q0|, tothe surroundings.

2.2.4. Available energy balanceCombining the energy balance, Eq. (8), and the entropy creation, Eq. (11),gives rise to

i

k

( T0)knk

i

+

|Wi| + |Qi|

1 T0Ti

rate of availableenergy contentsof material speciesowing into the system

rate of worksuppliedinto the system

rate of heatsuppliedinto the system

=

e

k

( T0)knk

e

+

|We| + |Qe|

1 T0Te

rate of availableenergy contentsof material speciesowing out of the system

rate of worksuppliedfrom the system

rate of heatsuppliedfrom the system

+ T0.

rate of availableenergy dissipationfrom the system

(12)

In light of the aforementioned denitions of and , term (T0) in theabove equation has a connotation of the available energy of molar species,for which symbol is coined; it is dened as the partial molar exergy; thus,

= T0.

specic availableenergy contentper unit massat T and P

specic energy(enthalpy) contentper unit massat T and P

temperatureat the deadstate

specic entropycontentper unit massat T and P

(13)

Hence, Eq. (11) can be rewritten as

i

k

knk

i

+

|Wi| + |Qi|

1 T0Ti

rate of availableenergy contentsof material speciesowing into the system

rate of worksuppliedto the system

rate of heatsuppliedto the system



=

{[e

(k

knk

)e

]+

[|We| + |Qe|

(1 T0

Te

)]}[rate of availableenergy contentsof material speciesowing out of the system



]

+ T0.[rate of availableenergy dissipationfrom the system

](14)

The quantities in the brace on the left-hand side of the above equation havean implication of the total available energy input to system A. Note thatthey are not equal to the quantities in the brace on the right-hand sideof equation that have an implication of the total available energy exitingfrom the system. Their dierence, T0, signies the energy dissipated byall types of irreversibility, which is transferred as thermal energy or heatfrom the system to its surroundings under the environmental conditions,as elaborated earlier. The above three balances can be extended to theunsteady-state open ow system with multiple input and output streamsunder the unsteady-state ow conditions (see Appendix 3). Such a systemreduces to the corresponding steady-state open ow system if the stateand velocity of the uid entering and leaving the system as well as thestate within the system remain invariant. It should be pointed out that thederivations of various balances are carried out for the system dened suchthat Ti > T > Te > T0; obviously, we have T0/Ti < 1 and T0/Te < 1.

2.3. First-law and second-law conservation (process)eciencies

The thermodynamic rst-law conservation (process) eciency, (1)p, of aprocess system is dened as:3,4,612,19,20

(1)p [energy transfer of the desired kind achieved by the system][energy input into the system] .(15)

Moreover, the thermodynamic second-law eciency, (2)p, is dened as

(2)p

[available energy transfer of the desired kind achieved

by the system

][available energy input into the system]

. (16)



In connection with the aforementioned energy and available energybalances, we have

(1)p [

e,u

(k knk

)e,u

]+ [ |We|+ |Qe| ][

i

(k knk

)i

]+ [ |Wi|+ |Qi| ]

, (17)

(2)p [

e,u (

k knk)e,u]+ [|We|+ |Qe| (1 T0/Te)][

i (

k knk)i]+ [|Wi|+ |Qi| (1 T0/Ti)]

. (18)

The thermodynamic eciency may assume many forms and expressionsdierent from the above two expressions. Nevertheless, the signicance ofeach form or expression is best understood in the light of the mass, energy,and available energy balances presented in the preceding subsection. Thus,it is of primary importance in a thermodynamic analysis of any system toestablish the valid energy and available energy balances and rigorousevaluation of various loss and dissipation terms in the balance expressions.

Suppose that the boundary of the system in Fig. 2(a) is expanded asillustrated in Fig. 2(b), to include not only the process plant but also theplant for generating power as well as the lines for transmitting the powerrequired by the utilities, such as electricity, steam, and compressed air, tomaintain the plant operation. Then, the available energy balance aroundthe system, i.e., Eq. (14), reduces to

Exf + Exi = Expm + Expe + Exw + Exd, (19)

where Exf is the exergy of the feeds including raw materials and/or fuels;Exi, the exergy of the work and available thermal energy (heat) suppliedto the system; Expm , the exergy of products; Expe , the work and availablethermal energy usefully extracted out of the system; Exw, the exergy of thewastes; and Exd, the dissipated exergy. In Eq. (19), the sum, (Exf +Exi), inthe left-hand side represents the input of exergy to the system, and the sum,(Expm+Expe), in the right-hand side represents the output of useful exergyfrom the system. Hence, according to the denition of (2)p expressed byEq. (16), we have

(2)p =Expm + ExpeExf + Exi

. (20)

Naturally, 0 (2)p < 1, and the larger the (2)p, the more sustainable theprocess. Thus, (2)p might also be regarded as a sustainability index.



Process Plant

Power Plant

Raw MaterialsExf

DissipationExd

Fuel Gas

FuelsExf

WastesExw

UtilitiesTransmission

lines

Boundary

Surroundings(To, Po)

Reactor(Biomass Pyrolysis Reactor)

ExpmBiomass and Air Fuel Gas

Exf = 0.6 10

6 kcal h1

Exf = 0.3 10

6 kcal h1

Exf = 2.69 10

6 kcal h1

Exf = 1.28 10

6 kcal h1

Fig. 2(b). The system resulting from expanding the boundary of the system depictedin Fig. 2(a) for multi-scale evaluation of thermodynamic eciencies: biomass pyrolysissystem where biomass is fed into a biomass pyrolysis reactor, i.e., pyrolizer, to generatepyrolysis gas as product and char as waste; a portion of the pyrolysis gas is burnt inthe pyrolizer to maintain its temperature; and the remainder is usable for the burnerand boiler.

The reactor in Fig. 2(b) is a biomass pyrolizer for which the pertinentdata are available.27 For this pyrolizer, a portion of the pyrolysis gas isburnt to maintain its temperature as noted in the caption of the gure,thus eliminating the need to supply heat; and work required to feed thebiomass and air is regarded as negligibly small. Moreover, neither usefulwork nor available thermal energy is extracted out of it. Consequently, forthe smallest system encircled by the dotted line, Exi and Expw in Eq. (20)vanish; accordingly, its second-law conservation eciency is:


=1.28 106 kcal h1 + 02.69 106 kcal h1 + 0 = 47.58%.

For illustration, the detailed thermodynamic analysis for the smallestsystem is presented in Sec. 2.4.2. For the larger system, i.e., the biomass



pyrolysis plant, encircled by the solid line, Exi includes only the utilitiesfor operating the plant, [|Win|+ |Qin|(1T0/Tin)], which is assumed to be0.3 106 kcal h1. Moreover, neither work nor available thermal energy isextracted usefully from it, i.e., Expe can be neglected. Thus, Eq. (20) givesrise to its second-law conservation eciency as


=1.28 106 kcal h1 + 0

2.69 106 kcal h1 + 0.3 106 kcal h1= 42.81%.

The largest system, enclosed by the dashed line, includes all theinfrastructure for supplying the utilities to the plant, the major componentsof which are the power plant and transmission lines. The power plantneeds to be fed with fuel for generating sucient power for the utilitiesand that for compensating the transmission loss. The exergy content offuel, which is part of Exf of this system, therefore, is assumed to be0.6 106 kcal h1. Obviously, neither work nor available thermal energy isextracted usefully out of the system. Thus, Eq. (20) yields its second-lawconservation eciency as


=1.28 106 kcal h1 + 0

(2.69 106 + 0.6 106) kcal h1 + 0 = 38.91%,

where coal is considered to be the fuel for the power plant. If coal is replacedby photons in the form of solar radiation, which is regarded as free,28 thecorresponding second-law conservation eciency is increased to


=1.28 106 kcal h1 + 0

(2.69 106 + 0) kcal h1 + 0 = 47.58%.

In assessing the sustainability of any system, however, the costs of all thefacilities within it also need to be taken into account. For instance, drivingthe power plant by solar radiation might not be economically viab

Recent Advances Sustainable Process 12

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