Quantitative assessment and Consequence modeling of deliberately induced Domino effects in Process facilities

Abstract

Process facilities handling hazardous chemicals at elevated temperature and pressure conditions are attractive targets to external attacks. The possibility of an external attack on a critical installation with an intention of triggering escalation of primary events into secondary and tertiary events, thereby increasing the severity of consequences needs to be effectively analyzed. A prominent Petrochemical Industry located in Kerala, India was identified for induced domino effect analysis. In this study, Bayesian network is used to model the development of a domino sequence and to quantitatively determine the occurrence probabilities of domino effect. Moreover, the updating feature of Bayesian networks is used to update probabilities in the light of new evidences. Phast Process hazard analysis software and ALOHA (Areal Locations of Hazardous Atmospheres) software is used for consequence modeling of the security event to obtain the impact zones. Recommendations to manage and reduce the domino effect attractiveness by incorporating inherently safer design concepts and use of appropriate active and passive mitigating barriers are also discussed.