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    Robustness Quantification of Transit Infrastructure under Systemic Risks: A Hybrid Network–Analytics Approach for Resilience Planning

    Source: Journal of Transportation Engineering, Part A: Systems:;2022:;Volume ( 148 ):;issue: 010::page 04022089
    Author:
    Rasha Hassan
    ,
    Ahmed Yosri
    ,
    Mohamed Ezzeldin
    ,
    Wael El-Dakhakhni
    DOI: 10.1061/JTEPBS.0000705
    Publisher: ASCE
    Abstract: Disruptions due to either natural or anthropogenic hazards can significantly impact the operation of critical infrastructure networks (e.g., transportation systems) as they may instigate network-level (cascade) systemic risks, thus impacting the overall city resilience. Recent relevant studies demonstrated the need to quantify the resilience of city infrastructure networks following failures of one/some of their main components, considering both topological and operational network measures. Subsequently, focusing on robustness (a key resilience attribute) and on transit (a major critical infrastructure network), the current study develops a related quantification tool employing a hybrid approach that integrates complex network theoretic measures with data analytics, and specifically clustering and genetic algorithms. To demonstrate the practical utility of the developed tool, the robustness of the City of Minneapolis bus transit network is quantified under possible cascade failures represented by node (i.e., bus stop), link (i.e., route segment), and route failure scenarios. The robustness quantification of this transit network is facilitated by analyzing 43 topological and operational measures using a coupled map lattice model integrated with a direction-based passenger flow redistribution model. Absorptive capacity thresholds are subsequently identified under different passenger flow-to-route capacity ratios. Finally, the routes are categorized based on their influences on the network robustness using genetic algorithms coupled with K-means clustering. The developed approach aims at providing a better understanding of transit systems pre- and postdisruptions by identifying key components that control the network robustness and subsequently devising reliable systemic risk management strategies and recovery plans. Such strategies and plans are expected to facilitate city resilience planning through management of cascade failure risks attributed to natural and anthropogenic hazard events.
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      Robustness Quantification of Transit Infrastructure under Systemic Risks: A Hybrid Network–Analytics Approach for Resilience Planning

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    contributor authorRasha Hassan
    contributor authorAhmed Yosri
    contributor authorMohamed Ezzeldin
    contributor authorWael El-Dakhakhni
    date accessioned2022-12-27T20:46:03Z
    date available2022-12-27T20:46:03Z
    date issued2022/10/01
    identifier otherJTEPBS.0000705.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4287955
    description abstractDisruptions due to either natural or anthropogenic hazards can significantly impact the operation of critical infrastructure networks (e.g., transportation systems) as they may instigate network-level (cascade) systemic risks, thus impacting the overall city resilience. Recent relevant studies demonstrated the need to quantify the resilience of city infrastructure networks following failures of one/some of their main components, considering both topological and operational network measures. Subsequently, focusing on robustness (a key resilience attribute) and on transit (a major critical infrastructure network), the current study develops a related quantification tool employing a hybrid approach that integrates complex network theoretic measures with data analytics, and specifically clustering and genetic algorithms. To demonstrate the practical utility of the developed tool, the robustness of the City of Minneapolis bus transit network is quantified under possible cascade failures represented by node (i.e., bus stop), link (i.e., route segment), and route failure scenarios. The robustness quantification of this transit network is facilitated by analyzing 43 topological and operational measures using a coupled map lattice model integrated with a direction-based passenger flow redistribution model. Absorptive capacity thresholds are subsequently identified under different passenger flow-to-route capacity ratios. Finally, the routes are categorized based on their influences on the network robustness using genetic algorithms coupled with K-means clustering. The developed approach aims at providing a better understanding of transit systems pre- and postdisruptions by identifying key components that control the network robustness and subsequently devising reliable systemic risk management strategies and recovery plans. Such strategies and plans are expected to facilitate city resilience planning through management of cascade failure risks attributed to natural and anthropogenic hazard events.
    publisherASCE
    titleRobustness Quantification of Transit Infrastructure under Systemic Risks: A Hybrid Network–Analytics Approach for Resilience Planning
    typeJournal Article
    journal volume148
    journal issue10
    journal titleJournal of Transportation Engineering, Part A: Systems
    identifier doi10.1061/JTEPBS.0000705
    journal fristpage04022089
    journal lastpage04022089_16
    page16
    treeJournal of Transportation Engineering, Part A: Systems:;2022:;Volume ( 148 ):;issue: 010
    contenttypeFulltext
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