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http://dx.doi.org/10.9711/KTAJ.2018.20.1.011

Study on the prediction of the stopping probabilities in case of train fire in tunnel by Monte Carlo simulation method  

Ryu, Ji-Oh (Dept. of Automotive Engineering, Shin-Han University)
Kim, Jong-Yoon (Dept. of Fire Safety Management, Seojeong College)
Kim, Hyo-Gyu (Jusung G&B. Inc.)
Publication Information
Journal of Korean Tunnelling and Underground Space Association / v.20, no.1, 2018 , pp. 11-22 More about this Journal
Abstract
The safety of tunnels is quantified by quantitative risk assessment when planning the disaster prevention facilities of railway tunnels, and it is decided whether they are appropriate. The purpose of this study is to estimate the probability of the train stopping in the tunnels at train fire, which has a significant effect on the results of quantitative risk assessment for tunnel fires. For this purpose, a model was developed to calculate the coasting distance of the train considering the coefficient of train running resistance. The probability of stopping in case of train fire in the tunnel is predicted by the Monte Carlo simulation method with the coasting distance and the emergency braking distance as parameters of the tunnel lengths and slopes, train initial driving speeds. The kinetic equations for predicting the coasting distance were analyzed by reflecting the coefficient train running resistance of KTX II. In the case of KTX II trains, the coasting distance is reduced as the slope increases in a tunnel with an upward slope, but it is possible to continue driving without stopping in a slope downward. The probability of the train stopping in the case of train fire in tunnel decreases as the train speed increases and the slope of the tunnel decreases. If human error is not taken into account, the probability that a high-speed train traveling at a speed of 250 km/h or above will stop in a tunnel due to a fire is 0% when the slope of the tunnel is 0.5% or less, and the probability of stopping increases rapidly as the tunnel slope increases and the tunnel length increases.
Keywords
Quantitative risk assessment; Coasting operation and distance; The coefficient of train running resistance; Probability of stopping in tunnel;
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