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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
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MULTIPERIOD DESIGN OFAZEOTROPIC SEPARATIONSYSTEMS 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 • Flowrate • Composition • Operating Time • Azeotropes F3 A Az C
F1 F2 PROBLEM DESCRIPTION B A C F B Az F3 A Az C
F1 F2 PROBLEM DESCRIPTION B A C F B F3 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 B A C F B Az F A Az C
AZEOTROPIC SYNTHESIS B A C F B Az F A Az C
AZEOTROPIC SYNTHESIS B A C F B F A Az C
S S S Slack Zero SIMULATION
Solve / Optimize Library Initialize SIMULATION Modify
REVISED RESEARCH THRUSTS • Collocation Error Detection • Scaling • Solver Design
Solve / Optimize Library Initialize SIMULATION Modify
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
F D / F TASK APPROXIMATION B • Variables: • Compositions • Flowrates • Relations: • Mass Balance • Lever Rule • Geometric Objects B D A Az 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)
Numerical Difficulties • Reflux = C1 * exp(-C2 * Trays) + C3 • Opt Feed Loc = C4 * Trays + C5 COLUMN APPROXIMATION • Gilliland Correlation
DATA COLLECTION • Fix Trays and Task • Find Optimal Reflux
Calculate Parameters Store In Database DATA COLLECTION B A Az C
F Database SIMULATION A C B F B Az A Az C
F Database SIMULATION A C B F B Az A Az C
S S S Slack Zero SIMULATION
Newton Solver Gradient Solver Trial Points ASYNCHRONOUS TEAMS • Independent Software Agents • Shared Memory
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 Approximation Data Problem Description Designs Design Agents
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
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 Approximation Data Problem Description Designs Design Agents
GENERAL BENEFITS • Alternative to Hierarchical Design • Persistent Data • Scenario Analysis • Human Agents
MULTIPERIOD DESIGN OFAZEOTROPIC SEPARATIONSYSTEMS Kenneth H. Tyner and Arthur W. Westerberg