A probabilistic quantitative risk assessment model for fire in road tunnels with parameter uncertainty

Meng, Q; Qu, X

A probabilistic quantitative risk assessment model for fire in road tunnels with parameter uncertainty

Meng, Q Qu, X

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Publication Type:: Journal Article
Citation:: International Journal of Reliability and Safety, 2011, 5 (3-4), pp. 285 - 298
Issue Date:: 2011-07-01

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Field	Value	Language
dc.contributor.author	Meng, Q	en_US
dc.contributor.author	Qu, X https://orcid.org/0000-0003-0973-3756	en_US
dc.date.issued	2011-07-01	en_US
dc.identifier.citation	International Journal of Reliability and Safety, 2011, 5 (3-4), pp. 285 - 298	en_US
dc.identifier.issn	1479-389X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/116517
dc.description.abstract	Fire in road tunnels can lead to catastrophic consequences in combination with tunnel safety provision failures, thus necessitating a need for a reliable and robust approach to assess tunnel risks caused by fire. In a quantitative risk assessment (QRA) model for road tunnels, uncertainty is an unavoidable component because input parameters of the model possess different levels of uncertainties which are inappropriate to be formulated by crisp numbers. In this paper, a Monte Carlo sampling-based QRA model is proposed to address parameter uncertainty of a QRA model. The tunnel risks are assessed in terms of percentile-based societal risk as well as expected number of fatalities (ENF) curve, which would facilitate tunnel managers to make decisions. A case study is carried out to demonstrate the approach. © 2011 Inderscience Enterprises Ltd.	en_US
dc.relation.ispartof	International Journal of Reliability and Safety	en_US
dc.relation.isbasedon	10.1504/IJRS.2011.041181	en_US
dc.title	A probabilistic quantitative risk assessment model for fire in road tunnels with parameter uncertainty	en_US
dc.type	Journal Article
utslib.citation.volume	3-4	en_US
utslib.citation.volume	5	en_US
utslib.for	090507 Transport Engineering	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
utslib.copyright.status	closed_access
pubs.issue	3-4	en_US
pubs.publication-status	Published	en_US
pubs.volume	5	en_US

Abstract:

Fire in road tunnels can lead to catastrophic consequences in combination with tunnel safety provision failures, thus necessitating a need for a reliable and robust approach to assess tunnel risks caused by fire. In a quantitative risk assessment (QRA) model for road tunnels, uncertainty is an unavoidable component because input parameters of the model possess different levels of uncertainties which are inappropriate to be formulated by crisp numbers. In this paper, a Monte Carlo sampling-based QRA model is proposed to address parameter uncertainty of a QRA model. The tunnel risks are assessed in terms of percentile-based societal risk as well as expected number of fatalities (ENF) curve, which would facilitate tunnel managers to make decisions. A case study is carried out to demonstrate the approach. © 2011 Inderscience Enterprises Ltd.

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http://hdl.handle.net/10453/116517