Transcript Document 7852248

MULTIPERIOD DESIGN OF
AZEOTROPIC SEPARATION
SYSTEMS
Kenneth H. Tyner
and
Arthur W. Westerberg
OVERVIEW
•
•
•
•
•
Problem Description
Problem Challenges
Related Research Issues
Solution Approach
Conclusions
PROBLEM DESCRIPTION
B
• Design An Optimal
Separation Plant
• Multiple Feeds
– Flowrate
– Composition
– Operating Time
F1
F3
F2
• Azeotropes
A
Az
C
PROBLEM DESCRIPTION
A
B
C
F
F1
B
Az
F3
F2
A
Az
C
PROBLEM DESCRIPTION
A
B
C
F
F1
B
F3
F2
A
Az
C
PROBLEM DESCRIPTION
FEED 1
FEED 2
FEED 3
PROBLEM DESCRIPTION
FEED 1
FEED 2
FEED 3
PROBLEM DESCRIPTION
FEED 1
FEED 2
FEED 3
PROBLEM DESCRIPTION
FEED 1
FEED 2
FEED 3
PROBLEM DESCRIPTION
FEED 1
FEED 2
FEED 3
PROBLEM CHALLENGES
• Highly Combinatorial
– Separation Pathways
– Process Units
– Task Assignment
• Difficult Subproblems
–
–
–
–
Large Models
Highly Nonlinear
Recycle Streams
Shared Equipment
INITIAL RESEARCH THRUSTS
• Synthesize Designs
• Evaluate Designs
• Optimize / Modify Designs
AZEOTROPIC SYNTHESIS
A
B
C
F
B
Az
F
A
Az
C
AZEOTROPIC SYNTHESIS
A
B
C
F
B
Az
F
A
Az
C
AZEOTROPIC SYNTHESIS
A
B
C
F
B
F
A
Az
C
SIMULATION
S
S
S
Slack
Zero
SIMULATION
Solve / Optimize
Library
Modify
Initialize
REVISED RESEARCH THRUSTS
• Collocation Error Detection
• Scaling
• Solver Design
SIMULATION
Solve / Optimize
Library
Modify
Initialize
SOLUTION APPROACH
• Approximation
– Separation Task
– Column Design and Operation
• Shortcut Costing
• Autonomous Agents
ECONOMICS
Cost = F( Feed, Distillate, Trays, Reflux )
ECONOMICS
Cost = F( Feed, Distillate, Trays, Reflux )
Separation Task
Contribution
ECONOMICS
Cost = F( Feed, Distillate, Trays, Reflux )
Separation Task
Contribution
Column Design and Operation
Contributions
TASK APPROXIMATION
B
• Variables:
– Compositions
– Flowrates
• Relations:
– Mass Balance
– Lever Rule
– Geometric Objects
B
F
D
A
Az
D/F
C
COLUMN APPROXIMATION
• Cost = F(Feed, Distillate, Trays, Reflux)
• Reflux = F(Trays, Feed Location)
COLUMN APPROXIMATION
• Cost = F(Feed, Distillate, Trays, Reflux)
• Reflux = F(Trays)
• Optimal Feed Location = F(Trays)
COLUMN APPROXIMATION
• Gilliland Correlation
– Numerical Difficulties
• Reflux = C1 * exp(-C2 * Trays) + C3
• Opt Feed Loc = C4 * Trays + C5
DATA COLLECTION
8
• Fix Trays and Task
• Find Optimal Reflux
Reflux
6
4
2
0
0
0.2
0.4
0.6
Feed Location
0.8
22
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
20
Reflux
18
16
14
12
10
8
30
35
40
45
50
Trays
55
60
65
Feed Location
DATA COLLECTION
DATA COLLECTION
B
Calculate
Parameters
Store In
Database
A
Az
C
SIMULATION
A
C
B
F
B
Az
F
Database
A
Az
C
SIMULATION
A
C
B
F
B
Az
F
Database
A
Az
C
SIMULATION
S
S
S
Slack
Zero
ASYNCHRONOUS TEAMS
• Independent Software Agents
• Shared Memory
Newton Solver
Gradient Solver
Trial Points
ASYNCHRONOUS TEAMS
• Independent Software Agents
• Shared Memory
Newton Solver
Gradient Solver
Trial Points
ASYNCHRONOUS TEAMS
• Independent Software Agents
• Shared Memory
Newton Solver
Gradient Solver
Trial Points
ASYNCHRONOUS TEAMS
• Independent Software Agents
• Shared Memory
Newton Solver
Gradient Solver
Trial Points
ASYNCHRONOUS TEAMS
• Independent Software Agents
• Shared Memory
• Advantages
– Scalable
– Ease of Creation / Maintenance
– Cooperation
ASYNCHRONOUS TEAMS
• Applications
– Train Scheduling
– Travelling Salesman Problem
– Building Design
ASYNCHRONOUS TEAMS
Approximation
Agents
Database
Problem
Description
Approximation
Data
Design
Agents
Designs
MINLP DESIGN AGENT
• Fixed:
– Separation Pathways
– Intermediate Streams
• Variable:
–
–
–
–
Task Assignment
Number of Columns
Column Dimensions
Operating Policy
MINLP DESIGN AGENT
• Fixed:
– Separation Pathways
– Intermediate Streams
• Variable:
–
–
–
–
Task Assignment
Number of Columns
Column Dimensions
Operating Policy
MINLP DESIGN AGENT
• Fixed:
– Separation Pathways
– Intermediate Streams
• Variable:
–
–
–
–
Task Assignment
Number of Columns
Column Dimensions
Operating Policy
TASK ASSIGNMENT
5
4.5
Diameter
4
3.5
3
2.5
2
1.5
1
0.5
0
20
30
40
Trays
50
60
TASK ASSIGNMENT
$1,100,000.00
$1,000,000.00
$900,000.00
$800,000.00
$700,000.00
$600,000.00
$500,000.00
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2
3
4
5
6
7
PATH SELECTION
• Sequential Selection
• Genetic Algorithm
• Active Constraint
MINLP DESIGN AGENT
• Fixed:
– Separation Pathways
– Intermediate Streams
• Variable:
–
–
–
–
Task Assignment
Number of Columns
Column Dimensions
Operating Policy
ASYNCHRONOUS TEAMS
Approximation
Agents
Database
Problem
Description
Approximation
Data
Design
Agents
Designs
GENERAL BENEFITS
•
•
•
•
Alternative to Hierarchical Design
Persistent Data
Scenario Analysis
Human Agents
MULTIPERIOD DESIGN OF
AZEOTROPIC SEPARATION
SYSTEMS
Kenneth H. Tyner
and
Arthur W. Westerberg