A new methodology is introduced based on Bayesian network both to model domino effect propagation patterns and to estimate the domino effect probability at different levels. The flexible structure and the unique modeling techniques offered by Bayesian network make it possible to analyze domino effects through a probabilistic framework, considering synergistic effects, noisy probabilities, and common cause failures. Further, the uncertainties and the complex interactions among the domino effect components are captured using Bayesian network. The probabilities of events are updated in the light of new information, and the most probable path of the domino effect is determined on the basis of the new data gathered. This study shows how probability updating helps to update the domino effect model either qualitatively or quantitatively. The methodology is applied to a hypothetical example and also to an earlier-studied case study. These examples accentuate the effectiveness of Bayesian network in modeling domino effects in processing facility. © 2012 Society for Risk Analysis.

Item Type:	Refereed Article
Keywords:	Bayesian network; Domino effect; Risk analysis; Common cause failure; Complex interaction; Domino effects; Modeling technique; Probabilistic framework; Processing facilities; Propagation pattern; Synergistic effect; Flexible structures; Probability
Research Division:	Engineering
Research Group:	Maritime engineering
Research Field:	Ocean engineering
Objective Division:	Mineral Resources (Excl. Energy Resources)
Objective Group:	Environmentally sustainable mineral resource activities
Objective Field:	Environmentally sustainable mineral resource activities not elsewhere classified
UTAS Author:	Khan, F (Professor Faisal Khan)
ID Code:	94460
Year Published:	2013
Web of Science® Times Cited:	145
Deposited By:	NC Maritime Engineering and Hydrodynamics
Deposited On:	2014-09-09
Last Modified:	2015-01-27
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