Modern society is critically dependent on a network of complex systems for almost every social and economic function. While increasing complexity in large-scale engineered systems offer many advantages including high efficiency, performance and robustness, it inadvertently makes them vulnerable to unanticipated perturbations. A disruption affecting even one component may result in large cascading impacts on the entire system due to high interconnectedness. Large direct and indirect impacts across national and international boundaries of natural disasters like Hurricane Katrina, infrastructure failures like the Northeast blackout, epidemics like the H1N1 influenza, terrorist attacks like the 9/11, and social unrests like the Arab Spring are indicative of the vulnerability associated with growing complexity. There is an urgent need for a quantitative framework to understand resilience of complex systems with different system architectures. In this work, a novel framework is developed that integrates graph theory with statistical and modeling techniques for understanding interconnectedness, interdependencies, and resilience of distinct large-scale systems while remaining cognizant of domain specific details. The framework is applied to three diverse complex systems, 1) Critical Infrastructure Sectors (CIS) of the U.S economy, 2) the Kalundborg Industrial Symbiosis (KIS), Denmark and 3) the London metro-rail infrastructure. These three systems are strategically chosen as they represent complex systems of distinct sizes and span different spatial scales.
The framework is utilized for understanding the influence of both network structure level properties and local node and edge level properties on resilience of diverse complex systems. At the national scale, application of this framework on the U.S. economic network reveals that excessive interconnectedness and interdependencies among CIS significantly amplify impacts of targeted disruptions, and negatively influence its resilience. At the regional scale, analysis of KIS reveals that increasing diversity, redundancy, and multifunctionality is imperative for developing resilient and sustainable IS systems. At the urban scale, application of this framework on the London Metro system identifies stations and rail connections that are sources of functional and structural vulnerability, and must be secured for improving resilience. This framework provides a holistic perspective to understand and propose data-driven recommendations to strengthen resilience of large-scale complex engineered systems.
|School:||University of Pittsburgh|
|School Location:||United States -- Pennsylvania|
|Source:||DAI-B 77/05(E), Dissertation Abstracts International|
|Keywords:||Complex systems, Critical infrastructure, Economic system, Graph theory, Network analysis, Resilience|
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