Dynamic Disaster Dynamic Disaster SimulationSimulation

Ken SochatsKen SochatsDirector, Center for National PreparednessDirector, Center for National Preparedness

Director, Visual Information Systems CenterDirector, Visual Information Systems CenterDirector, GIS and Visual Analytics, University Director, GIS and Visual Analytics, University

Center for Social and Urban ResearchCenter for Social and Urban Research

University of PittsburghUniversity of Pittsburgh

Dynamic Discrete Disaster Dynamic Discrete Disaster Decision Simulation System (DDecision Simulation System (D44SS22))

Provide a circumstance-independent Provide a circumstance-independent laboratory for testing how the type and laboratory for testing how the type and scale of the event, situational variables scale of the event, situational variables and command decisions affect and command decisions affect responders’ efficiency and effectiveness in responders’ efficiency and effectiveness in dealing with complex and evolving dealing with complex and evolving disasters.disasters.

DD44SS22 Team Team

Department of Industrial EngineeringDepartment of Industrial Engineering Bidanda BopayaBidanda Bopaya Larry Shuman Larry Shuman Shane WuShane Wu Glenn WangGlenn Wang

School of Medicine School of Medicine Carey BalabanCarey Balaban

Center for National PreparednessCenter for National PreparednessVisual Information Systems CenterVisual Information Systems Center

Matt KelleyMatt Kelley Bob ReganBob Regan Ken SochatsKen Sochats

University of PittsburghUniversity of Pittsburgh

DD44SS22

All HazardsAll Hazards

All LocationAll Location

Multi-EventMulti-Event

Collateral/Consequential EffectsCollateral/Consequential Effects

Response IssuesResponse Issues

Pre-ICS (Crisis Phase)Pre-ICS (Crisis Phase)

Command/Control/CommunicationsCommand/Control/Communications

Multi-jurisdictions/EscalationMulti-jurisdictions/Escalation

Training/ExercisesTraining/Exercises

InteroperabilityInteroperability

DD44SS22 Components Components

GIS - ArcGIS 9.2, ESRIGIS - ArcGIS 9.2, ESRI

Simulation – Arena 10, Rockwell Simulation – Arena 10, Rockwell AutomationAutomation

Decision Model – Microsoft Visual Basic Decision Model – Microsoft Visual Basic (.Net), SQL Server (.Net), SQL Server

Control Structure –, Microsoft Visual Basic Control Structure –, Microsoft Visual Basic (.Net)(.Net)

DD44SS22 Architecture Architecture

DD44SS22 Incident Model Incident Model

Event is a Function of:Event is a Function of: Location AttributesLocation Attributes Environmental AttributesEnvironmental Attributes Event TypeEvent Type TimeTime ActionsActions ReactionsReactions

DD44SS22 Process (Non-Linear) Process (Non-Linear)

Define EventDefine Event Type (CBRNE) 15 DHS Type (CBRNE) 15 DHS SiteSite ScopeScope

GeographicGeographic

TemporalTemporal

DD44SS22 Process Process

Extract GeoDatabase InformationExtract GeoDatabase Information VictimsVictims SitesSites AssetsAssets Response AssetsResponse Assets

DD44SS22 Process Process

Simulate EventSimulate Event ResponseResponse

Fire, Police, EMS, HAZMAT, etc.Fire, Police, EMS, HAZMAT, etc. VictimsVictims

ReactionReactionCasualty ClassesCasualty ClassesDeteriorationDeterioration

Event ProgressionEvent Progression EnvironmentEnvironment

Air Plumes and Water FlowAir Plumes and Water Flow

DD44SS22 Process Process

Model Decision MakingModel Decision Making StrategiesStrategies

EvacuationEvacuation

QuarantineQuarantine

Shelter in PlaceShelter in Place DispatchDispatch

AssetsAssets

TimingTiming

ReservesReserves

GIS ComponentsGIS Components

GeographicGeographic Roads, WaterwaysRoads, Waterways TopographyTopography

AssetAsset Fire, Police, EMS, HAZMATFire, Police, EMS, HAZMAT Public & PrivatePublic & Private

EnvironmentalEnvironmental WeatherWeather HydrologyHydrology

Development CaseDevelopment Case

PittsburghPittsburgh TopographyTopography HydrologyHydrology InfrastructureInfrastructure

BridgesBridges

TunnelsTunnels

PittsburghPittsburgh

GIS ModelGIS Model

GIS Model ZoomGIS Model Zoom

Simulation ModelSimulation Model

DD44SS22 Decision Modeling Decision Modeling

Rule BasedRule BasedRules DerivedRules Derived Standards Standards Best PracticesBest Practices PolicyPolicy ProceduresProcedures PlansPlans SMEs (EMT, Police, Fire, HAZMAT, Mil., etc.)SMEs (EMT, Police, Fire, HAZMAT, Mil., etc.)

InferenceInference InductiveInductive DeductiveDeductive

DD44SS22 Decision Model Architecture Decision Model Architecture

Decision RulesDecision Rules

Rule FormatRule Format <Condition1><Condition2>…:<Consequence1><Consequence2>…<Condition1><Condition2>…:<Consequence1><Consequence2>…

{Actor}{Probability}{RuleSet}{Warrant}{Risk}{Actor}{Probability}{RuleSet}{Warrant}{Risk}{ID}{ID}

ExamplesExamples <IncidentType “Chemical Spill”>: <IncidentType “Chemical Spill”>: <Dispatch Fire><Dispatch HazMat> <Dispatch Fire><Dispatch HazMat>

<Dispatch Police><AreaStrategy Evacuate>…{Actor Commander}{P <Dispatch Police><AreaStrategy Evacuate>…{Actor Commander}{P 1.00}{RuleSet EOC} {Warrant NIMS(1.25)}{Risk 1.3 7.4}{27} 1.00}{RuleSet EOC} {Warrant NIMS(1.25)}{Risk 1.3 7.4}{27}

<EventType ?> : <Establish Command Post> {Actor Incident <EventType ?> : <Establish Command Post> {Actor Incident Commander}{P 1.00}{RuleSet Pittsburgh Emergency Plan}{ Warrant Commander}{P 1.00}{RuleSet Pittsburgh Emergency Plan}{ Warrant NFPA 1561 5.1.3}{Risk 4.6}{1} NFPA 1561 5.1.3}{Risk 4.6}{1}

Progress/Issues/ConclusionsProgress/Issues/Conclusions

ValidationValidationIntegrated GISIntegrated GISInteractionInteractionBest Fit TaskingBest Fit TaskingInformation CompletenessInformation CompletenessModel SophisticationModel SophisticationTestbedTestbed JohnstownJohnstown