Research on Emergency Evacuation of Earthquake Secondary Fire in the Subway System
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摘要: 破坏性地震常伴随地震次生灾害，后果严重。地铁系统作为城市重要通行设施，研究其在地震次生灾害下的应急疏散十分必要。本文以地震次生火灾为例，基于地震次生火灾特点，深入探讨地铁站人员疏散情况。利用Pyrosim软件建立地震次生火灾模型，分析地铁站内部温度、CO浓度、能见度等因素的变化，确定影响人员疏散的关键因素。在此基础上，使用Pathfinder软件建立人员疏散模型，研究关键因素人员疏散速度的影响，从而获得更准确的疏散动态。研究结果表明，能见度是影响人员疏散的关键因素；此外，楼/扶梯处能见度下降导致疏散速度降低，尤其是在靠近火源位置的楼/扶梯上，滞留时间显著增加。Abstract: Destructive earthquakes are often accompanied by secondary disasters, which can lead to severe consequences. The urban subway system, as a vital transportation infrastructure, necessitates thorough study of emergency evacuation procedures in the event of earthquake-induced secondary disasters. This study focuses on earthquake secondary fires as a representative example. Based on the characteristics of such fires, it conducts an in-depth investigation into the evacuation behavior of subway station occupants. Using PyroSim software, an earthquake secondary fire model is established to analyze variations in internal temperature, CO concentration, visibility, and other critical factors within the subway station, thereby identifying the key factors influencing evacuation. Subsequently, a pedestrian evacuation model is developed using Pathfinder software to examine how these factors affect evacuation speed and dynamics, enabling a more accurate assessment of evacuation processes. The results demonstrate that visibility is the primary factor impacting evacuation efficiency. Moreover, reduced visibility on escalators notably decreases evacuation speed, particularly on escalators near the fire source, resulting in a significant increase in occupant residence time.
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Key words:
- Subway system /
- Earthquake secondary disaster /
- Fire simulation /
- Emergency evacuation
1)1 https://www.bilibili.com/video/av957969364/ -
图 1 地铁站震后火灾应急疏散模拟框架
Figure 1. Framework of subway station post-shock fire emergency evacuation simulation
图 4 沧安路地铁站各层内部布置情况示意图
Figure 4. Schematic diagram of the internal layout of each floor of Cang'anlu subway station
图 6 地铁站各层温度分布云图（360 s）
Figure 6. Temperature distribution cloud on each floor of the subway station （360 s）
图 8 地铁站各层CO浓度分布云图（360 s）
Figure 8. Cloud map of CO concentration distribution on each floor of the subway station （360 s）
图 10 地铁站各层能见度分布云图（153 s）
Figure 10. Cloud map of visibility distribution on each floor of the subway station （153 s）
图 11 能见度对疏散影响的分析流程
Figure 11. Analysis process of the impact of visibility on evacuation
表 1 预测远期高峰客流量（单位：人/h）
Table 1. Peak passenger flow in the long term prediction（Unit: person/h）
项目 下行方向 上行方向 上车 下车 断面 上车 下车 断面 客流量/(人·h−1) 2924 117 9991 108 2819 12125 
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表 2 人员特性表
Table 2. Personnel characteristics
类别 儿童 成年男性 成年女性 老人 步行速度/（m·s−1） 0.79 1.28 1.15 0.86 平均肩宽/cm 33 41 38 39 人员比例/% 9 41 39 11
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表 3 各楼/扶梯的能见度-速度折减系数
Table 3. The reduction coefficient of visibility of the escalators on each floor with speed
时间/s 折减系数 1号扶梯 2号楼梯 3号楼梯 2、3号楼梯 4号扶梯 0 1.00 1.00 1.00 1.00 1.00 30 1.00 1.00 1.00 1.00 1.00 60 1.00 1.00 1.00 1.00 1.00 90 1.00 1.00 1.00 1.00 1.00 120 1.00 1.00 1.00 1.00 1.00 150 0.44 1.00 1.00 1.00 1.00 180 0.28 1.00 1.00 0.81 1.00 210 0.21 0.76 1.00 1.00 1.00 240 0.22 0.63 1.00 0.70 0.85 270 0.20 0.49 0.64 0.46 0.63 300 0.20 0.41 0.47 0.37 0.45 330 0.20 0.36 0.44 0.45 0.45 360 0.20 0.31 0.33 0.41 0.43
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表 4 各区域滞留时间
Table 4. Stay time in each region
滞留时间 预反应 站台层 1号扶梯 速度折减前 60.0 s 88.0 s 53.5 s 速度折减后 60.0 s 88.0 s 64.1 s 增长率 0.0% 0.0% 19.8%
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