Computer simulated plant design for waste minimization/pollution prevention

Environmental science combined with computer technology. One click on a mouse and information flows into your PC from up to 10,000 miles away. When you receive this information you can ferret through the data and use it in any number of computer programs. The result: solutions to plant design problems that affect the health and well being of people around the globe. What does that mean to you, the environmental professional, scientist, or engineer?
Computer Simulated Plant Design for Waste Minimization/Pollution Prevention builds on the concepts introduced in Stan Bumble's Computer Generated Physical Properties, the first volume of the Computer Modeling for Environmental Management series. Bumble discusses using computer simulation programs to solve problems in plant design before they occur. He covers design issues for stationary and non-stationary sources of pollution, global warming, troposcopic ozone, and stratospheric ozone.
With Computer Simulated Plant Design for Waste Minimization/Pollution Prevention you will understand how to use computer technology to design plants that generate little or no pollution. Even better, you can use the information generated by computer simulation for technical data in proposals, presentations and as the basis for making policy decisions.

Part I. Pollution Prevention and Waste Minimization
1.1 Chemical Process Structures and Information Flow	p. 1
1.2 Analysis Synthesis and Design of Chemical Processes	p. 1
1.3 Strategy and Control of Exhausts	p. 2
1.4 Chemical Process Simulation Guide	p. 5
1.5 Integrated Design of Reaction and Separation Systems for Waste Minimization	p. 6
1.6 A Review of Computer Process Simulation in Industrial Pollution Prevention	p. 7
1.7 EPA Inorganic Chemical Industry Notebook Section V	p. 11
1.8 Models	p. 11
1.9 Process Simulation Seen as Pivotal in Corporate Information Flow	p. 12
1.10 Model-Based Environmental Sensitivity Analysis for Designing a Clean Process Plant	p. 13
1.11 Pollution Prevention in Design: Site Level Implementation Strategy For DOE	p. 13
1.12 Pollution Prevention in Process Development and Design	p. 14
1.13 Pollution Prevention	p. 15
1.14 Pollution Prevention Research Strategy	p. 16
1.15 Pollution Prevention Through Innovative Technologies and Process Design at UCLA's Center for Clean Technology	p. 17
1.16 Assessment of Chemical Processes with Regard to Environmental, Health, and Safety Aspects in Early Design Phases	p. 19
1.17 Small Plants, Pollution and Poverty: New Evidence from Brazil and Mexico	p. 20
1.18 When Pollution Meets the Bottom Line	p. 20
1.19 Pollution Prevention as Corporate Entrepreneurship	p. 20
1.20 Plantwide Controllability and Flowsheet Structure of Complex Continuous Process Plants	p. 21
1.21 Development of COMPAS	p. 21
1.22 Computer-Aided Design of Clean Processes	p. 21
1.23 Computer-Aided Chemical Process Design for P2	p. 23
1.24 LIMN-The Flowsheet Processor	p. 23
1.25 Integrated Synthesis and Analysis of Chemical Process Designs Using Heuristics in the Context of Pollution Prevention	p. 23
1.26 Model-Based Environmental Sensitivity Analysis for Designing a Clean Process Plant	p. 23
1.27 Achievement of Emission Limits Using Physical Insights and Mathematical Modeling	p. 24
1.28 Fritjof Capra's Foreword to Upsizing	p. 24
1.29 ZERI Theory	p. 24
1.30 SRI's Novel Chemical Reactor - PERMIX	p. 25
1.31 Process Simulation Widens the Appeal of Batch Chromatography	p. 25
1.32 About Pollution Prevention	p. 25
1.33 Federal Register/Vol. 62, No. 120/Monday, June 23, 1997/Notices/33868	p. 26
1.34 EPA Environmental Fact Sheet, EPA Releases RCRA Waste Minimization PBT Chemical List	p. 26
1.35 ATSDR	p. 27
1.36 OSHA Software/Advisors	p. 27
1.37 Environmental Monitoring for Public Access and Community Tracking	p. 27
1.38 Health: The Scorecard That Hit a Home Run	p. 28
1.39 Screening and Testing for Endocrine Disruptors	p. 28
1.40 Reducing Risk	p. 28
1.41 Risk: A Human Science	p. 32
1.42 IPPS	p. 35
Part II. Mathematical Methods
2.1 Linear Programming	p. 37
2.2 The Simplex Model	p. 37
2.3 Quadratic Programming	p. 37
2.4 Dynamic Programming	p. 37
2.5 Combinatorial Optimization	p. 37
2.6 Elements of Graph Theory	p. 37
2.7 Organisms and Graphs	p. 38
2.8 Trees and Searching	p. 38
2.9 Network Algorithms	p. 38
2.10 Extremal Problems	p. 38
2.11 Traveling Salesman Problem (TSP)-Combinatorial Optimization	p. 38
2.12 Optimization Subject to Diophantine Constraints	p. 39
2.13 Integer Programming	p. 39
2.14 MINLP	p. 39
2.15 Clustering Methods	p. 39
2.16 Simulated Annealing	p. 39
2.17 Tree Annealing	p. 40
2.18 Global Optimization Methods	p. 40
2.19 Genetic Programming	p. 41
2.20 Molecular Phylogeny Studies	p. 42
2.21 Adaptive Search Techniques	p. 42
2.22 Advanced Mathematical Techniques	p. 42
2.23 Scheduling of Processes for Waste Minimization	p. 42
2.24 Multisimplex	p. 43
2.25 Extremal Optimization (EO)	p. 43
2.26 Petri Nets and SYNPROPS	p. 43
2.27 Petri Net-Diagraph Models for Automating HAZOP Analysis of Batch Process Plants	p. 43
2.28 DuPont CRADA	p. 45
2.29 KBDS-(Using Design History to Support Chemical Plant Design)	p. 45
2.30 Dependency-Directed Backtracking	p. 45
2.31 Best Practice: Interactive Collaborative Environments	p. 46
2.32 The Control Kit for O-Matrix	p. 46
2.33 The Clean Process Advisory System: Building Pollution Into Design	p. 47
2.34 Nuclear Facility Design Considerations That Incorporate WM/P2 Lessons Learned	p. 47
2.35 Pollution Prevention Process Simulator	p. 48
2.36 Reckoning on Chemical Computers	p. 48
Part III. Computer Programs for Pollution Prevention and/or Waste Minimization
3.1 Pollution Prevention Using Chemical Process Simulation	p. 51
3.2 Introduction to the Green Design	p. 51
3.3 Chemicals and Materials from Renewable Resources	p. 52
3.4 Simulation Sciences	p. 52
3.5 EPA/NSF Partnership for Environmental Research	p. 53
3.6 BDK-Integrated Batch Development	p. 54
3.7 Process Synthesis	p. 54
3.8 Synphony	p. 56
3.9 Process Design and Simulations	p. 56
3.10 Robust Self-Assembly Using Highly Designable Structures and Self-Organizing Systems	p. 57
3.11 Self-Organizing Systems	p. 58
3.12 Mass Integration	p. 58
3.13 Synthesis of Mass Energy Integration Networks for Waste Minimization via In-Plant Modification	p. 59
3.14 Process Design	p. 59
3.15 Pollution Prevention by Reactor Network Synthesis	p. 59
3.16 LSENS	p. 60
3.17 Chemkin	p. 60
3.18 Computer Simulation, Modeling and Control of Environmental Quality	p. 62
3.19 Multiobjective Optimization	p. 62
3.20 Risk Reduction Through Waste Minimizing Process Synthesis	p. 63
3.21 Kintecus	p. 65
3.22 SWAMI	p. 66
3.23 SuperPro Designer	p. 66
3.24 P2-EDGE Software	p. 66
3.25 CWRT Aqueous Stream Pollution Prevention Design Options Tool	p. 68
3.26 OLI Environmental Simulation Program (ESP)	p. 68
3.27 Process Flowsheeting and Control	p. 68
3.28 Environmental Hazard Assessment for Computer-Generated Alternative Syntheses	p. 69
3.29 Process Design for Environmentally and Economically Sustainable Dairy Plant	p. 69
3.30 Life Cycle Analysis (LCA)	p. 69
3.31 Computer Programs	p. 70
3.32 Pollution Prevention by Process Modification Using On-Line Optimization	p. 73
3.33 A Genetic Algorithm for the Automated Generation of Molecules Within Constraints	p. 73
3.34 WMCAPS	p. 73
Part IV. Computer Programs for the Best Raw Materials and Products of Clean Processes
4.1 Cramer's Data and the Birth of Synprops	p. 75
4.2 Physical Properties form Groups	p. 75
4.3 Examples of SYNPROPS Optimization and Substitution	p. 76
4.4 Toxic Ignorance	p. 77
4.5 Toxic Properties from Groups	p. 78
4.6 Rapid Responses	p. 78
4.7 Aerosols Exposed	p. 79
4.8 The Optimizer Program	p. 82
4.9 Computer Aided Molecular Design (CAMD): Designing Better Chemical Products	p. 82
4.10 Reduce Emissions and Operating Costs with Appropriate Glycol Selection	p. 83
4.11 Texaco Chemical Company Plans to Reduce HAP Emissions Through Early Reduction Program by Vent Recovery System	p. 83
4.12 Design of Molecules with Desired Properties by Combinatorial Analysis	p. 83
4.13 Mathematical Background I	p. 84
4.14 Automatic Molecular Design Using Evolutionary Techniques	p. 84
4.15 Algorithmic Generation of Feasible Partitions	p. 85
4.16 Testsmart Project to Promote Faster, Cheaper, More Humane Lab Tests	p. 85
4.17 European Cleaner Technology Research	p. 86
4.18 Cleaner Synthesis	p. 87
4.19 THERM	p. 92
4.20 Design Trade-Offs for Pollution Prevention	p. 92
4.21 Programming Pollution Prevention and Waste Minimization Within a Process Simulation Program	p. 92
4.22 Product and Process Design Tradeoffs for Pollution Prevention	p. 94
4.23 Incorporating Pollution Prevention into U.S. Department of Energy Design Projects	p. 94
4.24 EPA Programs	p. 94
4.25 Searching for the Profit in Pollution Prevention: Case Studies in the Corporate Evaluation of Environmental Opportunities	p. 95
4.26 Chemical Process Simulation, Design, and Economics	p. 95
4.27 Pollution Prevention Using Process Simulation	p. 95
4.28 Process Economics	p. 95
4.29 Pinch Technology	p. 95
4.30 GIS	p. 96
4.31 Health	p. 96
4.32 Scorecard-Pollution Rankings	p. 97
4.33 HAZOP and Process Safety	p. 98
4.34 Safer by Design	p. 98
4.35 Design Theory and Methodology	p. 101
Part V. Pathways to Prevention
5.1 The Grand Partition Function	p. 103
5.2 A Small Part of the Mechanisms from the Department of Chemistry of Leeds University	p. 103
5.3 REACTION: Modeling Complex Reaction Mechanisms	p. 106
5.4 Environmentally Friendly Catalytic Reaction Technology	p. 107
5.5 Enabling Science	p. 107
5.6 Greenhouse Emissions	p. 110
5.7 Software Simulations Lead to Better Assembly Lines	p. 110
5.8 Cumulants	p. 111
5.9 Generating Functions	p. 111
5.10 ORDKIN a Model of Order and Kinetics for the Chemical Potential of Cancer Cells	p. 111
5.11 What Chemical Engineers Can Learn from Mother Nature	p. 114
5.12 Design Synthesis Using Adaptive Search Techniques and Multi-Criteria Decision Analysis	p. 114
5.13 The Path Probability Method	p. 114
5.14 The Method of Steepest Descents	p. 116
5.15 Risk Reduction Engineering Laboratory/ Pollution Prevention Branch Research (RREL/PPBR)	p. 117
5.16 The VHDL Process	p. 118
Conclusions	p. 119
End Notes	p. 121
References	p. 123
Index	p. 167

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