Introduction Process Integration Water distribution Summary
Visualisation and interaction for design
Professor Eric S Fraga
Department of Chemical EngineeringUCL (University College London)
ECOSSE Retrospective SymposiumEdinburgh
17 April 2009
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Visualisation and interaction for design
c©2009, All rights reserved.
Introduction Process Integration Water distribution Summary
Process design
Process design should be informed by robust optimisation withconfidence in results. But...
complex non-linear, non-convex,discontinuous & noisy models,
combinatorial search space,
small, possibly non-convex, feasibleregions, and
ill- or un-defined objective functionand constraint equations outsidefeasible regions.
600
700
800
900
1000
1100
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1300
1400
1500
0 5 10 15 20 25 30 35
Cos
t (k$
/yr)
Pressure (atm)
Cost versus Pressure
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
The simplest things give me ideas.
Joan Miro
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Visualisation and interaction
Computer based tools for design and optimization areintended for use by non-experts.
Visual representations critical for ease of use.
Interaction can enable engineer to apply own intuition.
Strategy is to combine data analytics, visualisation, androbust (hybrid) optimisation.
Applications in energy, water, carbon capture, sustainability,and control.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Heat-integrated process design
Task:
Identify potentialintegrations for givenconfiguration.
Enable processmodification forbetter integration.
Help engineer identifydesign alternatives.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
To simplify complications is the first essential ofsuccess.
George Earle Buckle
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Visual representation
For a given process configuration, we can display the hot andcold streams visually and support interaction, where
x-axis for position independentduties,
y -axis for temperature, and
hot stream overlapping coldstream indicates heat integration.
Allow user to manipulate process by moving streams (the tailwagging dog approach): streams can be moved horizontally fordifferent integrations and moved vertically or stretchedhorizontally to change underlying unit designs.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
HEN design algorithm
A graphical view ofprocess heat requirementsdefines left and rightend-points for each hotand cold stream in theprocess:
{(xa,i , ya,i)}
{(xb,i , yb,i)}
i = 1, . . . , ns andx , y ∈ Z+.
1 Define list of intervals
I ←ns⋃1
{{xa,i} ∪ {xb,i}}
2 For each interval [Ij , Ij+1]:
1 Generate list of active streams, A.2 Sort A from top to bottom using yb values.3 Generate match for each hot stream
immediately above cold stream in A.4 Generate utility match for all other
streams.
3 Coalesce adjacent similar matches.
4 Design exchanger for each match.
5 Cost all exchangers and utility use.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Demonstration
www ESF, Patel & Rowe (2001). ChERD 79(7):765–776
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Water distribution networks
We wish to design the pipe network for water distribution for agiven configuration with the aim of meeting water demandwith redundancy in the network. A small motivating problem:
7 nodes
8 pipes
1 reservoir
no pumps
Alperovits & Shamir (1977), Water Resource Research 13(6):885-900
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
The design problemGiven
network layout: connectivity, length (Lk), set of discrete pipediameters, pipe cost;
node demands, Dn; and,
minimum head requirements, Hminn .
Determine
diameter of each pipe, dk , chosen from the set of discretediameters;
flow amount and direction, Qk ; and,
head (pressure) at each node, Hn
so as to minimise total network cost.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
The model
min∑
k
∑m
CmLkykm
subject to: ∑k∈In
Qk −∑k∈On
Qk = Dn
∆Hk = Hn∈Ik − Hn∈Ok
∆Hk = w
(Qk
CHW
)βLk
∑m
d−γm ykm
Hn ≥ Hminn + En∑
m
ykm = 1
Indices: k , pipes/connections, n, nodes, and m, pipediameters.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Direct optimization
Solved minlp in gams, using dicopt with the cplex milpsolver and a variety of nlp solvers:
Initial Solution (103 $)
Configuration conopt2 conopt3 minos minos5
None 659 655 444 Fails
All flows = 100 441 441 452 452
Initialization affects success of the nlp solvers.
Consider visual and interactive tool for initialization ofsubsequent mathematical programming method: hybridapproach.
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Introduction Process Integration Water distribution Summary
Simplicity and complexity need each other.
John Maeda
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Discrete optimization
Use of visualization requires mapping from continuous todiscrete space.
Mapping converts MINLP to discreteprogramming model ...
... but equality constraints cannot besatisfied in discrete space.
So we use interval analysis to identifysolutions which are close to feasible indiscrete space.
The discrete model is solved either by the engineer throughinteraction or using an embedded stochastic optimisationprocedure.
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Introduction Process Integration Water distribution Summary
Interval arithmetic
Changes to model given that node heads are now intervals:
∆Hk = Hn∈Ik − Hn∈Ok
Qk =
(∆Hk
w Lk
Cβdγk
) 1β
0 ∈∑k∈In
Qk −∑k∈On
Qk − Dn
where indicates an interval value.
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Introduction Process Integration Water distribution Summary
Demonstration
www ESF & Papageorgiou (2007), Optimization and Its Applications, Springer, 4:311-332.
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Introduction Process Integration Water distribution Summary
Hybrid procedure results
Initial Solution (103 $)
Configuration conopt2 conopt3 minos minos5
None 659 655 444 Fails
All flows = 100 441 441 452 452
Hybrid 419 419 423 419
Behaviour of nlp solvers is more consistent.
The global optimum is found in 3 of the cases.
Solutions obtained are better in all cases.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Hybrid procedure results
Initial Solution (103 $)
Configuration conopt2 conopt3 minos minos5
None 659 655 444 Fails
All flows = 100 441 441 452 452
Hybrid 419 419 423 419
Behaviour of nlp solvers is more consistent.
The global optimum is found in 3 of the cases.
Solutions obtained are better in all cases.
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Summary
To simplify complications is the first essential ofsuccess.
George Earle Buckle
But...
Everything should be made as simple as possible, butnot simpler.
Albert Einstein
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Visualisation and interaction for design
Introduction Process Integration Water distribution Summary
Acknowledgements
The following have contributed to the work presented here:
Dr Lazaros Papageorgiou, UCLMs Rupal Patel, UCL
Dr Glenn Rowe, Dundee
and the ECOSSE group is to blame for my working in thisfield!
http://www.homepages.ucl.ac.uk/~ucecesf/research.html
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Visualisation and interaction for design
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