Muutke küpsiste eelistusi

E-raamat: Computer Simulated Plant Design for Waste Minimization/Pollution Prevention

(Consultant, Philadelphia, Pennsylvania, USA)
Teised raamatud teemal:
  • Formaat - PDF+DRM
  • Hind: 64,99 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Raamatukogudele
Computer Simulated Plant Design for Waste Minimization/Pollution PreventionSuurem pilt
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

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
Chemical Process Structures and Information Flow
1(1)
Analysis Synthesis & Design of Chemical Processes
1(1)
Strategy and Control of Exhausts
2(3)
Chemical Process Simulation Guide
5(1)
Integrated Design of Reaction and Separation Systems for Waste Minimization
6(1)
A Review of Computer Process Simulation in Industrial Pollution Prevention
7(4)
EPA Inorganic Chemical Industry Notebook Section V
11(1)
Models
11(1)
Process Simulation Seen as Pivotal in Corporate Information Flow
12(1)
Model-Based Environmental Sensitivity Analysis for Designing a Clean Process Plant
13(1)
Pollution Prevention in Design: Site Level Implementation Strategy For DOE
13(1)
Pollution Prevention in Process Development and Design
14(1)
Pollution Prevention
15(1)
Pollution Prevention Research Strategy
16(1)
Pollution Prevention Through Innovative Technologies and Process Design at UCLA's Center for Clean Technology
17(2)
Assessment of Chemical Processes with Regard to Environmental, Health, and Safety Aspects in Early Design Phases
19(1)
Small Plants, Pollution and Poverty: New Evidence from Brazil and Mexico
20(1)
When Pollution Meets the Bottom Line
20(1)
Pollution Prevention as Corporate Entrepreneurship
20(1)
Plantwide Controllability and Flowsheet Structure of Complex Continuous Process Plants
21(1)
Development of COMPAS
21(1)
Computer-Aided Design of Clean Processes
21(2)
Computer-Aided Chemical Process Design for P2
23(1)
LIMN-The Flowsheet Processor
23(1)
Integrated Synthesis and Analysis of Chemical Process Designs Using Heuristics in the Context of Pollution Prevention
23(1)
Model-Based Environmental Sensitivity Analysis for Designing a Clean Process Plant
23(1)
Achievement of Emission Limits Using Physical Insights and Mathematical Modeling
24(1)
Fritjof Capra's Foreword to Upsizing
24(1)
ZERI Theory
24(1)
SRI's Novel Chemical Reactor - PERMIX
25(1)
Process Simulation Widens the Appeal of Batch Chromatography
25(1)
About Pollution Prevention
25(1)
Federal Register/Vo1. 62, No. 120/Monday, June 23, 1997/Notices/33868
26(1)
EPA Environmental Fact Sheet, EPA Releases RCRA Waste Minimization PBT Chemical List
26(1)
ATSDR
27(1)
OSHA Software/Advisors
27(1)
Environmental Monitoring for Public Access and Community Tracking
27(1)
Health: The Scorecard That Hit a Home Run
28(1)
Screening and Testing for Endocrine Disruptors
28(1)
Reducing Risk
28(4)
Risk: A Human Science
32(3)
IPPS
35(2)
Part II. Mathematical Methods
Linear Programming
37(1)
The Simplex Model
37(1)
Quadratic Programming
37(1)
Dynamic Programming
37(1)
Combinatorial Optimization
37(1)
Elements of Graph Theory
37(1)
Organisms and Graphs
38(1)
Trees and Searching
38(1)
Network Algorithms
38(1)
Extremal Problems
38(1)
Traveling Salesman Problem (TSP)-Combinatorial Optimization
38(1)
Optimization Subject to Diophantine Constraints
39(1)
Integer Programming
39(1)
MINLP
39(1)
Clustering Methods
39(1)
Simulated Annealing
39(1)
Tree Annealing
40(1)
Global Optimization Methods
40(1)
Genetic Programming
41(1)
Molecular Phylogeny Studies
42(1)
Adaptive Search Techniques
42(1)
Advanced Mathematical Techniques
42(1)
Scheduling of Processes for Waste Minimization
42(1)
Multisimplex
43(1)
Extremal Optimization (EO)
43(1)
Petri Nets and SYNPROPS
43(1)
Petri Net-Diagraph Models for Automating HAZOP Analysis of Batch Process Plants
43(2)
DuPont CRADA
45(1)
KBDS-(Using Design History to Support Chemical Plant Design)
45(1)
Dependency-Directed Backtracking
45(1)
Best Practice: Interactive Collaborative Environments
46(1)
The Control Kit for O-Matrix
46(1)
The Clean Process Advisory System: Building Pollution Into Design
47(1)
Nuclear Facility Design Considerations That Incorporate WM/P2 Lessons Learned
47(1)
Pollution Prevention Process Simulator
48(1)
Reckoning on Chemical Computers
48(3)
Part III. Computer Programs for Pollution Prevention and/or Waste Minimization
Pollution Prevention Using Chemical Process Simulation
51(1)
Introduction to the Green Design
51(1)
Chemicals and Materials from Renewable Resources
52(1)
Simulation Sciences
52(1)
EPA/NSF Partnership for Environmental Research
53(1)
BDK-Integrated Batch Development
54(1)
Process Synthesis
54(2)
Synphony
56(1)
Process Design and Simulations
56(1)
Robust Self-Assembly Using Highly Designable Structures and Self-Organizing Systems
57(1)
Self-Organizaing Systems
58(1)
Mass Integration
58(1)
Synthesis of Mass Energy Integration Networks for Waste Minimization via In-Plant Modification
59(1)
Process Design
59(1)
Pollution Prevention by Reactor Network Synthesis
59(1)
LSENS
60(1)
Chemkin
60(2)
Computer Simulation, Modeling and Control of Environmental Quality
62(1)
Multiobjective Optimization
62(1)
Risk Reduction Through Waste Minimizing Process Synthesis
63(2)
Kintecus
65(1)
SWAMI
66(1)
SuperPro Designer
66(1)
P2-EDGE Software
66(2)
CWRT Aqueous Stream Pollution Prevention Design Options Tool
68(1)
OLI Environmental Simulation Program (ESP)
68(1)
Process Flowsheeting and Control
68(1)
Environmental Hazard Assessment for Computer-Generated Alternative Syntheses
69(1)
Process Design for Environmentally and Economically Sustainable Dairy Plant
69(1)
Life Cycle Analysis (LCA)
69(1)
Computer Programs
70(3)
Pollution Prevention by Process Modification Using On-Line Optimization
73(1)
A Genetic Algorithm for the Automated Generation of Molecules Within Constraints
73(1)
WMCAPS
73(2)
Part IV. Computer Programs for the Best Raw Materials and Products of Clean Processes
Cramer's Data and the Birth of Synprops
75(1)
Physical Properties from Groups
75(1)
Examples of SYNPROPS Optimization and Substitution
76(1)
Toxic Ignorance
77(1)
Toxic Properties from Groups
78(1)
Rapid Responses
78(1)
Aerosols Exposed
79(3)
The Optimizer Program
82(1)
Computer Aided Molecular Design (CAMD): Designing Better Chemical Products
82(1)
Reduce Emissions and Operating Costs with Appropriate Glycol Selection
83(1)
Texaco Chemical Company Plans to Reduce HAP Emissions Through Early Reduction Program by Vent Recovery System
83(1)
Design of Molecules with Desired Properties by Combinatorial Analysis
83(1)
Mathematical Background I
84(1)
Automatic Molecular Design Using Evolutionary Techniques
84(1)
Algorithmic Generation of Feasible Partitions
85(1)
Testsmart Project to Promote Faster, Cheaper, More Humane Lab Tests
85(1)
European Cleaner Technology Research
86(1)
Cleaner Synthesis
87(5)
THERM
92(1)
Design Trade-Offs for Pollution Prevention
92(1)
Programming Pollution Prevention and Waste Minimization Within a Process Simulation Program
92(2)
Product and Process Design Tradeoffs for Pollution Prevention
94(1)
Incorporating Pollution Prevention into U.S. Department of Energy Design Projects
94(1)
EPA Programs
94(1)
Searching for the Profit in Pollution Prevention: Case Studies in the Corporate Evaluation of Environmental Opportunities
95(1)
Chemical Process Simulation, Design, and Economics
95(1)
Pollution Prevention Using Process Simulation
95(1)
Process Economics
95(1)
Pinch Technology
95(1)
GIS
96(1)
Health
96(1)
Scorecard-Pollution Rankings
97(1)
HAZOP and Process Safety
98(1)
Safer by Design
98(3)
Design Theory and Methodology
101(2)
Part V. Pathways to Prevention
The Grand Partition Function
103(1)
A Small Part of the Mechanisms from the Department of Chemistry of Leeds University
103(3)
Reaction: Modeling Complex Reaction Mechanisms
106(1)
Environmentally Friendly Catalytic Reaction Technology
107(1)
Enabling Science
107(3)
Greenhouse Emissions
110(1)
Software Simulations Lead to Better Assembly Lines
110(1)
Cumulants
111(1)
Generating Functions
111(1)
ORDKIN a Model of Order and Kinetics for the Chemical Potential of Cancer Cells
111(3)
What Chemical Engineers Can Learn from Mother Nature
114(1)
Design Synthesis Using Adaptive Search Techniques & Multi-Criteria Decision Analysis
114(1)
The Path Probability Method
114(2)
The Method of Steepest Descents
116(1)
Risk Reduction Engineering Laboratory/ Pollution Prevention Branch Research (RREL/PPBR)
117(1)
The VHDL Process
118(49)
Conclusions
119(2)
End Notes
121(2)
References
123(10)
List of Figures
Figure 1 Toxicity vs. Log (Reference Concentration)
133(1)
Figure 2 Parallel Control
133(1)
Figure 3 Series Control
133(1)
Figure 4 Feedback Control
133(1)
Figure 5 A Simple Series Circuit
133(1)
Figure 6 The Feeding Mechanism
133(1)
Figure 7 Organisms and Graphs
134(1)
Figure 8 P-graph of Canaan Geneology Made by Papek Program
134(1)
Figure 9 Example and Matrix Representation of Petri Net
134(1)
Figure 10 Petri Nets
134(1)
Figure 11 Ratio of s in Two Transfer Functions
135(1)
Figure 12 The Control Kit
135(1)
Figure 13 The Bode Diagram
135(1)
Figure 14 Conventional and P-graph Representations of a Reactor and a Distillation Column
135(1)
Figure 15 Tree for Accelerated Branch-and-Bound Search for Optimal Process Structure with Integrated in Plant Waste Treatment (Worst Case)
136(1)
Figure 16 Optimally Synthesized Process Integrating In-Plant Treatment
136(1)
Figure 17 Conventional and P-Graph Representations of a Separation Process
136(1)
Figure 18 P-Graph Representation of a Simple Process
136(1)
Figure 19 Representation of Separator: a) conventional, b) Graph
137(1)
Figure 20 Graph Representation of the Operating Units of the Example
137(1)
Figure 21 Maximal Structure of the Example
138(1)
Figure 22 Three Possible Combinations of Operating Units Producing Material A-E for the Example
138(1)
Figure 23 P-Graph where A, B, C, D, E, and F are the Materials and 1, 2, and 3 are the Operating Units
138(1)
Figure 24 P-Graph Representation of a Process Structure Involving Sharp Separation of Mixture ABC into its Three Components
138(1)
Figure 25 Feasible Process Structures for the Example
139(1)
Figure 26 Enumeration Tree for the Basic Branch and Bound Algorithm Which Generates 9991 Subproblems in the Worst Case
139(1)
Figure 27 Enumeration Tree for the Accelerated Branch and Bound Algorithm with Rule a(1) Which Generates 10 Subproblems in the Worst Case
139(1)
Figure 28 Maximal Structure of Synthesis Problem (P3, R3, O3)
140(1)
Figure 29 Maximal Structure of Synthesis Problem (P4, R4, O4)
140(1)
Figure 30 Maximal Structure of the Synthesis Problem of Grossman (1985)
140(1)
Figure 31 Maximal Structures of 3 Synthesis Problems
141(1)
Figure 32 Maximal Structure of the Example for Producing Material A as the Required Product and Producing Material B or C as the Potential Product
142(1)
Figure 33 Solution-Structures of the Example: (a) Without Producing a Potential Product; and (b) Producing Potential Product B in Addition to Required Product A
142(1)
Figure 34 Maximal Structure of the PMM Production Process Without Integrated In-Plant Waste Treatment
142(1)
Figure 35 Maximal Structure of the PMM Production Process with Integrated In-Plant Waste Treatment
142(1)
Figure 36 Structure of the Optimally Synthesized Process Integrating In-Plant Waste Treatment but Without Consideration of Risk
143(1)
Figure 37 Maximal Graph for the Folpet Production with Waste Treatment as an Integral Part of the Process
143(1)
Figure 38 Flowchart for APSCOT (Automatic Process Synthesis with Combinatiorial Technique)
143(1)
Figure 39 Reaction File for a Refinery Study of Hydrocarbons Using Chemkin
144(2)
Figure 40 Influence of Chemical Groups on Physicaland Biological Properties
146(2)
Figure 41 Structural Parameters and Structure to Property Parameter Used in SYNPROPS
148(1)
Figure 42 Properties of Aqueous Solutions
148(1)
Figure 43 SYNPROPS Spreadsheet of Hierarchical Model
149(1)
Figure 44 SYNPROPS Spreadsheet of Linear Model
150(1)
Figure 45 Synthesis and Table from Cleaner Synthesis
151(1)
Figure 46 Thermo Estimations for Molecules in THERM
151(1)
Figure 47 Table of Therm Values for Groups in Therm
152(1)
Figure 48 NASA Format for Thermodynamic Value Used in Chemkin
153(1)
Figure 49 Iteration History for a Run in SYNPROPS
154(1)
Figure 50 SYNGEN
155(1)
Figure 51 Building a Synthesis for an Estrone Skeleton
155(1)
Figure 52 Any Carbon in a Structure Can Have Four General Kinds of Bonds
156(1)
Figure 53 SYNGEN Synthesis of Cortical Steroid
156(1)
Figure 54 Pericyclic Reaction to Join Simple Starting Materials for Quick Assembly of Morphinan Skeleton
156(1)
Figure 55 Sample SYNGEN Output Screen from Another Bondset
156(1)
Figure 56 Second Sample SYNGEN Output Screen
156(1)
Figure 57 The Triangular Lattice
157(1)
Figure 58 Essential Overlap Figures
157(1)
Figure 59 Effect of Considering Larger Basic Figures
157(1)
Figure 60 The Rhombus Approximation
157(1)
Figure 61 The Successive Filling of Rhombus Sites
157(1)
Figure 62 Distribution Numbers for a Plane Triangular Lattice
158(1)
Figure 63 Order and Complexity
158(1)
Figure 64 Order-Disorder, c=2.5
158(1)
Figure 65 Order-Disorder, c=3
159(1)
Figure 66 p/pO for Rhombus
159(1)
Figure 67 u/kT vs. Occupancy
159(1)
Figure 68 Activity vs. Theta
159(1)
Figure 69 F/kT: Bond Figure
159(1)
Figure 70 Probability vs. Theta, c = 2.77
159(1)
Figure 71 Probability vs. Theta, c = 3
160(1)
Figure 72 d vs. Theta
160(1)
Figure 73 d for Rhombus
160(1)
Figure 74 Metastasis/Rhombus
160(1)
Figure 75 A Fault Tree Network
160(1)
Figure 76 Selected Nonlinear Programming Methods
161(1)
Figure 77 Trade-off Between Capital and Operating Cost for a Distillation Column
161(1)
Figure 78 Structure of Process Simulators
162(1)
Figure 79 Acetone-Formamide and Chloroform-Methanol Equilibrium Diagrams Showing Non-Ideal Behavior
162(1)
Figure 80 Tray Malfunctions as a Function of Loading
162(1)
Figure 81 McCabe-Thiele for (a) Minimum Stages and (b) Minimum Reflux
162(1)
Figure 82 Algorithm for Establishing Distillation Column Pressure and Type Condenser
163(1)
Figure 83 P-Graph of the Process Manufacturing Required Product H and Also Yielding Potential Product G and Disposable Material D From Raw Materials A, B, and C
163(1)
Figure 84 Enumeration Tree for the Conventional Branch-and-Bound Algorithm
163(1)
Figure 85 Maximal Structure of Example Generated by Algorithm MSG
163(1)
Figure 86 Maximal Structure of Example
164(1)
Figure 87 Solution-Structure of Example
164(1)
Figure 88 Operating Units of Example
164(1)
Figure 89 Structure of Synphony
165(1)
Figure 90 Cancer Probability or u/kT
165(1)
Figure 91 Cancer Ordkin-Function
165(1)
Figure 92 Order vs. Age for Attractive Forces
166(1)
Figure 93 Order vs. Age
166(1)
Figure 94 Regression of Cancers
166(1)
Index 167


Stan Bumble, Ph.D., has guided research, development, and engineering at DuPont and Dow Corning with computer programs that optimized the best products and properties. He has used computer programs for assisting the U.S. government with the development of their missile program and with the recovery of disaster victims. He has helped (with the assistance of computers) the U.S. Department of Justice and the Environmental Protection Agency at many hazardous sites such as Love Canal.
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
Püsilink: https://www.kriso.ee/db/97814200329702e.html
Märksõnad: