A COMPUTATIONAL FRAMEWORK FOR OPTIMIZATION-BASED INTERDEPENDENT INFRASTRUCTURE ANALYSIS AND VULNERABILITY
Kuc, Matthias P.
Alderson, David L., Jr.
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Civilian communities and military installations operate numerous critical infrastructure systems to deliver services like power, water, mobility, and communications to people and missions. The vulnerability of these systems can be measured by considering the robustness of each infrastructure network on its own or by considering the interdependencies between different networks. Diverse infrastructure network models are available to analyze system vulnerability, yet a standard architecture for linking pre-existing models for interdependent analysis does not exist. We develop a computational framework to generate combined models that link multiple network-flow optimization models together for interdependent analysis. We validate our methods and implementation in the Python programming language with well-studied interdependent energy networks. We further demonstrate the versatility of our methods by developing a new assessment of fictitious energy and transportation networks with models not originally created with interdependencies. Overall, this work develops a standard way to conduct interdependent infrastructure analysis with pre-built models and sets a foundation for future analysis of other interdependencies and systems.
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