Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/59248
Title: Uncertainty propagation in quantitative risk assessment modeling for fire in road tunnels
Authors: Meng, Q. 
Qu, X.
Keywords: Fire
fuzzy sets
parameter uncertainty
quantitative risk assessment (QRA)
road tunnel
Issue Date: 2012
Citation: Meng, Q., Qu, X. (2012). Uncertainty propagation in quantitative risk assessment modeling for fire in road tunnels. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 42 (6) : 1454-1464. ScholarBank@NUS Repository.
Abstract: Road tunnels are critical transportation infrastructures that provide underground passageways for motorists and commuters. Fire in road tunnels in combination with tunnel safety provisions failure may lead to catastrophic consequences, and thus, necessitates a robust and reliable approach to assess tunnel risks. This article proposes a quantitative risk assessment model for fire in road tunnel by taking into consideration two types of uncertainties. A Monte Carlo-based estimation method is developed to propagate parameter uncertainty in quantitative risk assessment model consisting of event tree analysis as well as consequence estimation models. The percentile-based individual risks and α-cut-based societal risks are put up and the risk indices are proven to be very useful for tunnel operators with distinct risk attitudes to assess the safety level of a road tunnel. Finally, the proposed research methodology is applied to Singapore KPE road tunnels. © 1998-2012 IEEE.
Source Title: IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews
URI: http://scholarbank.nus.edu.sg/handle/10635/59248
ISSN: 10946977
Appears in Collections:Staff Publications

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