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Operational risk assessment: A case of the Bhopal disaster


Yang, M and Khan, FI and Amyotte, P, Operational risk assessment: A case of the Bhopal disaster, Process Safety and Environmental Protection, 97 pp. 70-79. ISSN 0957-5820 (2015) [Refereed Article]

Copyright Statement

Copyright 2015 The Institution of Chemical Engineers

DOI: doi:10.1016/j.psep.2015.06.001


Accidental releases of hazardous chemicals from process facilities can cause catastrophic consequences. The Bhopal disaster resulting from a combination of inherently unsafe designs and poorly managed operations is a well-known case. Effective risk modeling approaches that provide early warnings are helpful to prevent and control such rare but catastrophic events. Probability estimation of these events is a constant challenge due to the scarcity of directly relevant data. Therefore, precursor-based methods that adopt the Bayesian theorem to update prior judgments on event probabilities using empirical data have been proposed. The updated probabilities are then integrated with consequences of varying severity to produce the risk profile. This paper proposes an operational risk assessment framework, in which a precursor-based Bayesian network approach is used for probability estimation, and loss functions are applied for consequence assessment. The estimated risk profile can be updated continuously given real-time operational data. As process facilities operate, this method integrates a failure-updating mechanism with potential consequences to generate a real-time operational risk profile. The real time risk profile is valuable in activating accident prevention and control strategies. The approach is applied to the Bhopal accident to demonstrate its applicability and effectiveness.

Item Details

Item Type:Refereed Article
Keywords:accident precursor, Bayesian networks, Bhopal disaster, dynamic risk assessment, loss functions, operational risk assessment
Research Division:Engineering
Research Group:Engineering practice and education
Research Field:Risk engineering
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Khan, FI (Professor Faisal Khan)
ID Code:120652
Year Published:2015
Web of Science® Times Cited:40
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-08-30
Last Modified:2017-11-01

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