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Modeling and Simulation of Critical Infrastructure Interdependencies.
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Modeling and Simulation of Critical Infrastructure Interdependencies • The National Infrastructure Simulation and Analysis Center (NISAC) is joint program at Sandia National Laboratories and Los Alamos National Laboratory, funded and managed by the Department of Homeland Security’s (DHS) Preparedness Directorate. • Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000. H.S. Jason Min, Walter Beyeler, and Theresa Brown Sandia National Laboratories Critical Infrastructures Modeling and Simulation Group
Sandia DHS Infrastructure Protection Programs • National Infrastructure Simulation and Analysis Center (NISAC) • DHS, Information Analysis and Infrastructure Protection • Jon MacLaren, Program Manager • Los Alamos National Lab • Critical Infrastructure Protection Decision Support System (CIP/DSS) • DHS, Science and Technology • Paul Domiche, Program Managers • Los Alamos National Lab and Argonne National Lab
Water Energy Public Agriculture Health Food Transportation Emergency Services Postal & Government Shipping Monuments Defense Industrial Base & Icons Banking Information & & Finance Telecommunications Chemical Industry & Hazardous Shipments Mission Provide fundamentally new modeling and simulation capabilities for the analysis of critical infrastructures, their interdependencies, vulnerabilities, and complexities. These advanced capabilities improve the robustness of our Nation’s critical infrastructures by aiding decision makers in the areas of policy assessment, mitigation planning, education, training, and near real-time assistance to crisis response organizations.
Analysis for Homeland Security • Quantify the potential impacts to Infrastructures for major events • Threats • Natural Disasters • Policy Analyses • Planning Exercises • Prioritization and Prioritization Methodologies • Knowledge Management Systems • Analysis Tools • Infrastructure Disruption Models NISAC provides comprehensive, quantitative analyses of the nation’s infrastructures and their interdependencies against all threats (e.g., natural, accidental and malevolent) in support of homeland security concerns for DHS
Only know what is measured or monitored limited to specific set of conditions Event Lib CFS Census Effects of conditions and limitations on system operation Port Simulators Petroleum System CIP/DSS National CIP/DSS Urban Multiple Viewpoints Realistic Abstract Decreasing detail, computation and development time High-fidelity models -individual infrastructure elements Systems models of aggregate supply - demand dynamics Generic, highly abstracted network models Data on system elements Detailed simulation of changes in conditions or behaviors UIS Suite N-ABLE NSMART R-NAS IEISS Air Model WISE Simulation and identification of vulnerabilities of different network topologies to disruptions and effective mitigation PolyNet
Modeling and analyzing Interdependencies of Critical Infrastructures • Importance - analyzing cascading effects of failure of one infrastructure across other infrastructures • Difficulties - Data acquisition is difficult - Each individual infrastructure is complicated - Infrastructures are evolving - Governing regulations are changing • Methodologies used - System Dynamics - IDEF0 - Decision Support System (Optimization tool)
National Infrastructure Interdependency Model - SD The Critical Infrastructure Protection Decision Support System (CIP/DSS) is a joint project between Argonne, Los Alamos and Sandia National Laboratories, in the Critical Infrastructure Protection Portfolio, of the DHS Science & Technology Directorate
One Particular Model: Power generation system dynamics model
Notation Used in the Study: Li = capacity loss of critical infrastructure i; CIi = total available products/services of critical infrastructure i; αij = satisfaction rate of desired consumption of Product/Service i for demand sector j; Dij = desired consumption of product/service i for demand sector j; Iij = available inventory of product/service i for demand sector j; ERj = economic revenues of demand sector j Rij = relative availability of product/Service i for sector j; LA = labor availability; APij = allocated product/service i for demand sector j; i = p(Power), f(Fuel), g(Natural Gas), w(Drinking Water), c(Communication); j = R(Residential), C(Commercial), I(Industrial), T(Transportation).
Disruption Experiments and results • Scenarios: • Scenario 1: No disruption • Scenario 2: a. A power disruption starts at time 60 hour and ends at time 108 hour. b. 40% (Lp = 0.4 )of power generation capacity is lost at time 60 hour. c. market allocation algorithm of each critical infrastructure determined the allocation of each infrastructure materials/services. • Scenario 3: a. the same conditions with Scenario 2 used. b. the allocation of power is determined by the DSS using simulation based nonlinear optimization algorithm, and allocation of other infrastructure materials/services is determined by the market allocation of each critical infrastructure.
Conclusion • Case Study: Based on the results of experiments, the intervention of market of the critical infrastructure may be necessary in the case of disruptions or damages in order to minimize global economic impact. • Modeling and analyzing interdependencies of infrastructures is important • The framework of the study successfully integrates the existing individual models together with system dynamics, functional models, and decision support system.