Interdependencies between critical infrastructure systems and processes exacerbate the consequences of initial failure, lead to cascading effects, and compound the propagation of damage. The project enhances the fundamental understanding of interdependent critical infrastructures (ICIs) by providing theoretical guidelines. The framework developed in the project serves as the basis of future computing for a multi-infrastructure modeling, design and simulation platform. This framework interfaces existing software tools for individual infrastructures and enables engineering design and public policy analysis. In addition, the quantitative methodologies developed in this project bridge the disciplines of engineering, computer science, social and economic sciences, and create a new interdisciplinary paradigm that provides a holistic view towards ICI resilience planning and design.
The main focus of this project is to develop a meta-network system framework that captures the physical, cyber and human dependencies within an individual infrastructure and across multiple ICIs and to assess their effects on the outcomes of disastrous events. This theoretical framework considers feedback loops, cascading chains of failures and self-aggravating effects. The identification of network structures or motifs provides insights on the design of resilient ICIs and allows for the quantification of metrics relevant to resilience. The techniques for finding multi-resolution representations of meta-network models provide a system modeling platform that is appropriate not only for designing engineering resilient solutions but also for examining socio-economic policies and communication protocols in the context of organizational behaviors. An event-driven and network-based reliability model provides quantitative metrics such as hitting time and mean time to failure. Control and game theory capture risks and uncertainty and assist in the design of risk-sensitive and robust resilient planning schemes for ICIs.