Journal ArticleDOI
Measuring the Topological Robustness of Transportation Networks to Disaster-Induced Failures: A Percolation Approach
TLDR
A framework that integrates network theory methods into infrastructure network assessment in order to investigate transportation network robustness from a topological perspective is presented.Abstract:
This paper presents a framework that integrates network theory methods into infrastructure network assessment in order to investigate transportation network robustness from a topological pe...read more
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Proceedings ArticleDOI
Random graphs
TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.
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An integrated physical-social analysis of disrupted access to critical facilities and community service-loss tolerance in urban flooding
TL;DR: Integrated spatial analysis result reveals different spatial clusters of vulnerability across the study region and provides important insights regarding the critical infrastructure protection prioritization and hazard mitigation planning.
Journal ArticleDOI
Probabilistic modeling of cascading failure risk in interdependent channel and road networks in urban flooding
TL;DR: The proposed Bayesian network analysis framework integrates network structural properties and empirical flood propagation data to model the spread of flooding and provides a new tool to help decision-makers prioritize infrastructure protection plans and emergency response actions.
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Robust component: a robustness measure that incorporates access to critical facilities under disruptions
TL;DR: The metric robust component and a probabilistic link-removal strategy to assess network robustness through a percolation-based simulation framework and can be generalized into a wide range of scenarios, thus enabling engineers to pinpoint the impact of disastrous disruption on network robusts.
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A network-of-networks percolation analysis of cascading failures in spatially co-located road-sewer infrastructure networks
TL;DR: A network-of-networks analysis framework of interdependent critical infrastructure systems, with a focus on the co-located road-sewer network, provides a holistic approach to analyze the network robustness under different failure scenarios and can be extended to a larger interdependent system.
References
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Journal ArticleDOI
Emergence of Scaling in Random Networks
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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Resilience and Stability of Ecological Systems
TL;DR: The traditional view of natural systems, therefore, might well be less a meaningful reality than a perceptual convenience.
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Networks: An Introduction
TL;DR: This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.
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Error and attack tolerance of complex networks
TL;DR: It is found that scale-free networks, which include the World-Wide Web, the Internet, social networks and cells, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected even by unrealistically high failure rates.
Proceedings ArticleDOI
Random graphs
TL;DR: Some of the major results in random graphs and some of the more challenging open problems are reviewed, including those related to the WWW.