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Regional Seismic Damage Assessmentand
Interdependencies of CriticalInfrastructures during Earthquakes
Prof. Carlos E. VenturaUniversity of British Columbia
Workshop on Seismic Hazard and MicrozonationToronto, 13 January 2012
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Seismic Risk Studies in BC
Seismic risk in south-western BC Deals with damage, monetary losses and casualties
Critical Infrastructure Interdependencies Development of technology and tools to better understand the interdependency between critical infrastructure during natural and man-made disasters
Real-time monitoring of infrastructure in BCDevelopment of Internet-based technology for monitoring earthquakes and their effects in BC.
The methodology of each of these projects will be presented briefly.
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PGA / MMI
Select Probability Level
% Damage and $ Loss
Damage Table
Building TypeSeismicHazard
BuildingVulnerability
SeismicRisk
Elements of Seismic Risk
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Prevalent Material Type by Block
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Structural Damage in Vancouver Average MDF (%) by Block for MMI VIII
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Main geological units and the corresponding amplification factors are:
R2 1.0C1 1.5F 1.5C2 2.0O1 2.5
Geological Units in Victoria
These amplification factors are for strong shaking and long-period ground motion.
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Structural Damage in Victoriawith and without Site Amplification
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Monetary Losses
Economic losses estimated based on building use, replacement value and damage
FEMA Facility Dependent monetary loss estimation
18%
62%
20%
13%
70%
17%
8%
48%
44%
0%10%20%30%40%50%60%70%80%90%
100%
% o
f Tot
al L
osse
s
Office Hotel Hospital
Building type
Cost Distribution in Buildings
ContentsNonstructuralStructural
After Prof. E. Miranda
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Non-structural Damage
Average MDF for NSCs on UBC Campus
0
5
10
15
20
25
30
35
VI VII VIII IX X XI XII
Instrumental Intensity
MD
F (%
)
Contents
Displacement
Acceleration
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Building Functionality 10
Instrumental Intensity
Num
ber o
f Bui
ldin
gs
UBC Campus
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Collaborative work in BC to adapt HAZUS Methodology
to CANADA
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Recent collaborative work in BC
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Example of Earthquake Damage Scenarios
Developed by NRCan as part of this Collaborative Work
The following slides were kindly provided by Dr. M. Journeay of NRCan
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Disclaimer:
The results presented here are of verypreliminary nature and should only be usedto better understand the concepts describedin this presentation and to get a general ideaof the comparative impact of various types ofearthquakes that may affect the BC region
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UNDERSTANDING INTERDEPENDENCIES AMONG CRITICAL INFRASTRUCTURES
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System of Systems - interdependencies
Electric
Power Plant Substation
Transmission
FoodDistribution center
Production centerLocal store
Water
PurificationPlantPump Station
Pipe
Oil & Gas
Refinery
Oil Field Compressor Station
CommunicationsPhone
Internet
Mobile
Transportation
Local roadBridge Regional Highway
Emergency Responders
FirefighterParamedic
Hospital
911 E-Comm
Critical EventLocal road
• Many critical infrastructure Networks rely on one another in order to function• In the event of a disaster, Critical Infrastructures can sustain significant
damage which could render them inoperable• Important to identify infrastructure interdependencies in order to mitigate the
effects of a disaster
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How do we do it?
First, there are interdependencies within and in between infrastructures networks
Second, we need to recognize that interdependencies are time dependent and have very complex relationships
Third, we have to recognize that this is a difficult problem to solve because it is highly nonlinear and time dependent
The problem can be made more manageable by linearizing the interdependencies in segments of time, using Seismic Risk Assessment techniques for individual infrastructures and implementing a rational approach to combine the information available to determine the effect of these interdependencies
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I2Sim
I2Sim is a tool that we have developed to determine the consequences of the failure of one or more of the infrastructures
www.i2sim. ca
3ST
2LT
1Urgent
1 steam
distributor_to_Power_House
In1
In2
p_hospital
p_powerhouse
distributorcontroller
Waterstation
UBC_hospital
UBC Substation
currenttime
TIME
Steamstation
Powerhouse
A_ch1
A_ch6
_powertoph
swh
swf12
-C-
External Water2
-C-
External Water
-C-
External Gas
Display
In1
Out
1
Channel 9
In1 Out1Channel 8
In1
Out
1
Channel 7
In1 Out1Channel 6
In1 Out1Channel 5
In1 Out1
Channel 4
In1 Out1Channel 3
In1 Out1Channel 2
In1 Out1Channel 11
In1 Out1Channel 10
In1
Out
1Channel 1
Node 1
Node 4
Node 3
Node 5
Node 2
3ST
2LT
1Urgent
1 steam
distributor_to_Power_House
In1
In2
p_hospital
p_powerhouse
distributorcontroller
Waterstation
UBC_hospital
UBC Substation
currenttime
TIME
Steamstation
Powerhouse
A_ch1
A_ch6
_powertoph
swh
swf12
-C-
External Water2
-C-
External Water
-C-
External Gas
Display
In1
Out
1
Channel 9
In1 Out1Channel 8
In1
Out
1
Channel 7
In1 Out1Channel 6
In1 Out1Channel 5
In1 Out1
Channel 4
In1 Out1Channel 3
In1 Out1Channel 2
In1 Out1Channel 11
In1 Out1Channel 10
In1
Out
1Channel 1
Node 1
Node 4
Node 3
Node 5
Node 2
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Superimposed Layers
34
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Cell’s State
Physical Operability 100% (green)
Effective Operability 50% because of lack of water
Physical Operability 50% (yellow)
Effective Operability 0% because of lack of electricity
Sensory Information 0%
Sensory information 100%
PM01
water
PM03
electricity
35
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i2Sim Model
36
Cell 2
Channel i
+
X
Cell 1
PMRM
Control points
Distributor
Aggregator
Structure + NSCs + Lifelines
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Interdependencies
Can be represented by the following equation:
[T]: Transportation matrix
[X]: Received Goods
[W]: Sent Goods
][]][[ wxT
Power
Water
Roads
xxxxxxxxx
xxxxxxxxx
xxxxxxxxx
p1p2p3
w1w2w3
r1r2r3
Sp1Sp2Sp3
Sw1Sw2Sw3
Sr1Sr2Sr3
p1 = power token value node 1p2 = power token value node 2...w1 = water token value node 1...
Sp1 = power source value node 1Sp2 = power source value node 2...Sw1 = water source value node 1...
y
yyy y
y
y
yy y
x = internal transmission linky = interdependency link
y
y
y y
y yy
p1 p2 p3 r1 r2 r3w1 w2 w3
w1w2w3
r1r2r3
p1
p2p3
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Real-Time Responsiveness
Closed solution much faster than open iterative solutions (e.g., agent-based modelling) by two or three orders of magnitude
As an example, a system of 3,000 cells with 15 inputs/outputs per cell (45,000 state variables) for a 10 hr scenario with ∆t = 5 minutes can be anylized in a few seconds of computer time
Interactive scenario playing is basically instantaneous
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2008011639
Cells Outputs
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50
10
20
30
40
50
60
70
80
90
100
TIME (h)
WA
TE
R (
%)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50
10
20
30
40
50
60
70
80
90
100
TIME (h)
ME
DIC
INE
(%
)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50
50
100
150
TIME (h)
DO
CT
OR
S (
%)
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50
10
20
30
40
50
60
70
80
90
100
TIME (h)
BE
DS
(%
)
Wat
er (%
)D
octo
rs (%
)
Med
icin
es (%
)B
eds
(%)
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No Action (Sim)Alternative
actions
Action A1 (Sim)
Action A2 (Sim)
Real World
Action B1 (Sim)
Action B2 (Sim)
A
B
A, B = decision pointsDecision A- Take Action A2Decision B- Take Action B1Screens at A- Real World- No Action (Sim)- Action A1 (Sim)- Action A2 (Sim)
A
No Action (Sim)
Decision Making Scenario
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UBC Campus Case Study
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UBC Campus Case
Why modeling UBC campus? The UBC campus shares many
attributes of a small city 47000 daily transitory occupants 10000 full time residents own utilities providers
Information
After an earthquake, you will have losses in the services (electricity, water, etc.)What will be the overall functionality of UBC?Where to put the available resources?
42
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Campus Networks: GIS
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Campus Fiber Network
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45Earthquake Damage Assessment
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GIS: Decision Makers Risk Mapping
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Water system
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Global Interdependency of the Hospital
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
VI VII VIII IX X XI
Functio
nality Co
ndition
s
Instrumental Intensity
Global Interdependency between hospitalwater and electricity systems
H interdependencyElectricity to HWater Zone A12Hospital
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www.bcsims.ca
Internet-based tools for:
• Instant notification of levels of ground shaking (main shock and aftershocks)
• Real-time shake maps• Performance of
infrastructure• Emergency response
planning• Real-time maps of damage
distribution• Earthquake warning system
Collaborative effort between BCMOT-UBC-GSC (and BCMOE)
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Remarks
When interdependencies are taken into account, they can help develop more realistic risk reduction programs and emergency response plans.
Methodologies being developed are useful for the identification of regions of high seismic risk and the interdependencies among critical infrastructures
Real-time information tools, such as the BCSIMS project, and simulators, such as I2SIM, are powerful tools that allow the investigation of risk levels and interdependencies among Critical Infrastructure, so that consequences can be minimized.
Improving response to infrastructure failures is a necessary condition for disaster resilience
First priority during disaster situations is, and should be, human survival