Assessing the vulnerability of infrastructure networks based on distribution measures

• Published in: Reliability engineering & system safety Vol. 196; p. 106743
• Main Authors: Galvan, Giulio, Agarwal, Jitendra
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01-04-2020; Elsevier BV
• Subjects: Disruption; Disruption scenarios; Infrastructure; Infrastructure systems; Networks; Reliability engineering; Vulnerability analysis; Vulnerability analysis; Networks; Disruption scenarios; Infrastructure systems
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2019.106743

•A distributional metric for infrastructure vulnerability is proposed.•Its effectiveness is illustrated through power, transport and water supply networks.•Uncertainty in the vulnerability assessment of high-order disruption scenarios is quantified.•Vulnerability analysis framework is formalised.
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.