MULTIPERIOD DESIGN OF AZEOTROPIC SEPARATION SYSTEMS

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MULTIPERIOD DESIGN OF AZEOTROPIC SEPARATION SYSTEMS. Kenneth H. Tyner and Arthur W. Westerberg. OVERVIEW. Problem Description Problem Challenges Related Research Issues Solution Approach Conclusions. F1. F2. PROBLEM DESCRIPTION. B. Design An Optimal Separation Plant Multiple Feeds - PowerPoint PPT Presentation

Transcript of MULTIPERIOD DESIGN OF AZEOTROPIC SEPARATION SYSTEMS

MULTIPERIOD DESIGN OFAZEOTROPIC SEPARATION

SYSTEMS

Kenneth H. Tyner

and

Arthur W. Westerberg

OVERVIEW

• Problem Description

• Problem Challenges

• Related Research Issues

• Solution Approach

• Conclusions

PROBLEM DESCRIPTION

• Design An Optimal Separation Plant

• Multiple Feeds– Flowrate

– Composition

– Operating Time

• Azeotropes

A

B

CAz

F1

F3F2

PROBLEM DESCRIPTION

A

B

CAz

F1

F3F2

F

A

B

C

Az

PROBLEM DESCRIPTION

A

B

CAz

F1

F3F2

F

A

B

C

PROBLEM DESCRIPTIONFEED 1 FEED 3FEED 2

PROBLEM DESCRIPTIONFEED 1 FEED 3FEED 2

PROBLEM DESCRIPTIONFEED 1 FEED 3FEED 2

PROBLEM DESCRIPTIONFEED 1 FEED 3FEED 2

PROBLEM DESCRIPTIONFEED 1 FEED 3FEED 2

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

CAz

F

F

A

B

C

Az

AZEOTROPIC SYNTHESIS

A

B

CAz

F

A

B

C

Az

F

AZEOTROPIC SYNTHESIS

A

B

CAz

F

F

A

B

C

SIMULATION

ZeroSlack

S

S

S

SIMULATION

Solve / Optimize

Initialize

ModifyLibrary

REVISED RESEARCH THRUSTS

• Collocation Error Detection

• Scaling

• Solver Design

SIMULATION

Solve / Optimize

Initialize

ModifyLibrary

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 TaskContribution

ECONOMICS

Cost = F( Feed, Distillate, Trays, Reflux )

Separation TaskContribution

Column Design and OperationContributions

TASK APPROXIMATION

• Variables:– Compositions

– Flowrates

• Relations:– Mass Balance

– Lever Rule

– Geometric Objects

A

B

CAz

F

D / F

D

B

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

• Reflux = C1 * exp(-C2 * Trays) + C3

• Opt Feed Loc = C4 * Trays + C5

– Numerical Difficulties

• Gilliland Correlation

DATA COLLECTION

• Fix Trays and Task• Find Optimal Reflux

0

2

4

6

8

0 0.2 0.4 0.6 0.8

Feed Location

Ref

lux

DATA COLLECTION

8

10

12

14

16

18

20

22

30 35 40 45 50 55 60 65

Trays

Ref

lux

00.050.10.150.20.250.30.350.40.450.5

Fee

d L

ocat

ion

DATA COLLECTION

A

B

CAz

Store InDatabase

CalculateParameters

SIMULATION

F

A

B

C

Az

A

B

CAz

F

Database

SIMULATION

F

A

B

C

Az

A

B

CAz

F

Database

SIMULATION

ZeroSlack

S

S

S

ASYNCHRONOUS TEAMS

• Independent Software Agents

• Shared Memory

Trial Points

Newton Solver Gradient Solver

ASYNCHRONOUS TEAMS

• Independent Software Agents

• Shared Memory

Trial Points

Newton Solver Gradient Solver

ASYNCHRONOUS TEAMS

• Independent Software Agents

• Shared Memory

Trial Points

Newton Solver Gradient Solver

ASYNCHRONOUS TEAMS

• Independent Software Agents

• Shared Memory

Trial Points

Newton Solver Gradient Solver

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

ProblemDescription

ApproximationData

Designs

Database

DesignAgents

ApproximationAgents

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

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

20 30 40 50 60

Trays

Dia

mete

r

TASK ASSIGNMENT

$500,000.00

$600,000.00

$700,000.00

$800,000.00

$900,000.00

$1,000,000.00

$1,100,000.00

1 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

ProblemDescription

ApproximationData

Designs

Database

DesignAgents

ApproximationAgents

GENERAL BENEFITS

• Alternative to Hierarchical Design

• Persistent Data

• Scenario Analysis

• Human Agents

MULTIPERIOD DESIGN OFAZEOTROPIC SEPARATION

SYSTEMS

Kenneth H. Tyner

and

Arthur W. Westerberg