Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1539-6924.2010.01503.x
Title: Quantitative Risk Assessment Modeling for Nonhomogeneous Urban Road Tunnels
Authors: Meng, Q. 
Qu, X. 
Wang, X.
Yuanita, V.
Wong, S.C.
Keywords: Individual risk
Nonhomogeneous urban road tunnel
QRA
Traffic congestion
Issue Date: Mar-2011
Source: Meng, Q., Qu, X., Wang, X., Yuanita, V., Wong, S.C. (2011-03). Quantitative Risk Assessment Modeling for Nonhomogeneous Urban Road Tunnels. Risk Analysis 31 (3) : 382-403. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1539-6924.2010.01503.x
Abstract: Urban road tunnels provide an increasingly cost-effective engineering solution, especially in compact cities like Singapore. For some urban road tunnels, tunnel characteristics such as tunnel configurations, geometries, provisions of tunnel electrical and mechanical systems, traffic volumes, etc. may vary from one section to another. These urban road tunnels that have characterized nonuniform parameters are referred to as nonhomogeneous urban road tunnels. In this study, a novel quantitative risk assessment (QRA) model is proposed for nonhomogeneous urban road tunnels because the existing QRA models for road tunnels are inapplicable to assess the risks in these road tunnels. This model uses a tunnel segmentation principle whereby a nonhomogeneous urban road tunnel is divided into various homogenous sections. Individual risk for road tunnel sections as well as the integrated risk indices for the entire road tunnel is defined. The article then proceeds to develop a new QRA model for each of the homogeneous sections. Compared to the existing QRA models for road tunnels, this section-based model incorporates one additional top event-toxic gases due to traffic congestion-and employs the Poisson regression method to estimate the vehicle accident frequencies of tunnel sections. This article further illustrates an aggregated QRA model for nonhomogeneous urban tunnels by integrating the section-based QRA models. Finally, a case study in Singapore is carried out. © 2010 Society for Risk Analysis.
Source Title: Risk Analysis
URI: http://scholarbank.nus.edu.sg/handle/10635/59177
ISSN: 02724332
DOI: 10.1111/j.1539-6924.2010.01503.x
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