China Safety Science Journal ›› 2023, Vol. 33 ›› Issue (12): 167-175.doi: 10.16265/j.cnki.issn1003-3033.2023.12.2206

• Public safety • Previous Articles     Next Articles

Coupling smoke information and Monte Carlo simulation for evacuation of tunnel fires and its optimization

ZHANG Xiaochun1(), CHEN Linjie1, ZHOU Geyao1, ZHANG Zhaomin2, WEI Ruichao2,**(), WU Binbin3   

  1. 1 School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou Guangdong 511400, China
    2 Institute of New Energy Vehicle Research, Shenzhen Institute of Vocational Technology, Shenzhen Guangdong 518055, China
    3 Guangdong Provincial Academy of Building Research Group Co., Ltd., Guangzhou Guangdong 510010, China
  • Received:2023-06-20 Revised:2023-09-18 Online:2023-12-28 Published:2024-06-28
  • Contact: WEI Ruichao

Abstract:

In order to ensure the safe evacuation of people under tunnel fire, a tunnel in Guangzhou city was studied as an example. Firstly, 18 simulation conditions were formed by the combination of three factors: fire heat release rate, natural wind speed and fire location. Secondly, the available safe evacuation time (ASET) was solved with the fire dynamics simulator(FDS), and the hazard characteristic parameters such as smoke visibility, temperature and CO concentration in the grid were obtained. Then, the smoke information was coupled with Monte Carlo simulation to solve the required safe egress time (RSET) and fractional effective dose (FED) with the Pathfinder. Finally, the double criterion (whether ASET was greater than RSET or not, and whether individual risk value FED exceeded the standard or not) were used to analyze the scenarios, and the hazard scenarios were optimized and their effects were quantified. The results show that the personnel evacuation risk is significantly correlated with the fire heat release rate and natural wind speed, but has nothing to do with fire location. In addition, the evacuation optimization efficiency of the method based on zonal evacuation and dynamic exits is more than 10%.

Key words: tunnel fire, personnel evacuation, smoke information, Monte Carlo simulation, evacuation risk, dual criterion, optimization effect