Engineering Complex Systems Julio M. Ottino R.R. McCormick School of Engineering

McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Engineering Complex Systems
Julio M. Ottino
R.R. McCormick School of Engineering
and Applied Sciences
Northwestern University
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Collaborators
•
•
•
•
•
•
•
•
Ashley Smart
Ben Severson
Nick Pohlman
Pengfei Chen
Stan Fiedor
Gabe Juarez
Steve Cisar
Steve Meier
• Nitin Jain
• Jim Gilchrist
• Joe McCarthy
•
•
•
•
•
Luis Amaral
Rich Lueptow
D.V. Khakhar
Paul Umbanhowar
Randy Snurr
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
What does Complex Mean?
“Complex”, signifying “composed of parts”,
comes from the French, ca 1650
the adjective meaning of “not easily
analyzed” is first recorded in 1715
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Complex Systems:
Numerous
Examples in….
Biological
Systems
Social
Systems &
Organizations
Physical
& Chemical
systems
www.northwestern.edu/nico/
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Sociology
“From Micromotives to
Macrobehavior”
Thomas Schelling, 1978
Nobel Prize
Economics 2005
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
From back cover of Schelling’s book
• Through familiar and readily grasped examples,
[the writer] demonstrates what happens when
behavior in the aggregate is more than a simple
summation of individual behaviors, how members
of a society tend to be blind to the collective
consequences of their separate decisions, and why
attempts to infer individual intentions from group
phenomena are tricky at best and often downright
impossible.
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Uri Wilensky, [email protected]
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Granular Materials and Suspensions
“dry” (DGS)
air
“wet” (LGS)
liquid
Examples in nature
and technology
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Segregation heap formation S2 systems
In, uniform mixture
Magnified view
Makse et al., Nature (1997)
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Shallow cylinders and long cylinders
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Mixing by avalanching
(1) Geometry
wedges ⇒ wedges
(2) Dynamics
Random mixing within wedges
Model
Model
Experiment
Experiment
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
γ = rate of mixing, χ=γ x total area being mixed
Metcalfe, Ottino, et al. Nature 1995
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Energy in: Vibration
Small brass spheres
Amplitude A frequency f
Umbanhowar, Swinney
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
How particles interact, bottom-up understanding
Contact Forces
Normal Forces
Tangential Forces
α
Spring and Slider
Fn = k nα 3 / 2 − k d vn α
Hertz repulsion
with dissipation
Ft = min ( kt s , µFn )
Linear tangential spring
with maximum
JMOttino 9/06
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
top view
perspective
view
side view
Vibrated granular matter
Umbanhowar, Swinney et al.
1996
JMOttino 9/06
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
S+D system
1mm steel
2mm glass
# steel 3455
#glass particles 432
(volume ratio ~ 1:1)
5cm diameter tumbler
axial length of 6.4mm
(3.2 times diameter
of large particles)
flat endwall condition
angular velocity 0.21rad/s
Pengfei Chen (2006)
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Segregation, Unmixing
f=4
f=6
f=8
Fiedor & Ottino
J. Fluid Mech.
(2005).
DGS
f=4
f=6
f=8
LGS
n=3
n=4
n=5
Poincaré
Sections
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Poincaré
Model
Exp (S-DGS)
Interpenetrating
Continua Model
S.E. Cisar, P.B. Umbanhowar, and J.M. Ottino, 2006
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Long cylinder, band dynamics (LGS)
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Effect of rotation rate - DGS
5 RPM
10 RPM
15 RPM
20 RPM
25 RPM
JMOttino 9/06
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Evolution
granular
matter
time
Fiedor &. Ottino, Phys.
Rev. Lett. (2003).
Fiedor, Umbanhowar &
Ottino, Phys. Rev. E,
(2006).
JMOttino 9/06
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
DGS
LGS
Laws? Logarithmic decay
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Complex system… recognize by…
(1) What is does: Display organization without any
organizing principle being applied, i.e. behavior
emerges
(2) How can be analyzed: Decomposing the system
and analyzing a part does not give a clue as to the
behavior of the whole.
Rich behavior with simple parts
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simple
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
complicated
complex
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
GO
CHESS
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
“More is different”
Philip Anderson
Science, 1972
John von Neumann 1903-1957
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Avalanches…
Per Bak
“How Nature
Works:
The Science of
Self Organized
Criticality”
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Osborne Reynolds
(1842-1912)
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
• Osborne Reynolds “On the dilatancy of media composed
of rigid particles in contact. With experimental
illustrations”. Philosophical Magazine, December 1885.
• Rode Lecture in 1902 (“On an inversion of ideas as to
the structure of the universe”)
“I have in my hand the first experimental model
universe, a soft India rubber bag filled with small shot”.
• “The Sub-Mechanics of the Universe” (Reynolds
1903). “By this research it is shown that there is one,
and only one, conceivable purely mechanical system
capable of accounting for all the physical evidence, as
we know it, in the Universe.”
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
• Mechanical theory of the ether. Universe filled
with rigid grains size: 5.534x10-18 cm, mean
free path 8.612x10-28 cm.
• Planck length (‘quantum of length’) smallest
measurement of length with any meaning:
1.6 x 10-37 cm or about 10-20 times the size of a
proton.
• ….but Reynolds was a teacher of J.J.
Thomson (discoverer of the electron).
…so much for the modernity of far-reaching
analogies…
JMOttino 9/06
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Unmixing,
self-organization
f=4
f=6
f=8
f=4
f=6
f=8
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Questions
• Can we guide systems that want to design
themselves ?
• Is it possible to design elements – built in
interactions – so that systems design
themselves in an “intelligent” manner?
• Given a final picture, can we uncover the
organizing rules?
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Complexity in materials self-assembly
Structures emerge from
basic thermodynamic
principles and forces
among building blocks
(e.g. atoms, molecules,
nanoparticles, and
colloids).
Designer
building blocks
Reference
S.C. Glotzer,
Science, 306,
419 (2004).
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
First Steps…
Packing rigid shapes on a square lattice
An agent-based approach
for modeling
molecular self-organization
Troisi, Wong, and Ratner
Proc. Nat. Acad. 2005
25 rigid shapes, “molecules” consisting of four “atoms”
neutral (red), positive (blue), negative (black).
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Initial definition of
agents and moves
Pick one agent
A shape for the elementary object is
selected. This is rigid and cannot be
+
broken. Examples
−
+
−
Randomly or one at the time
The agent moves
Given an agent to be moved, the energy Em
of each allowed move (m) is computed. The
move is selected following a Metropolis MC
move.
Does the agent need
to be merged?
If there are no moves that lower the energy
(a fact established in the previous step) the
agent is merged with one other agent.
Merge with
another agent
The current agent is merged with a second
agent selected to have the largest interaction
(negative) energy with the first one.
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
An Example
MC
shape:
AB
Monte Carlo
Agent-based
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
James Clerk Maxwell
1831-1897
Insight: From individual trajectories
to distributions
Statistical Mechanics
Adolphe Quetelet
1796-1874
Mécanique Sociale
Ref. Critical Mass,
Philip Ball,
FSG, 2004
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Granular force network
g
P(f)
Force Distribution,
P(f)
Ashley Smart 2006
f /<f>
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Networks: Nodes
•Grains
Nodes
•Genes
•Proteins
•Metabolites
•Neurons
•Persons
•Species
•Organizations
•Cities
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Networks: Nodes & Links
•Grains
Links
Nodes
•Genes
Forces
Cross regulation
•Proteins
Complex participation
•Metabolites
Chemical reaction
•Neurons
Signaling
•Persons
Relationship
•Species
Trophic relation
•Organizations
Supply chains
•Cities
Travel connections
JMOttino 9/06
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Predictions…
Northwest Atlantic fishery
http://www.imma.org/orlando.pdf
JMOttino 9/06
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Harp seals
Food chain
Cod
Crustaceans
Harp seals
Cod
Crustaceans
Sand eels
Haddock
Food tree
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Harp seals
Cod
Crustaceans
Harp seals
The
real
web
Cod
Crustaceans
Sand eels
Haddock
Luis Amaral et al.
Northwestern, 2005
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Structure, Scaling Food Webs
Amaral et al. Phys Rev E 56, 030901(R) (2002)
Phys Rev Lett 88, 228102 (2002)
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Power Grid
Transportation…
Critical Infrastructure
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Snaptshot of the Internet
K. C. Claffy
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Cell Metabolism
Two Prevailing Points of View:
Pathways
Network
reactions
metabolites
or
e.g. Edwards and Palsson, (2000)
e.g. Ma and Zeng (2003)
Biological “assembly line”
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
A “network interpretation” of the cell metabolism
Connect a pair of nodes (metabolites) with a directed edge if
they participate in the same reaction
A+B+C → D+E
A
D
B
E
C
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
An alternative interpretation of the cell metabolism
Bipartite graph (S-graph) consists of metabolite and
reaction nodes
A+B+C → D+E
A
D
1
B
C
E
(1 = Enzyme)
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
How Robust is this Network to Node Failure?
Algorithm for cascading failure
A
D
4
1
I
E
5
B
2
F
J
H
C
3
K
G
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Algorithm for Cascading Failure
Steady State: consumption must be balanced by production
The concentration of a metabolite with outgoing edges and no
incoming edges goes to zero
A
D
4
1
I
E
5
B
2
F
H
C
3
Remove
Reaction 2
J
K
G
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Algorithm for Cascading Failure
(Reverse Direction)
Steady State: consumption must be balanced by production
The concentration of a metabolite with incoming edges but no
outgoing edges goes to infinity
A
D
4
1
I
E
5
B
2
F
H
C
3
Remove
Reaction 4
J
K
G
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Algorithm for Cascading Failure
(Reverse Direction)
Steady State: consumption must be balanced by production
The concentration of a metabolite with incoming edges but no
outgoing edges goes to infinity
A
D
4
1
I
E
5
B
2
F
H
C
3
Remove
Reaction 4
J
K
G
JMOttino 9/06
McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Special Cases
• Feed Metabolites (allowed to deplete)
• Product Metabolites (allowed to accumulate)
• Equilibrium Reactions (coupled “half reaction” nodes)
A+B↔C+D
A
B
C
1
D
⇒
A
B
1F
1R
C
D
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Simple
“Complex”
“Complex”
Simple
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Engineering, Engineer
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
• “… if a situation is complex and poorly
understood, and if the solution is
constrained by limited resources
(knowledge?)….
then you are in the presence of an
engineering problem.
“To be human is to be an engineer”
*Discussion of the Method, Billy Vaughn Koen
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
• “… if a situation is complex and poorly
understood, and if the solution is
constrained by limited resources
(knowledge?)….
then you are in the presence of an
engineering problem.
“To be human is to be an engineer”
*Discussion of the Method, Billy Vaughn Koen
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Complexity and Engineering
Conflict
• The hallmarks of complex systems are adaptation,
self-organization and emergence.
• Engineers engineer. Engineering is about making
things happen, about consistency of design, about
convergence.
• Engineering has typically dealt with complicated
systems as opposed to complex
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Barriers to Inter-Disciplinary Work
• Language, Mindset/Culture, Academic Silos
• Cultural differences, expectations, practices,
community norms
• Epistemological Roots:
– Engineering: engineering method, heuristics (since dawn of
civilization)
– Mathematics: True for all time, deductive (Euclid, Gödel,
Russell …)
– Natural Science: Observation, reductionist, inductive vs
falsifiable (Galileo, Newton, Popper, …)
• Understanding of what constitutes “truth”, proof and
belief for different scientific approaches
From Shail Patel 2006
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Complexity and Engineering
• Benefit by adoption of complex systems tools to standard
toolkit.
Ecological systems, supply chains, and materials selfassembly; new disciplines (e.g. security engineering).
• Expanding modelling and prediction
• Expanding understanding.
• If modelling is defined as “all happens as if...”, we define
understanding as “not being surprised or making sense of
outcomes”.
• What does “solution” mean?
• Choice for engineering is not between designing everything at
the outset and letting systems designing themselves – it is
attacking the most pressing problems facing us today.
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Security Engineering:
Protecting Critical Infrastructure
•
•
•
•
•
•
Natural disasters
Weather
Congestion of facilities
Business failures
Labor disruptions
Terrorist actions
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Evolution of Disciplines
Engineering in no danger of
becoming obsolete
(same not true of branches)
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Large
Fight to
keep in
Crisis of
Control
Size of the
Discipline
Crisis of
leadership
Growth through
coordination
Fight to get in
Small
Growth through
Creativity
Young
Mature
Age of the Discipline
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Core and periphery;
Nature of knowledge
expansions
State of the art of
domain
at time t
“Break-with”
Breakthrough
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Core-periphery balance
Core
Core
Tools unify picture
Pieces only loosely connected by tools
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
How could the Future be like?
The Central Question:
• Anything that should be in the (new)
core that it is missing?
and if so….What types of “new”
problems could be engineering
problems?
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R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
The Tools of Complexity
•
•
•
•
Nonlinear dynamics
Broad-based statistical mechanics
Agent-based models
Network theory
Ref. J.M. Ottino, Complex Systems,
AIChEJ, 49, 292-299 (2003).
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McCormick
R.R. McCormick School of Engineering and Applied Science
Robert R. McCormick School of Engineering and Applied Science
Further Reading (about this seminar)
• J.M. Ottino, Complex Systems, AIChEJ, 49, 292-299 (2003).
• Amaral, L.A.N. and J.M. Ottino, Complex Networks: Completing
the framework for the study of complex systems, European Physics
Journal, 38, 47-162 (2004).
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