Uncertainty Propagation in Quantitative Risk Assessment Modeling for Fire in Road Tunnels

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 $alpha $-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.