Green Design, Industrial Ecology, and Sustainability

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Green Design, Industrial Ecology, and
Sustainability

• Urmila Diwekar
• Center for Uncertain Systems Tools for
  Optimization and Management
• (CUSTOM)
• Vishwamitra Research Institute
• Westmont, IL 60559
• urmila_at_vri-custom.org

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Center for Uncertain Systems Tools for
Optimization and Management
CUSTOM
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Algorithms, Methods, and Tools
Energy and Environment
Sustainability and Security NOx
Reduction Renewable Energy Coal Based Power
Plants Nuclear Waste Management Solvent Selection
Recycling
Sustainability Uncertainty Analysis Optimization
Under Uncertainty Fractal Dimension
Approach Multi-objective Optimization AI
Optimization Options Theory
Molecular Design Under Uncertainty Computational
Chemistry
Batch Distillation Design, Optimization,
Optimal Control Synthesis Feasibility
Efficiency

Value of Research Asset Development and
Management of Natural Gas Reserves
Material and Molecular Modeling
Manufacturing, Planning, and Management
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Traditional Process Design Steps
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Greener by Design
Risk, Reliability Safety
Products
Integration and Control
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Single and Multi-objective Optimization Problems
Multi-Objective e.g. Min Cost, Max Safety, Min
Emissions, Max Flexibility Min/Max
Z(Z1,Z2,..,Zp) Zi fi(x) Subject to h(x)
0 g(x) lt 0 x - Decision variables
Single Objective - e.g. Min Cost Min/Max Z Z
f(x) Subject to h(x) 0 g(x) lt 0 x -
Decision variables
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A Simple Multi-objective Linear Example
Max Z1 6x1 x2 Z2 - x1
3x2 subject to 3x1 2x2 ? 12
3x1 6x2 ? 24 x1 ? 3
x1, x2 ? 0
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Weighting Method Max.Y?1Z1?2Z2
Objective Space
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E
Max. Z1 6x1x2
12
Max. Z2-x13x2
10
D
8
6
Z2
4
2
Pareto set
C
0
A
0
5
10
15
20
25
-2
-4
B
Z1
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CANNON Low Temperature Oxidation
ProcessIndustrial Boiler Applications
EMISSION FREE FLUE GAS
Nox, Sox emission O3 slip
DEAERATOR
FLUE GAS
MAKE UP WATER
Vg Vl height1 height2 Diameter1 Diameter2
CONDENSER
ECONOMIZER
Cin_NOx Temp_in
OXIDIZER DUCT
Temp_out
BOILER
Length_oxidizer
Na2SO4 NaNO3 HNO3
SODIUM CARBONATE
OZONE
SCRUBBER
Ratio_O3/NOx Pressure_O3
TO SEWER
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Multi-objective Optimization of an Environmental
Control Process
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Multi-objective Optimization under Uncertainty
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Important Properties of Sampling Techniques

• Independence / Randomness
• Uniformity
• In most applications, the actual relationship
  between successive points in a sample has no
  physical significance, hence, randomness of the
  sample for approximating a uniform distribution
  is not critical (Knuth, 1973).
• Once it is apparent that the uniformity
  properties are critical to the design of sampling
  techniques, constrained or stratified sampling
  becomes appealing (Morgan and Henrion, 1990).

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Wozniakowski-Hammersley
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New Sampling Technique

• Hammersley Sequence Sampling (HSS) based on a
  Quasi-random number generator
• HSS sampling is at least 3 to 100 times faster
  than LHS or MCS.
• HSS is preferred sampling for stochastic modeling
  and/or stochastic optimization.

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Multi-objective Optimization under Uncertainty
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Weighting Method Max.Y?1Z1?2Z2
Objective Space
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E
Max. Z1 6x1x2
12
Max. Z2-x13x2
10
D
8
6
Z2
4
2
Pareto set
C
0
A
0
5
10
15
20
25
-2
-4
B
Z1
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Comparison of the New MINSOOP Algorithm with the
Conventional Method
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SOFC-PEM Hybrid Power Plant
Rating 1472 kW Efficiency 72.6 Capital
Cost 1773 /kW Cost of Electricity 6.35 c/kWh
176F, 25 psi 190 mA/cm2
1750F, 20 psi 75 mA/cm2 70 fuel utilization
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Uncertainties and Trade-off Surface
Stochastic trade-off surface Uncertainties in PEM
and SOFC models
Deterministic trade-off surface
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Greener by Design
Risk, Reliability Safety
Products
Integration and Control
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Acetic Acid Recovery in Continuous Distillation
Process ( )
Case Study I

• HOAc extraction/separation process

Upstream processes
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Case Study I
Challenges of HOAc Extraction Process

• No degree of freedom
• Process instability upon feed variations

(Current extracting solvent)
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Solvent Selection
Solvent Selection
Solvent selection? - Systematic design of clean
o
solvents
Approaches for solvent selection
o
Experiments
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Database Search
Computer-aided molecular design (CAMD)
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Computer-Aided Molecular Design

• CAMD
• Reverse use of group contribution method (GCM)

• Combinatorial optimization problem
• Uncertainties

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Pareto Solutions
5 Normal distribution
o
4 Pareto solutions
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Ethyl acetate (1) Two
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Design
Isopropyl acetate(3)
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Methyl propionate(7)
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Conceptual Framework for Industrial Ecology
Spatial Global National Sector Region Firm
Community Division Industrial Plant Unit
Operation
Sustainability Quality of Life Environmental
Quality Environmental Impact Energy
Reduction Material Reduction Profitability CostPr
oduction Throughput Eco-Efficiency Thermal
Efficiency
Local National Economic Data
Qualitative
Firm, Plant Production Data
Scale of Application
Mass and Energy Balances
Process Simulation and Optimization
Quantitative
Uncertainty Analysis
Thermodynamic Constraints
Physical Constraints
Criteria for Evaluation
Sources of Information
Tools for Analysis
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Sustainability

• Development that meets the needs of the present
  without compromising the ability of the future
  generations to meet their own need
• -- The world commission on environment and
  development

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The Mercury Cycle
Mercury Research Strategy (USEPA)
Consumption of mercury is highly dangerous to
humans

• Long term exposure effects
• Permanent damage to-
• Brain
• Kidney
• Developing fetus

• Short term exposure high levels exposure effects
• Lung damage
• Diarrhea
• Blood pressure increase

Mercury management at various points important
for successful control of mercury pollution

• Consumption of contaminated fish is the biggest
  source of human exposure to mercury
• Fish consumption advisories at many lakes and
  rivers in United States

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Controlling Ecological Impact

• PH Control by Liming
• Reduce methyl mercury formation
• Food-web, Predator pray models
• Reduce bioaccumulation

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Stochastic Model Comparison
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Lake Liming Results
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Sustainable Systems Hypothesis

• Sustainability is a multi-disciplinary concept
• Any type of data or model can be converted to
  some kind of information irrespective of their
  disciplinary origin

• Necessary condition for the system dynamic
  regime to be sustainable, the fisher information
  must be constant

Reference Fath and Cabezas, 2000
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Mercury Bioaccumulation

• Factors affecting
• bioaccumulation
• Mercury chemistry and abundance
• Species-specific effects
• Geochemical influences (water salinity,
  temperature)
• Food uptake

• Manipulation of food-chain regimes to affect the
  food intake thereby affecting mercury
  bioaccumulation
• Use of control theory and information theory to
  derive regime manipulation strategies

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Optimal Control Problem Results
Control variable Nutrient flow rate D
Controlled system shows lower mercury
bioaccumulation
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Summary

• Decision making in process design and industrial
  ecology is a multi-objective problem with
  uncertainties
• A Multi-objective Framework
• provides trade-offs among objectives
• provides environmentally friendly and economical
  designs
• Uncertainties can change decisions and decisions
  significantly
• Sustainability is a multi-disciplinary
• Ecological systems involve time dependent
  uncertainties and time dependent decision making
• Financial literature and optimal control theory
  provides a systematic decision making

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Contributors

• Dr. Yan Fu, Ford Motor Company
• Karthik Subramanayan, GE
• Yogendra Shastri, UIUC

• Financial Support
• National Science Foundation
• Environmental Protection Agencies
• DOE, National Energy Technology Laboratories

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