A dynamic stochastic methodology for quantifying HAZMAT storage resilience

Chao Chen, Ming Yang*, Genserik Reniers

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)
39 Downloads (Pure)


A disruption to hazardous (flammable, explosive, and toxic) material (HAZMAT) storage plants may trigger escalation effects, resulting in more severe storage performance losses and making the performance restoration more difficult. The disruption, such as an intentional attack, may be difficult to predict and prevent, thus developing a resilient HAZMAT storage plant may be a practical and effective way to deal with these disruptions. This study develops a dynamic stochastic methodology to quantify the resilience of HAZMAT storage plants. In this methodology, resilience evolution scenarios are modeled as a dynamic process that consists of four stages: disruption, escalation, adaption, and restoration stages. The resistant capability in the disruption stage, mitigation capability in the escalation stage, adaption capability in the adaption stage, and restoration capability in the restoration stage are quantified to obtain the HAZMAT storage resilience. The uncertainties in the disruption stage and the mitigation stage are considered, and the dynamic Monte Carlo method is used to simulate possible resilience scenarios and thus quantify the storage resilience. A case study is used to illustrate the developed methodology, and a discussion based on the case study is provided to find out the critical parameters and resilience measures.

Original languageEnglish
Article number107909
JournalReliability Engineering and System Safety
Publication statusPublished - 2021


  • Dynamic evolution
  • Escalation effects
  • Hazardous material
  • Storage resilience
  • Uncertainty


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