Accident probability estimation is a common and central step to all quantitative risk assessment methods. Among many techniques available, bow-tie model (BT) is very popular because it represent the accident scenario altogether including causes and consequences. However, it suffers a static structure limiting its application in real-time monitoring and probability updating which are key factors in dynamic risk analysis. The present work is focused on using BT approach in a dynamic environment in which the occurrence probability of accident consequences changes. In this method, on one hand, failure probability of primary events of BT, leading to the top event, are developed using physical reliability models, and constantly revised as physical parameters (e.g., pressure, velocity, dimension, etc) change. And, on the other hand, the failure probability of safety barriers of the BT are periodically updated using Bayes' theorem as new information becomes available over time. Finally, the resulting, updated BT is used to estimate the posterior probability of the consequences which in turn results in an updated risk profile. © 2012 Elsevier Ltd. All rights reserved.

Item Type:	Refereed Article
Keywords:	Bayes' theorem; Bow-tie approach; Dynamic risk analysis; Physical reliability models; Accident probability; Accident scenarios; Bayes' theorem; Bow tie; Dynamic environments; Failure Probability; Occurrence probability; Physical parameters; Models
Research Division:	Engineering
Research Group:	Maritime Engineering
Research Field:	Ocean Engineering
Objective Division:	Energy
Objective Group:	Renewable Energy
Objective Field:	Renewable Energy not elsewhere classified
UTAS Author:	Khan, FI (Professor Faisal Khan)
ID Code:	85055
Year Published:	2012
Web of Science® Times Cited:	128
Deposited By:	NC Maritime Engineering and Hydrodynamics
Deposited On:	2013-06-12
Last Modified:	2017-10-27
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