Post on 29-Jun-2015
description
VASAInteractive Computational Steering of Large
Asynchronous Simulation Pipelines for Societal Infrastructure
SUNGAHN KO JIEQIONG ZHAO JING XIA SHEHZAD AFZAL XIAOYU WANGGREG ABRAM NIKLAS ELMQVIST LEN KNE DAVID VAN RIPER KELLY GAITHER
SHAUN KENNEDY WILLIAM TOLONE WILLIAM RIBARSKY DAVID S. EBERT
Society is under threat from many sources…
Power grid
Power plants
Motivating scenario slide:Picture of critical infrastructure
Highways
Supply chains
Simulation slide:Simulation is the answer
DISASTERstrikes…
When
HOW CAN WE PREPARE?
WHEN REAL-WORLD EXERCISES ARE COSTLY AND DANGEROUS
simulationI S T H E A N S W E R
IDEA: pipeline of asynchronous simulations
Weathersimulation
Powergrid model
Road networks
Criticalinfrastructure
System-of-systems:multiple heterogeneous systemscombined into a unified systemgreater than its individual parts
CHALLENGES
C1Monolithic simulation
C2Complex relations
C3Non-
standard data
C4Long exec. times
C5Certainty
+ fidelity
VASAVISUAL ANALYTICS FOR SIMULATION-BASED ACTION
Distributed component-based framework for computational steering of systems-of-systems simulations for societal
infrastructure based on a visual analytics approach
CASUAL EXPERTS:Deep expertise in domain
No expertise insimulation + data science
RESILIENCE + RESPONSE:Understand and trace events
Identify vulnerabilities“What if?” scenarios
COMPLEX SYSTEMS:Supply chain logistics
Public safetyCybersecurity
USERS TASKS DOMAIN
DESIGN GUIDELINES
• Avoids integration of a monolithic design with another • Provides a data exchange format (C1, C3)• Enables parallel execution of distributed models (C4)
G1Simulation services
• Provides approximated results for interactive response• Enables real-time response hiding long execution times
G2Simulation proxies
• Help to simplify configurations for non-experts• Provides a data exchange format (C1, C3)
G3Visual Relations
DESIGN GUIDELINES (2)
• Partial and interruptible computational steering
G4Computational steering
• Uncertainty visualization (C5)• Propagation of errors
G5Visual representations
• Main focus of VASA is mapsG6Spatiotemporal focus
VASA WORKBENCH
Interactive desktop tool fora distributed system
Visual analytics dashboard w/multiple coordinated views
Configure + steer + explore(simulation models)
Control distributedsimulations
using REST API
Simulation proxyprovides real-time response
VASA COMPONENT:WEATHER
MODEL PROXY
NOAA: National Oceanic andAthmospheric Administration
ADCIRC: AdvancedCirculation
Prepares eventdatasets from server
Historic data(Irene, Sandy, etc)
Visualizes hurricane coneover time using slider
Generates inputs todownstream components
VASA COMPONENT:CRITICAL INFRASTRUCTURE
MODEL PROXY
E.g. Electric grids, telecomnetworks, gas distribution
Simplified connectivitygraph of important structures
Vu environmentwith submodels
Example: show impact ofhurricanes on restaurants
VASA COMPONENT:ROUTING
MODEL PROXY
Inputs: barriers and closuresOutputs: new transport routes
Simulation engine:ArcGIS Server
Approximates disabledroutes and facilities
Maintains road networkfor critical infrastructure
Visualizes disabledroutes and facilities
VASA COMPONENT:SUPPLY CHAIN
MODEL PROXY
Discrete event simulation onchain in geolocated facilities
Our models: poultry firm + fast food = farm to restaurant
Accepts externalinputs (weather and roads)
Supply chains dependon business and goods
Supports road closures, powerless stores and flooding (polygons)
Food contaminationalso modeled and visualized
Optimizes distribution and even redistributes
products
EXAMPLE: U.S. HURRICANE SEASON
Hurricane Irene hits NorthCarolina on August 27, 2011
34-knot winds batter the coast; criticalinfrastructure proxy estimates impacted
restaurants
EXAMPLE: U.S. HURRICANE SEASON (2)
Complete power grid simulation is run;a shaded polygon shows actual
power outage
Supply chain simulation runshows that some routes are no
longer completing deliveries
CASE STUDIES + FEEDBACK
Regional FEMA•Unprecedented work•Visual investigation• Instant approximations
• “Whole Community”•Meets missions needs•Enable informed decisions
•Suggestion: real-time weather data
U.S. Coast Guard•Dire need with no current solution
•VASA could drastically change their operations
•Potential interface for emergency response
•Great potential
CONCLUSION
•VASA: Visual Analytics for Simulation-based Action•Systems-of-systems approach•Multiple heterogeneous systems into a unified system
•Case studies•Hurricane impact on societal critical infrastructures• Feedback by FEMA and U.S. Coast Guard
FUTURE WORK
Advanced simulation:Energy infrastructures, transportationnetworks, societal infrastructure
Visual representations:Configurations, proxies, intermediate,and final results from simulations
QUESTIONSWork supported by the U.S Department of Homeland Security’s
VACCINE Center 2009-ST-061-CI0001-06.
We thank our analysts and partners for feedback and advice during the project.
Iconography created by designers from the Noun Project.
Niklas Elmqvistelm@umd.edu
David Ebertebertd@purdue.edu