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Risk Management of Domino Effects Considering Dynamic Consequence Analysis

Authors

  • Nima Khakzad,

    Corresponding author
    1. Safety and Risk Engineering Group, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, NL, Canada
    • Address correspondence to Nima Khakzad, Safety and Risk Engineering Group, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, A1B 3X5, Canada; nkhakzad@gmail.com.

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  • Faisal Khan,

    1. Safety and Risk Engineering Group, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, NL, Canada
    2. AMC, University of Tasmania, Launceston, TAS, Australia
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  • Paul Amyotte,

    1. Department of Process Engineering and Applied Science, Dalhousie University, Halifax, NS, Canada
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  • Valerio Cozzani

    1. LISES - Dipartimento di Ingegneria Civile, Chimica, Ambientale e dei Materiali, Alma Mater Studiorum - Università di Bologna, Bologna, Italy
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Abstract

Domino effects are low-probability high-consequence accidents causing severe damage to humans, process plants, and the environment. Because domino effects affect large areas and are difficult to control, preventive safety measures have been given priority over mitigative measures. As a result, safety distances and safety inventories have been used as preventive safety measures to reduce the escalation probability of domino effects. However, these safety measures are usually designed considering static accident scenarios. In this study, we show that compared to a static worst-case accident analysis, a dynamic consequence analysis provides a more rational approach for risk assessment and management of domino effects. This study also presents the application of Bayesian networks and conflict analysis to risk-based allocation of chemical inventories to minimize the consequences and thus to reduce the escalation probability. It emphasizes the risk management of chemical inventories as an inherent safety measure, particularly in existing process plants where the applicability of other safety measures such as safety distances is limited.

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