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Dynamic Disaster Simulation

Dynamic Disaster Simulation. Ken Sochats Director, Center for National Preparedness Director, Visual Information Systems Center Director, GIS and Visual Analytics, University Center for Social and Urban Research University of Pittsburgh.

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Dynamic Disaster Simulation

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  1. Dynamic Disaster Simulation Ken Sochats Director, Center for National Preparedness Director, Visual Information Systems Center Director, GIS and Visual Analytics, University Center for Social and Urban Research University of Pittsburgh

  2. Dynamic Discrete Disaster Decision Simulation System (D4S2) • Provide a circumstance-independent laboratory for testing how the type and scale of the event, situational variables and command decisions affect responders’ efficiency and effectiveness in dealing with complex and evolving disasters.

  3. D4S2 Team • Department of Industrial Engineering • Bidanda Bopaya • Larry Shuman • Shane Wu • Glenn Wang • School of Medicine • Carey Balaban • Center for National Preparedness • Visual Information Systems Center • Matt Kelley • Bob Regan • Ken Sochats • University of Pittsburgh

  4. D4S2 • All Hazards • All Location • Multi-Event • Collateral/Consequential Effects

  5. Response Issues • Pre-ICS (Crisis Phase) • Command/Control/Communications • Multi-jurisdictions/Escalation • Training/Exercises • Interoperability

  6. D4S2 Components • GIS - ArcGIS 9.2, ESRI • Simulation – Arena 10, Rockwell Automation • Decision Model – Microsoft Visual Basic (.Net), SQL Server • Control Structure –, Microsoft Visual Basic (.Net)

  7. D4S2 Architecture

  8. D4S2 Incident Model • Event is a Function of: • Location Attributes • Environmental Attributes • Event Type • Time • Actions • Reactions

  9. D4S2 Process (Non-Linear) • Define Event • Type (CBRNE) 15 DHS • Site • Scope • Geographic • Temporal

  10. D4S2 Process • Extract GeoDatabase Information • Victims • Sites • Assets • Response Assets

  11. D4S2 Process • Simulate Event • Response • Fire, Police, EMS, HAZMAT, etc. • Victims • Reaction • Casualty Classes • Deterioration • Event Progression • Environment • Air Plumes and Water Flow

  12. D4S2 Process • Model Decision Making • Strategies • Evacuation • Quarantine • Shelter in Place • Dispatch • Assets • Timing • Reserves

  13. GIS Components • Geographic • Roads, Waterways • Topography • Asset • Fire, Police, EMS, HAZMAT • Public & Private • Environmental • Weather • Hydrology

  14. Development Case • Pittsburgh • Topography • Hydrology • Infrastructure • Bridges • Tunnels

  15. Pittsburgh

  16. GIS Model

  17. GIS Model Zoom

  18. Simulation Model

  19. D4S2 Decision Modeling • Rule Based • Rules Derived • Standards • Best Practices • Policy • Procedures • Plans • SMEs (EMT, Police, Fire, HAZMAT, Mil., etc.) • Inference • Inductive • Deductive

  20. D4S2 Decision Model Architecture

  21. Decision Rules • Rule Format • <Condition1><Condition2>…:<Consequence1><Consequence2>… {Actor}{Probability}{RuleSet}{Warrant}{Risk}{ID} • Examples • <IncidentType “Chemical Spill”>: <Dispatch Fire><Dispatch HazMat> <Dispatch Police><AreaStrategy Evacuate>…{Actor Commander}{P 1.00}{RuleSet EOC} {Warrant NIMS(1.25)}{Risk 1.3 7.4}{27} • <EventType ?> : <Establish Command Post> {Actor Incident Commander}{P 1.00}{RuleSet Pittsburgh Emergency Plan}{ Warrant NFPA 1561 5.1.3}{Risk 4.6}{1}

  22. Progress/Issues/Conclusions • Validation • Integrated GIS • Interaction • Best Fit Tasking • Information Completeness • Model Sophistication • Testbed • Johnstown

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