1. Simulation of Infrastructure Interdependencies Dynamics for Disaster Response Coordination
UBC – I2C Team
11/22/2018
JRM 07/01/31

2. JIIRP Canada Project
PSEPC (Public Safety and Emergency Preparedness Canada)
NSERC (Natural Sciences and Engineering Research Council of Canada)
11/22/2018
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3. UBC Team
Electrical and Computer Engineering Dr. J. R. Martí (Project Leader) Dr. K. Beznosov Dr. J. Jatskevitch Dr. P. Kruchten Dr. K.D. Srivastava Dr. M. Armstrong Dr. J. Hollman M. DeTao Q. Han L. Liu H. Rahman N. Ozog M. Sotoodeh
Civil Engineering Dr. C. Ventura H. Juarez K. Thibert
Computer Science Dr. K. Booth Dr. R. Pottinger Dr. R. Rosenberg A. Merrit J. Xu
Geography Dr. B. Klinkenberg A. Cervantes
Sauder School of Business Dr. C. Woo K. Monu
Simon Fraser University Dr. L. Bartram C. Jiang
Centre for Teaching and Academic Growth Dr. G. Poole A. Clarkson
11/22/2018
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4. UBC’s Partners British Columbia Transmission Corporation BC Hydro
Telus Corporation
Greater Vancouver Regional District
Vancouver International Airport Authority
11/22/2018
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5. Collaborators
David Grigg (UBC, Infrastructure & Services Planning, Assoc. Director)
Gord Apperley (UBC Utilities, Director)
John Manougian (UBC Hospital, Facilities Manager)
Rick Critchlow (Fire Hall UBC)
Sheena Vivian (BCHydro, Emergency Planning Manager)
Doug Allan (JELC, GVRD, Project Manager)
W.A.S. (Bill) White (PSEPC) (JELC)
Gregg Smith (GVRD, Manager Corporate Services)
Jim Gurney (BCTC, Manager Research and Development)
Allan Galambos (Ministry of Transp.)
Sharlie Huffman (Ministry of Transportation)
Murray Day (JIBC, Director Emergency Management Div.)
Jeff Cornell (JIBC)
David Zajdlik (UBC Health & Safety Committee)
James Whyte (Regional Manager for B.C. PEP)
Maiclaire Bolton (Emergency Management Analyst – Seismic Hazards B.C. PEP)
Kevin Molloy (YVR, Vice President & Chief Information Officer)
Ivan Kusal (Telus, Director Corporate Business)
11/22/2018
JRM 07/01/31

6. Our Mandate
“Develop innovative solutions to mitigate large disaster situations involving multiple infrastructure systems”
11/22/2018
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7. Long-Term Objectives
Develop simulator to capture system behaviour at level needed for coordinated response of multiple infrastructures
Develop database of critical disaster scenarios and decision making strategies (eigencases) to be used for planning, training, and base-case for real-time response
11/22/2018
JRM 07/01/31

8. Achieved
I2Sim real-time simulator for I2C (Infrastructure Interdependencies Coordination)
I2Dam earthquake damage assessment
I2dB relational database for eigencases and simulator data
GIS interlinked to I2dB
UBC Test Case
I2Psy psychological assessment
Decision interdependencies flow
11/22/2018
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9. Infrastructure Networks
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10. Oil grid
11/22/2018
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11. Electricity grid
11/22/2018
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12. Water Grid
11/22/2018
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13. Multi-Layered Networks
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14. Water Supply System
11/22/2018
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15. Cell/Channel Operational ModelW H E E H E W H W E T T
YVR H W
Channel
11/22/2018
Hospitals
Water Reservoirs
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Electrical Substations T
Transportation hubs

16. 11/22/2018
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17. Ontology
From Greek ὄν, genitive ὄντος: of being (part. of εἶναι: to be)
Who are the objects in our world, what do they look like at a given moment and where are they located? (snapshot1)
What do they look like at another moment and where are they are located? (snapshot2)
How and why the objects go from snapshot1 to snapshot2?
11/22/2018
JRM 07/01/31

18. It will answer all our cognitive questions …
Who the objects are
What the objects do (which will change them)
Where are they located
When they do things
How they do things
Why they do them
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19. I2Sim Ontology
Representation should allow multiple dissimilar systems to be solved simultaneously
Representation should capture the information needed for decision making across multiple infrastructures, but only at the detail needed at a given decision making level
Representation should be applicable to any particular infrastructure despite the detail differences among them
Representation should not break down when only limited knowledge is available
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20. Our Objects
Cells: produce something given some inputs (e.g., pressured water given water and electricity)
Channels: carry the resources from the output one cell to the input of another cell (e.g., pressured water from water station to hospital)
Tokens: Resources carried from the output of one cell to the input of another cell (e.g., pressured water)
External Sources: Resources brought into the system from outside the system
Reserves (“Internal Sources”): Resources available at the cell’s location
Aggregators: They add up inputs of the same token
Distributors: They split an output to send it to different receiving cells
Humans: They communicate information, take actions, and make decisions. For example, if electrical substation has 100MW, 70MW will be delivered to the hospital and 30MW to the water station
Events: (e.g., earthquake) They can modify cells/channels parameters and affect their Operability. They can also affect the input from external sources
11/22/2018
JRM 07/01/31

21. Power Station Operability m = 60%
x(output)(t) = m.x(input)(t)
Reserve
x(received)(t) = a.x(sent)(t-Tau)
Cell
Cell
x4(t)
distributor
Hospital m = 70%
Power Station Operability m = 60%
x1(t)
x2(t)
x3(t)
x5(t)
Channel electrical
healed people
aggregator
x6(t)
Channel electrical
External Source
Cell
Channel water
Water Station m = 80%
System
External Source
Channel water
Cell
Residential m = 40%
Channel electrical
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22. Channels Medicines arrive at hospital in 1.5 hours 5% are spoiled
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23. Decisions 100 MW 60 MW 0 MW 0 km3 30 MW 150 km3 0 MW 10 MW 0 km3
Power Substation 100 MW available
100 MW
Hospital needs 100 MW 200 km3 water
60 MW
0 MW
0 km3
30 MW
150 km3
0 MW
10 MW
Water Station needs 50 MW
Residences need 20 MW 50 km3 water
0 km3
30 km3
11/22/2018
JRM 07/01/31

24. The Per-Unit Method to Add Apples and Oranges
You cannot add 3 apples and 2 oranges and get 5 apples or 5 oranges but you can get 5 fruits!
We can add electricity and water at the input of a water pumping station and get pressurized water at the output
The “per-unit” method allows us to combine entities of different nature and different reference levels
Then 1 pu (100%) of water (corresponding to 1,500 m3/hr of capacity of the water pumps) and 1 pu (100%) of electricity (corresponding to 500 kW of power supply) result in a 1 pu (100%) of pressurized water (1,500 m3/hr) at the output of the water pumping station
11/22/2018
JRM 07/01/31

25. Hospital Winter (HRT) 11/22/2018 JRM 07/01/31 Input output xw1 xe1 xs1
xh1
xe2
xs2
doctors
nurses
meds
patients
Long
Short
Emergency
100% 0%
80%
90%
xw1 = water from the powerhouse to the hospital
xh1 = steam for sterilization of the surgery equipment surgery
xe1 = power for the Koerner building
xe2 = power for the Purdy building
xs1 = heating for the Koerner building
xs2 = heating for the Purdy building
11/22/2018
JRM 07/01/31

26. Cell and Channel Functions
Cells are defined by the relationship between their inputs and their outputs:
[x(output)(t)] = [m] [x(input)(t)]
In the most common case, a cell will have inputs from multiple infrastructures and one or more outputs of a given infrastructure. In per-unit quantities if all inputs have rated values of 1 pu then all outputs will also be 1 pu and the cell factor m = 1
Channels are defined by the relationship between a quantity put at the sending end and the quantity that arrives at the receiving end:
x(received)(t) = a.x(sent)(t-Tau)
In the channels the resource received is the same as the resource sent with some possible loss and with a time delay
a = 0.9 means 90% of the tokens are accepted (10% are lost). Tau = 1hr travelling time with light traffic can change to Tau = 3hrs with heavier traffic
11/22/2018
JRM 07/01/31

27. Indices
Operability (“m” factor): If m < 1 means reduced cell or channel performance due to damage in physical infrastructure or reduced human performance assuming all necessary inputs are available. For example a power substation is designed to deliver an output of 200 MW but because of earthquake damage, it is able to deliver only 120 MW has m = 0.6 (notice that increased human performance can result in m > 1)
Resource Availability (“r” factor): Reduced cell output which is not due to reduced cell’s performance but to scarcity of resources. For example r = 0.7 means that due to lacking input or reserve resources the cell will only be able to produce 70% of its capacity assuming full physical/human functionality (m=1)
11/22/2018
JRM 07/01/31

28. Wellness Wellness (“w” factor): Capability of producing output:
w = output_capable/output_rated
Wellness can deteriorate by a reduction in m, a reduction in r, or a reduction in both
11/22/2018
JRM 07/01/31

29. Cells Water Pumping Station m = 1; w = 1 . xn x2 x1 yn y2 y1
[y]=[m] [x]
100% Pressurized Water
100% Electricity
75% Water
Water Pumping Station m = 1; w = 0.25
25% Pressurized Water
35% Electricity
75% Water
Water Pumping Station m = 0.5; w = 0.5
50% Pressurized Water
60% Electricity
(assumes 4 equal pumps)
11/22/2018
JRM 07/01/31

30. Forces of Change
Events (e.g., earthquake) affect cell’s m values and channel’s a and Tau values. They also affect external sources values. Production and flow of tokens is affected. Demand rises, production decreases
Psychological Responses (e.g., panic) affect cell’s m values and channel’s a and Tau values
Human Processes (e.g., bureaucratic red tape) affect cell’s m values and channel’s a and Tau values
Human Decisions affect how many tokens are delivered to one cell or to another cell when resources are limited
11/22/2018
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31. Levels & Networks Overlapping & Links 6 5 3 4 1 2 7 11/22/2018
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32. Linearized Cell Model
Four-region approximation and corresponding table of input/output relationship:
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33. Detailed Cell Models
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34. Simulation Scenario At 10 minutes the water supply goes down by 50%
At 30 minutes the supply of medicine goes down by 50%
At 1 hour 20% more doctors arrive to the hospital
At 2 hours a new supply of medicines arrives
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35. Earthquake Scenario
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36. Earthquake Scenario (cont.)
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37. 11/22/2018
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38. 11/22/2018
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39. States
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40. I2Dam (CEN) I2dB (CEN) HUMAN/VIS (CEN) I2Sim (CEN)
GIS (CEN)
I2Dam (CEN)
I2dB (CEN)
I2See (REM)
scenarios
Update Cell/Channel
analysis
dumps
Node names; pt to Cell Model File;
Cell Model File (CEN) Hospital (private)
HUMAN/VIS (CEN)
I2Sim (CEN)
Linearized Cell Model 1
real time
Interdependencies; sensitivities; thresholds
Linearized Cell Model 2
Flows; scripts
System Model: Dynamical
Data Model: GIS and Relational Database
Linearized Cell Model 3
pick model
System Model: Dynamical
Data Model: GIS and Relational Database
Detailed Cell Model
Channel Model File (CEN) (private)
Roads (REM)
Hospital (REM)
Linearized Chan Model 1
Human Readable Table
(HRT)
Human Readable Table
(HRT)
Linearized Chan Model 2
Internal Chan Model
11/22/2018
JRM 07/01/31

41. Simulation vs Reality
“Before the battle is joined, plans are everything, but once the shooting begins, plans are worthless.” (Dwight D. Eisenhower during WWII)
I2Sim merges together planed scenarios, simulation, and reality in a very fast real-time platform
11/22/2018
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42. Scenario Play Out System design Database of eigenscenarios Training
Real time coordination
11/22/2018
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43. Level 1 Coordination CENTRAL 1 Moderator SCENARIO PLAYOUT (CEN)
Power Agent
Roads Agent
Water Agent
SCENARIO PLAYOUT (CEN)
CC Models
We would like to redirect power. Can it be done?
We would like to redirect water. Can it be done? CC CC
I2Sim
I2dB
GIS
I2Vis
Level 2
Power Control Centre (REM)
Roads Control Centre (REM)
Water Control Centre (REM) CC CC CC
CCD
CCD
CCD
done
11/22/2018
Change Substation A Dispatch
JRM 07/01/31

44. Simulation Threads Decision Level 1
Real World A
Alternative actions
No Action (Sim)
A, B = decision points Decision A - Take Action A2
Decision B - Take Action B1
Action A1 (Sim)
Action A2 (Sim) A B
No Action (Sim)
Screens at A - Real World - No Action (Sim) - Action A1 (Sim) - Action A2 (Sim)
Action B1 (Sim)
Action B2 (Sim)
11/22/2018
JRM 07/01/31

45. Simulation Threads Decision Level 2
Level 1 decisions: A, B, … Level 2 decisions: a, b, … Level 3 decisions: i, ii, …
Level 1 decision
Level 2 decisions A a B
Action a1 (Sim)
Action a2 (Sim)
For Level 2, Level 1decision A has already been taken and Level 2 proceeds from there. The combined results of multiple Level 2 decisions will create a new real-world picture which will prompt Level 1 decision B. Level 2 decisions will be the starting point for Level 3 decisions, etc.
11/22/2018
JRM 07/01/31

46. Level 2 Operators
Level 2 agents are the water network operator, power network operator, etc. They need a detailed view of their network (D) but channels/cells (CC) for the other networks
Level 2 agents use a copy of I2Sim replacing (CC) by (D) for their own network
11/22/2018
JRM 07/01/31

47. Level 2 Coordination Power Control Centre (REM) Power Control Centre
Change Substation A Dispatch
done
Power Control Centre
CCD Model
Cells/Channels Water Model
Cells/Channels Gas Model
Detailed Electric Network Model
11/22/2018
JRM 07/01/31

48. Level 2 Coordination Water Control Centre (REM) Water Control Centre
CCD Model
Cells/Channels Power Model
Cells/Channels Gas Model
Detailed Water Network Model
11/22/2018
JRM 07/01/31

49. Database Sharing (“Small-World Networks”)
CC Models and CC Actions are shared across infrastructures and with higher level moderators
D Models and D actions are kept private to individual infrastructures
CC Models do not reveal internal details of the infrastructures
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50. Vertical Scalability Upwards: Islanding Downwards: Ground Zero
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51. Moderator Regional Central Agent 1, Central Agent 2, etc.
Up Level Islanding
Island 1
Island 2
Island 3
Island 4
200 MW
100 MW
500 G
CENTRAL 1
CENTRAL 2
CENTRAL 3
CENTRAL 4
200 G
50 MW
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52. Jurisdictions
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53. Down Level Ground Zero Moderator Ground Zero Fire Fighters Network
Fire Marshal
Medical Network
Can I have 5 ambulances?
You can have 3
Ambulance
Social Care Network
Police Network
Social Workers
Can I have 10 officers?
Police Chief
You can have 8
11/22/2018
JRM 07/01/31

54. Simulator Solves the System of Systems
Power
Water
Roads x p1 p2 p3 w1 w2 w3 r1 r2 r3
Sp1
Sp2
Sp3
Sw1
Sw2
Sw3
Sr1
Sr2
Sr3 y
y = Interdependencies p1
= power token value node 1 p2
= power token value node 2
... w1
= water token value node 1
Sp1
= power source value node 1
Sp2
= power source value node 2
Sw1
= water source value node 1
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55. UBC Campus Case
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56. Mathematical Analysis
[T] = Dynamic Interdependencies Matrix
Built from cell’s m factors and channel’s (a, tau) factors
Interdependencies Analysis
Sensitivity Analysis
Dynamic Trajectories Analysis
11/22/2018
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57. Real-Time Performance
I2Sim solves a piece-wise linear system between Delta-t steps. This allows for solution speeds 1,000 to 10,000 times faster than standard (non-linear) simulators
E.g., I2Sim can solve a system of 3,000 cells with 15 inputs/outputs per cell (45,000 state variables) for a 10 hr scenario with Delta-t = 5 minutes in less than a second of computer time
Interactive scenario playing is basically instantaneous
Linear speedup in PC-Clusters (e.g., a cluster with 10 processors makes the solution 10 times faster)
11/22/2018
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58. Continued Developments
Integration of visualization and decision support systems
Possible extensions of simulator and support systems to:
City of Vancouver
Vancouver international airport YVR
City of Richmond
Vancouver 2010
Multi-cities coordination GVRD
Multi-layered coordination
11/22/2018
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59. Thank You!
11/22/2018
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