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On the application of near accident data to risk analysis of major accidents


Khakzad, N and Khan, F and Paltrinieri, N, On the application of near accident data to risk analysis of major accidents, Reliability Engineering and System Safety, 126 pp. 116-125. ISSN 0951-8320 (2014) [Refereed Article]

Copyright Statement

Copyright 2014 Elsevier Ltd. All rights reserved.

DOI: doi:10.1016/j.ress.2014.01.015


Major accidents are low frequency high consequence events which are not well supported by conventional statistical methods due to data scarcity. In the absence or shortage of major accident direct data, the use of partially related data of near accidents - accident precursor data - has drawn much attention. In the present work, a methodology has been proposed based on hierarchical Bayesian analysis and accident precursor data to risk analysis of major accidents. While hierarchical Bayesian analysis facilitates incorporation of generic data into the analysis, the dependency and interaction between accident and near accident data can be encoded via a multinomial likelihood function. We applied the proposed methodology to risk analysis of offshore blowouts and demonstrated its outperformance compared to conventional approaches. © 2014 Elsevier Ltd. All rights reserved.

Item Details

Item Type:Refereed Article
Keywords:hierarchical Bayesian analysis, major accident, multinomial distribution, offshore blowout, precursor data, probabilistic risk analysis
Research Division:Information and Computing Sciences
Research Group:Information systems
Research Field:Decision support and group support systems
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Khan, F (Professor Faisal Khan)
ID Code:119391
Year Published:2014
Web of Science® Times Cited:96
Deposited By:Australian Maritime College
Deposited On:2017-07-31
Last Modified:2018-03-20

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