Print Email Facebook Twitter A dynamic stochastic methodology for quantifying HAZMAT storage resilience Title A dynamic stochastic methodology for quantifying HAZMAT storage resilience Author Chen, C. (TU Delft Safety and Security Science) Yang, M. (TU Delft Safety and Security Science) Reniers, G.L.L.M.E. (TU Delft Safety and Security Science; Universiteit Antwerpen; Katholieke Universiteit Leuven) Date 2021 Abstract 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. Subject Dynamic evolutionEscalation effectsHazardous materialStorage resilienceUncertainty To reference this document use: https://doi.org/10.4233/uuid:07cd678b-894b-47b9-b9d5-0e024a77aff1 DOI https://doi.org/10.1016/j.ress.2021.107909 ISSN 0951-8320 Source Reliability Engineering & System Safety, 215 Part of collection Institutional Repository Document type journal article Rights © 2021 C. Chen, M. Yang, G.L.L.M.E. Reniers Files PDF 1_s2.0_S0951832021004269_main.pdf 5.11 MB Close viewer /islandora/object/uuid:07cd678b-894b-47b9-b9d5-0e024a77aff1/datastream/OBJ/view