CRISP: Type 1: Reductionist and Integrative Approaches to Improve the Resiliency of Multi-Scale Interdependent Critical Infrastructure

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Critical infrastructures are evolving to be more diverse and increasingly connected. The growing complexity creates convoluted dependencies and interdependencies between infrastructures arising from cyber-physical, geographical, supply-and-demand, and human-in-the-loop relationships between different components of the system. Understanding these interactions requires a reductionist and an integrative approach. The reductionist approach focuses on studying the characteristics of four fundamental classes of dependency links, while the integrative approach uses them as building blocks to establish a holistic network framework to capture the interdependencies of the infrastructure systems. This bottom-up methodology provides a systematic way to generate an integrated and multi-scale view of a system of systems, enabling the identification and quantitative characterization of unanticipated interdependencies through feedback loops. The overarching goal of this project is to improve the resiliency of interdependent infrastructures, enabling them to recover from disruptive events and disturbances within an acceptable amount of time and cost.The proposed research will expand the knowledge base of such interdependencies by adopting both reductionist and integration approach to create a bottom-up methodology to provide fundamental principles to understand interdependencies. The project aims to classify and characterize four fundamental classes of dependencies using principles from physical laws, communications theory, supply chain theory, and game and economic theory. In addition, the project will develop automated scalable vertical and horizontal compositional techniques to form a holistic interdependency network model to investigate the fundamental tradeoff between heterogeneous measures, and the tradeoff between pre-event and post-event measures. The analysis of these relationships will lead to an optimal design of a multi-scale resilience mechanism, which will be applied to case study scenarios of Staten Island during Superstorm Sandy and a nuclear power plan accident such as the one that occurred in Fukushima, Japan.