Resilience Characterization for Multi-Layer Infrastructure Networks

Mehmet Baran Ulak*, Lalitha Madhavi Konila Sriram, Ayberk Kocatepe, Eren Erman Ozguven, Reza Arghandeh

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
185 Downloads (Pure)

Abstract

Catastrophic weather has significantly battered the U.S. Gulf Coast in recent years and exposed critical deficiencies in the resilience across communities and organizations. These deficiencies compel the devising of strategies to identify critical infrastructure components that require more attention with regard to building resilience. This article presents a holistic approach to assessing urban resilience by studying the coresilience of infrastructure networks. For this purpose, Tallahassee, Florida is used as a case study with a focus on both power and roadway networks and includes real-life disaster data from three extreme weather events that recently hit the study area. This article contributes to the coresilience concept through: 1) ­developing a geographical information system-based information-gathering approach to obtain an integrated infrastructure network and feed the causality models, 2) developing novel coresilience metrics to spatially identify and evaluate the high-risk locations, and 3) presenting a comprehensive case study and application of the developed approaches by using real-life data from three major storms that hit the study area.
Original languageEnglish
Pages (from-to)2-13
Number of pages12
JournalIEEE Intelligent Transportation Systems Magazine
Volume14
Issue number4
DOIs
Publication statusPublished - 18 Mar 2021

Keywords

  • Hurricanes
  • Indexes
  • Measurement
  • Neural networks
  • Resilience
  • Storms
  • Transportation

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