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

机译:参数不确定的公路隧道火灾概率量化风险评估模型

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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.
机译:公路隧道中的火灾可能会导致灾难性后果,同时还会导致隧道安全设置失败,因此需要一种可靠且强大的方法来评估火灾引起的隧道风险。在公路隧道的定量风险评估(QRA)模型中,不确定性是不可避免的组成部分,因为模型的输入参数具有不同程度的不确定性,这些不确定性不适合用清晰数字来表示。本文提出了一种基于蒙特卡洛采样的QRA模型来解决QRA模型的参数不确定性。隧道风险根据基于百分比的社会风险以及预期的死亡人数(ENF)曲线进行评估,这将有助于隧道管理者做出决策。进行了案例研究以证明该方法。

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