몬테카를로 시뮬레이션에 의한 화재열차의 터널 내 정차확률 예측에 관한 연구 = Study on the prediction of the stopping probabilities in case of train fire in tunnel by Monte Carlo simulation method

국문 초록 (Abstract)

철도터널의 방재시설 계획 시 터널의 안전성을 정량적 위험도 평가에 의해서 정량화하여 방재시설의 적정성 여부를 판단하도록 하고 있다. 이에 본 연구에서는 터널화재에 대한 정량적 위험도 평가 시 결과에 크게 영향을 미치는 화재열차의 터널 내 정차확률을 예측하는 방법을 제시하였다. 이를 위해서 열차의 주행저항계수를 고려하여 타력운전거리를 계산하기 위한 모델을 개발하였으며, 타력운전특성과 비상제동거리를 고려하여 몬테카를로 시뮬레이션 기법에 의해 터널연장 및 경사도, 초기주행속도를 변수로 하여 화재열차가 터널에 정차할 확률을 예측하였다. 타력운전거리의 예측을 위한 운동방정식은 KTX II의 주행저항계수를 반영하여 분석하였다. KTX II 열차의 경우, 타력운전거리는 상향경사의 터널에서는 경사도가 증가할수록 감소하나 하향경사구간에서는 정지하지 않고 계속하여 주행이 가능하다. 화재열차의 터널 내 정차확률은 열차의 주행속도가 증가할수록, 경사도가 낮을수록 감소하며, 고속열차(주행속도 250 km/h 이상)는 인적오류를 고려하지 않는 경우, 경사도 0.5% 이하의 터널에서는 화재 시 열차가 터널에 정차할 확률은 0%이고, 경사도가 증가하고 터널연장이 증가하면 정차확률은 급격하게 증가하는 것으로 나타났다.

다국어 초록 (Multilingual 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.

참고문헌 (Reference)

1 최원일, "고속철도 터널의 정량적 위험도 분석(QRA)을 위한 세부기준에 관한 고찰" 한국암반공학회 18 (18): 393-407, 2008

2 Arkin, Y., "Using quantitative risk assessment (ARA) and cost benefit analysis (CBA) to prioritize fire and life safety risk reduction measures in old railway tunnels" 2002

3 Vuchic, V.R., "Urban Public Transportation: Systems and Technology" Prentice-Hall, Inc 1981

4 Beard, A., "The handbook of tunnel fire safety" ICE Publishing 555-587, 2005

5 UIC, "TSI-high speed-safteyin tunnels-law-and-techn text-with annexes" 2007

6 Broder, B., "Risk based design of long railway tunnel up to 20 km length" 173-182, 1999

7 Andrews, H.I., "Railway traction: the principles of mechanical and electrical railway traction" Elsevier 1986

8 KORAIL, "Large-scale accident field manual for high-speed railway" 2016

9 Mann, P., "Fire risk assessment study for a high speed train, PMSC Limited Paper on Generic Approach to Fire QRA for High Speed Trains" 1-23, 2005

10 Yoo, J.O., "Designing the roadbed of the Seoul Metropolitan Expressway (Suseo-Pyeongtaek) - Designing a quantitative risk assessment standard"

11 Jong, J.C., "Analytical solutions for predicting train coasting dynamics" 4 : 91-103, 2003

12 Yun, S.H., "Analysis and validation of a general expression for high-speed train resistance" 166-171, 2015

13 Park, S. C., "A study on high speed high speed propulsion control system (commissioned report)" Korea Railroad Research Institute 29-34, 2009

14 Kwon, H.B., "A prediction of the equation of resistance to motion for Korean high-speed train" 1-7, 2007