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Title. A Systems Engineering Approach for identifying the Performance of a City’s Transportation Critical Infrastructure Network: Applying Multi Objective Modeling to Geographical Interdependencies of the Transportation Network. Objective.

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  1. Title A Systems Engineering Approach for identifying the Performance of a City’s Transportation Critical Infrastructure Network: Applying Multi Objective Modeling to Geographical Interdependencies of the Transportation Network

  2. Objective To develop a model based on system engineering methodologies and practices for assessing the transportation critical infrastructure (CI) as a complex system-of-systems with respect to system performance for various types of disconnects encountered by the highway’s network

  3. Model

  4. Requirements • Model shall provide a ranking of the transportation networks’ links and nodes based on defined performance parameters • Model shall be adaptive such that the input states change

  5. Requirements • Model shall help the emergency responders and or City government users in the decision making process for resource allocation

  6. Model Constraints • Transportation Highway Network • Major US City • Steady State Exhibited • Geographical Interdependencies located within ¼ mile of the network

  7. System Output Two sets of outputs: • Preliminary Output • Estimated Cost • Estimated Risk • Estimated Throughput • Final Output • Network Performance

  8. Simulation Flow Diagram Likelihood Input / Variables Assume Steady State

  9. Model Input Type of Disconnect Accident Chemical Multiple Fatality Single Fatality Multiple Injuries Severe Injury Minor Injury Fender Bender Natural Disaster Earthquake Flooding Hurricane Tornado Severe Weather Type of Disconnect (Continued) Terror Explosion Chemical Bio/Hazard Other Special Events Construction School Closings Time of Day Rush Hour AM PM Other Morning Lunch Afternoon Evening Late Night Early Morning Day of Wk Day of Wk Holliday New Years Easter Memorial Day 4th July Labor Day Thanks Giving Christmas

  10. Model Variables Geographical Interdependencies Power Lines Bridges Intersections Rail Lines DC Locations Water Ports Air Ports Coupling Relationship of Impact Power Lines Bridges Intersections Rail Lines DC Locations Water Ports Air Ports

  11. i, j Nodes Links Geo. Inter. TI i, j RR DT TR Graphical Representation DFW TI – TX Instruments; CI 4 & 8 TR – Trinity River; CI 12 DT – Downtown; CI 2 & 5 RR – Railroad; 11

  12. Model Function

  13. Estimate Cost • Accidents • Non fatal injuries • Fatal • Highway Construction • Time Delays • Goods to market • Personal time Stochastic Monte Carlo Simulation

  14. Quantify and Rank Risks • Failure Modes, Effects, and Criticality Analysis (FMECA) • Risk Filtering, Ranking and Management (RFRM) • Quantitative Risk Analysis (QRA) • Fault Tree (FT) • Event Tree (ET) Bayesian Analysis Markov Chain Monte Carlo Simulation

  15. Estimate Throughput • Throughput estimates for: • Nodes • Links Stochastic Queuing Analysis Monte Carlo Simulation

  16. Model Output: Part I • Economic Impact: The estimated Primary Metropolitan Statistical Area economic impact of a disconnect • Risk Factors: The estimated amount of risk at each link and node of the transportation network

  17. Model Output: Part I • Throughput: The amount of vehicles per unit of time passing a defined link or node of the transportation network

  18. Weighted Analysis • Use Weighted Analysis to arrive at a single output metric • Value and Weight for: 1. Cost 2. Risk 3. Throughput

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