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Risk Management of Domino Effects Considering Dynamic Consequence Analysis
Author(s) -
Khakzad Nima,
Khan Faisal,
Amyotte Paul,
Cozzani Valerio
Publication year - 2014
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/risa.12158
Subject(s) - domino effect , risk analysis (engineering) , domino , risk assessment , bayesian network , risk management , process (computing) , bayesian probability , computer science , reliability engineering , engineering , computer security , business , biochemistry , chemistry , physics , finance , artificial intelligence , nuclear physics , operating system , catalysis
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.