JRC-090505

CI Interdependencies: Real time disaster response capability

CI Interdependencies: Real time disaster response capability

José R. Martí, KD Srivastava, and i2Sim TeamThe University of British Columbia

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Complex Interdependent Systems Group

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University of British ColumbiaUniversity of British Columbia

JIIRP project Sponsored by PS (Public Safety Canada and NSERC)

V2010 Olympics Sponsored by DRDC (Defence Research and Development Canada)

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UBC’s Multidisciplinary TeamUBC’s Multidisciplinary Team

Electrical and Computer Engineering

Civil Engineering

Software Engineering

Computer Science

Business

Geography

Clinical Psychology

Graphics and Multi-Media

12 Researchers

12 Graduate Students

2 Post Doctoral Fellows

2 Research Engineer

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Our Objective and MotivationOur Objective and Motivation

“First priority during disaster situations is, and

should be, human survival”

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Human VulnerabilityHuman Vulnerability

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Panic and BelongingPanic and Belonging

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San Francisco Bay: Earthquake of M6.8or Greater Due Now!San Francisco Bay: Earthquake of M6.8or Greater Due Now!

A major earthquake on the Hayward Fault, in a highly populated section of the San Francisco Bay Area, is due. • The last major earthquake on the Hayward Fault was in

1868, 140 years ago– Research by the U.S. Geological Survey (USGS) indicate the past

five such earthquakes have been 140 years apart on average.

• A Hayward Fault EQ will adversely impact up to 5 Million people

– Damage will likely exceed $1.5 Trillion– Up to 70% of the loss will be sustained in Alameda and Santa Clara

Counties - The majority of that being in Alameda County

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Vancouver’s Juan de Fuca PlateVancouver’s Juan de Fuca Plate

88Source: GSC

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The Big One (M7-9) due this CenturyMedium ones (M6-7) Due NowThe Big One (M7-9) due this CenturyMedium ones (M6-7) Due Now

Juan de Fuca’s plate slid into the continental coast 400-500 years ago

It is due time to slide back

The magnitude is expected to be fairly large (VIII to X), “THE BIG ONE”

Historically, nine moderate to large earthquakes have occurred (Mw = 6-7) within 250 km of Vancouver in the last 130 years

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Human Needs (Maslow)Human Needs (Maslow)

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Disaster Mitigation TimelineDisaster Mitigation Timeline

Normal Alert Emergency Recovery

Months to years Days to weeks Hours to days Days to months

1 Preparation 2 Response 3 Recovery

Physiological

Safety

Love/Belonging

Esteem

Being

1111

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Individual Survival Needs & Critical SectorsIndividual Survival Needs & Critical Sectors

SURVIVAL TOKENS1. Water (suitable for drinking)2. Food (adequate for emergency

situations)3. Body Shelter (breathable air,

clothing, temperature, housing)4. Panic Control (hope, political and

religious leaders, psychologists, media)

5. Personal Communication (whereabouts of loved ones)

6. Individual Preparedness (education)7. Sanitation (waste disposal, washing)8. Medical Care (medicines, physicians,

nurses)9. Civil Order (fire fighters, police, army)

CRITICAL SECTORS (CANADA)1. Energy2. Water3. Food4. Financial5. Communications6. Transport7. Health8. Safety, Order9. Government, Defence10. Manufacturing

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System of SystemsSystem of Systems

Electric

Power PlantSubstation

Transmission

FoodDistribution center

Production centerLocal store

Water

PurificationPlant

Pump Station

Pipe

Oil & Gas

Refinery

Oil Field Compressor Station

Communications

PhoneInternet

Mobile

Transportation

Local roadBridge Regional Highway

Emergency Responders

FirefighterParamedic

Hospital

911 E-Comm

Critical EventLocal road

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ScopeScope

Systems Planning• Time scale of weeks, months

• Statistical models, steady state models, long-dynamics models

• Policy planning

Disaster Response• Time scale of hours, days

• Urgency of saving human lives

• Infrastructures emergency response plans

• Emergency response management (EOC’s)

• Real time models

First Responders• Ground zero actions

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Disaster Response PlansDisaster Response Plans

During normal times, each infrastructure (power grid, telecom system, etc.) knows very well how to respond to problems in its own system: send out repair crews, readjust operation, etc.

Disaster response plans are normally developed assuming the other infrastructures will be available

However, during large-scale disasters, multiple infrastructures are damaged simultaneously and individual response plans are not sufficient

Vital survival tokens need to be delivered very rapidly to prevent panic

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Each Infrastructure is Responsiblefor its Internal OperationEach Infrastructure is Responsiblefor its Internal Operation

Each entity, be it a power network or a hospital, has its own models and internal modes of operation for normal times and for emergency times

Models exist to simulate disaster events, e.g., forest fires, floods, etc.

We can separate disaster modelling from infrastructures operating modes

i2Sim provides an integration environment to optimize the combined actions of the interdependent infrastructures

Solution is very fast for real-time what-if scenarios

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Hospital needs100 MW

200 km3 water

Power Substation100 MW available

out of 200 MW

Water Station needs60 MW Residences need

40 MW50 km3 water

100 MW

0 MW 0 km3

60 MW

30 MW

10 MW0 MW

150 km3

0 km3

30 km3

Resources AllocationResources Allocation

Black bad decision because hospital cannot function without water

Blue good decision to optimize global objective

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Fast Survival ResponseTemporary IslandsFast Survival ResponseTemporary Islands

SUPERNODE EOC

ISLAND II

ISLAND III

ISLAND I

ISLAND'SMAIN NODE EOC

WATER

ROADS

POWER

ISLAND'SMAIN NODE EOC

Sub-NodeWATER

ROADS

POWER

ISLAND'SMAIN NODE EOC

WATER

ROADS

POWER

Sub-Node

Sub-Node

Sub-Node

Sub-Node

Sub-Node

Sub-Node

Sub-Node

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Coordination & Control (C2’)

I2Sim

EOCEmergency Operations Centre

(can be virtual)

Power Agent Water AgentRoads Agent

i2SimChoices in redirecting power?

Change Substation Dispatch

done

Level 2

Thévenin Models

Thé

veni

n

Thé

veni

n

Power Control Centre Roads Control Centre Water Control Centre

Detailed InternalThévenin External

Detailed InternalThévenin External

Detailed InternalThévenin External

Thé

veni

n

IDBi2dB

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Choices in redirecting water?

Choices in alternative roads?

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No Action A (I2Sim)Alternative

actions

Action A1 (I2Sim)

Action A2 (I2Sim)

Real World

Action B1 (I2Sim)

Action B2 (I2Sim)

A

B

A, B = decision pointsDecision A- Take Action A2Decision B- Take Action B1

Screens at A- Real World- No Action A (I2Sim)- Action A1 (I2Sim)- Action A2 (I2Sim)

A

No Action B (I2Sim)

Decision MakingLook-Ahead and Rewind CapabilityDecision MakingLook-Ahead and Rewind Capability

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I2Sim Real Time PlatformI2Sim Real Time Platform

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i2Sim Ontologyi2Sim Ontology

Cells (Production Units)• A hospital cell requires inputs: electricity, water, doctors, medicines,

etc. and produces outputs: patients healed

Channels (Transportation Unit)• The electricity to the hospital is carried by wires, the water is carried by

pipes, the doctors are carried by the transit system

Tokens (Exchange Unit)• Quantities that are the inputs and the outputs of the cells, e.g., water is

a token, a doctor is a token, a phone call is a token

Controls (Distributors, Aggregators)• Interface the physical layer with the decisions making layer, e.g., if

electricity supply is limited, how much should go to the hospital and how much to the water pumping station

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Basic i2Sim ModelBasic i2Sim Model

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HospitalPower Station

Water Station

x1(t) x5(t)x2(t) x3(t)x4(t)

Residential

Cell Cell

x6(t)

Cell

healedpeople

Cell

Aggregator

Distributor

ExternalSource

Reserve

ExternalSource

Channelelectrical

Channelwater

Channelwater

Channelelectrical

x7(t) x8(t)

Request

electricity

Decisions Coordination:

controls distributors and aggregators

according to global system

objectives

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High-Voltage Electric Power

Primary Distribution

Area A

High-Level Water Primary

Distribution

X

XArea B

Area C

High-LevelReservoir

High-VoltageTransmission

EHA

WHA

Low-Voltage Electric Power

Secondary Distribution

Low-Level Water Secondary Distribution

Residences

HospitalXEHA

WHA

X

Sick PeopleElectricity

Water

Healed People

Area A

Regional ScalingRegional Scaling

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Hospitalm = 70%

Power StationOperabilitym = 60%

Water Stationm = 80%

x1(t) x5(t)x2(t) x3(t)

x4(t)

Residential m = 40%

Cell Cell

x6(t)

Cell

Channelelectrical

healedpeople

Cell

x2 (t) = a.x1 (t-Tau)

aggregator

distributor

ExternalSource

Reserve

ExternalSource

Channelelectrical

Channelwater

Channelwater

Channelelectrical

x7(t) x8(t)

x8(t)=m x7(t)

Only power operator needsdetails of power station

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Cell ModelCell Model

Hospital Cell Function

electricity

nurses

doctors

supplies

water short-term beds

long-term beds

mid-term beds

¼Unintended Controls: Damage

Intended Controls: Reinforcement

Backup Electricity

Backup Water

),,,f( 21 nxxxy

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Channel ModelChannel Model

Medicines Channelsupplier hospital

losses

)( )( txatx sendarrive

ikx

ikx

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Internal Details PrivateOnly External Operating Modes NeededInternal Details PrivateOnly External Operating Modes Needed

Detailed or Crude Cell Description

System/I2Sim Interface

Thévenin Equivalent

TE

I2Sim Cell/Channel Model

Seen by disaster response

community

Private (seen by infrastructure

operator)HRT

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Colour Code by DHSColour Code by DHS

HRT-090211 29

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Input (x) Internal (m) Output (y)

Power Water Pumps Water

100% 100% 2 100%

100% 100% 1 50%

50% 100% 2 or 1 50%

0% 100% 2 or 1 0%

100% 50% 2 or 1 50%

100% 0% 2 or 1 0%

0% 0% 2 or 1 0%

Human Readable Table (HRT)Water Pumping StationHuman Readable Table (HRT)Water Pumping Station

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hidden

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Physical Modes and Resource ModesPhysical Modes and Resource Modes

Colors (DHS)

Physical Operability

85-100%

70-84%

45-69%

26-44%

0-25%

PM01 Patients

discharged/ho

ur

Electricity

Water Doctors

y x1 x2 x3

RM01 100% 100% 100% 100%

RM02 50% 70% 50% 40%

RM03 0% 0% 0% 0%

PM02 Patients

discharged/ho

ur

Electricity

Water Doctors

y x1 x2 x3

RM01 60% 70% 40% 60%

RM02 20% 30% 30% 20%

RM03 0% 0% 0% 0%

Effective Operability

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Models GranularityModels Granularity

The HRT’s can be built with fine granularity data or with very coarse data with no numerical problems in the solution

High granularity data rarely available and not really needed for effective emergency response

Choices by operating models are usually limited (e.g., power substation, hospital, etc.)

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Cells StateCells State

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PM01

water

Physical Operability (100%)

Effective Operability (50%)because of lack of water

PM02

electr

Physical Operability (50%)

Effective Operability (0%)because of lack of electricity

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Human FactorsHuman Factors

Can be incorporated the same way as physical damage, i.e., as physical operability reduction

Doctors past their shift time will have slower reactions, as a result, the hospital output will be reduced

Human errors can reduce output and also create accidents

Accidents correspond to damage events

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EventsEvents

An event is an action that changes the operability of cells or channels

Model is independent of what or who produces the event

Damage event degrades operability

Repair event upgrades operability

Decisions change resources allocation at output distributors

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Some MathSome Math

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00.2

0.40.6

0.8

1

0

0.2

0.4

0.6

0.8

10

0.2

0.4

0.6

0.8

1

x1 x2

y1

x1 x2 y1

100% 100% 100%90% 100% 86%50% 100% 63%0% 100% 50%

100% 0% 50%0% 0% 0%

Linearized Thévenin ModelLinearized Thévenin Model

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Transportation/Interdependencies MatrixTransportation/Interdependencies Matrix

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Power

Water

Steam

xxx

xxx

xxx

xxx

xxx

xxx

xxx

xxx

xxx

xp1 = input power at 1xp2 = input power at 2...xw4 = input water at 4

...

yp10 = output power at 10yp11 = output power at 11...yw15 = output water at 15

...

y

y

yy

y

y

yy y

x = internal linky = interdependency link

y

y

y

p1 p2 p3 s7 s8 s9w4 w5 w6

w4

w5

w6

s7

s8

s9

p1

p2

p3

xw4xw5xw6

xp1xp2xp3

xs7xs8xs9

yp10yp11yp12

yw13yw14yw15

ys16ys17ys18

y

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UBC CampusI2Sim Interdependencies MatrixUBC CampusI2Sim Interdependencies Matrix

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Sensitivity AnalysisSensitivity Analysis

The well-known “Sensitivity Network Approach” can be directly applied to the interdependencies matrix

Where h is some parameter in T or W

hhhW

XT

TX 1

WTX

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State MatrixState Matrix

System dynamics can be expressed in state-space form:

Where state matrix A represents the system’s own dynamics and matrix B represents the state transitions forced by the excitation events

Matrices A and B can be directly obtained from the system’s transportation matrix:

)()()( ttt UBXAX

WTX

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PC-Cluster for Large SystemsPC-Cluster for Large Systems

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UBC’s Vancouver campus is a small municipality• 2,000 acres• 50,000 daily

transitory occupants

• 10000 full time residents

• own utilitiesHuman and Physical layers were classified into: 19 types of cells; and 7 types of channels

UBC Campus Test CaseUBC Campus Test Case

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UBC Buildings Structural DamageUBC Buildings Structural Damage

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UBC LifelinesUBC Lifelines

4545

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Power House

Main Substatio

n

Residences

Hospital

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Cells and Channels from Physical MapCells and Channels from Physical Map

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Interdependent Damage AssessmentInterdependent Damage Assessment

Interdependent (new)

Overlaid (classical)

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Damage and CasualtiesDamage and Casualties

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Events:

• Damage by flood

• Change distributor ratio

• Repair asset

• Human error

• Human tiredness

• ...

Multiple Events Simulation FlowMultiple Events Simulation Flow

Event:Earthquake

Damage on cells and channel

Change HRT’s

Event:Repair Cable

Change Elec. Channel

HRT

Event:Traffic Police Arrives

Change Transportation Channel HRT

Event:Inspectors

Clear Building

Change Hospital Cell

HRTEvent:

Change Distributor

Ratio

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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

A_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

PC-Cluster SimulationPC-Cluster Simulation

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TimingsTimings

Closed solution much faster than open iterative solutions (e.g., agent-based modelling) by two or three orders of magnitudeAs an example, 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 a few seconds of computer timeInteractive scenario playing is basically instantaneousAllows for look ahead and rewind for decision making in real time

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SummarySummary

All infrastructures represented

Models based on operability tables (HRT’s)

HRT’s determined by physical damage and resources availability

Decisions determine resources allocation

Real time environment

What if capability

Off-line system design

On-line training

Real-Time disaster event management

JRC-090505

Thank You!

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