Skip to content

Assessing the Vulnerability of Infrastructure Networks based on distribution measures

Research output: Contribution to journalArticle

Original languageEnglish
Article number106743
Number of pages32
JournalReliability Engineering and System Safety
Early online date11 Nov 2019
DOIs
DateAccepted/In press - 10 Nov 2019
DateE-pub ahead of print (current) - 11 Nov 2019

Abstract

Infrastructure networks enable communities to be resilient by distributing essential services and supporting the relief and recovery actions necessary to bounce back from disruptive events. In order for infrastructures to play
this central role, their own vulnerability needs to be assessed and managed. In this paper, a new distributional metric for vulnerability assessment is presented. Unlike existing methodologies, it aims at producing a
characterisation of infrastructure vulnerability which accounts in full for the variability of the service delivery performance across disruption scenarios. The applications of the metric to theoretical configurations as well as
real infrastructure networks are exemplified. These examples demonstrate that the proposed metric enables transparent and comprehensive information on the vulnerability of infrastructure networks. It is noted that the use
of average values of system performance under different disruption scenarios may lead to unsafe conclusions about the system vulnerability. The proposed approach is also able to quantify the uncertainty in the vulnerability
assessment of high-order scenarios. The paper also shows how the formalisation of the building blocks of vulnerability analysis made here, unifies many of the other methodologies found in the literature.

    Research areas

  • Disruption Scenarios, Infrastructure Systems, Networks, Vulnerability Analysis

Documents

Documents

  • Full-text PDF (author’s accepted manuscript)

    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Elsevier at https://doi.org/10.1016/j.ress.2019.106743 . Please refer to any applicable terms of use of the publisher.

    Accepted author manuscript, 1 MB, PDF document

    Embargo ends: 11/11/20

    Request copy

    Licence: CC BY-NC-ND

DOI

View research connections

Related faculties, schools or groups