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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