摘要
为了提高地下停车场火灾中人车混行疏散的安全性和高效性,采用Python语言构建基于元胞自动机的背景场模型,加入PyroSim模拟的火灾场数据,得到火灾与人车混行疏散动态耦合模型。以西安某商业综合体地下停车场为研究对象,开展人车混行疏散仿真模拟实验。结果表明:相较于行人疏散,人车混行的必需安全疏散时间延长了20%~130%,仅在一定的行人密度和车位占用率下才能实现安全疏散;行人密度较大时会在出口产生拱形效应,同时降低行人和车辆的疏散效率;车辆疏散失败的概率约为行人的22倍,行人即使成功疏散至出口,依然有15%~25%存在不同程度受伤,重伤和濒死人数比例与疏散行人密度呈正相关。研究结果可为地下停车场防火设计优化和人车疏散预案制定提供参考依据。
In order to enhance the safety and efficiency of pedestrian-vehicle evacuation in underground parking lot fires,a background field model based on cellular automata is constructed using Python.The model incorporates fire field data of the PyroSim simulation to create a dynamic coupling model of fire and pedestrian-vehicle evacuation.A simulation study is conducted in the underground parking lot of a commercial complex in Xi'an.The results show that,compared to pedestrian evacuation,the Required Safety Egress Time(RSET)for pedestrian-vehicle evacuation is extended by 20%to 130%.Safe evacuation is only achievable under specific conditions of pedestrian density and parking space occupancy.The arch effect is observed at the exit when pedestrian density is high,which reduces the evacuation efficiency of both pedestrians and vehicles.The probability of vehicle evacuation failure is approximately 22 times higher than that of pedestrians.Even if pedestrians successfully reach the exit,15%to 25%still suffer from varying degrees of injury,with the proportion of serious injuries and near-death cases positively correlated with the pedestrian evacuation density.These findings can serve as a reference for optimizing fire protection design in underground parking lots and formulating evacuation plans for both people and vehicles.
作者
翟越
韩珠琳
屈璐
韩策
Zhai Yue;Han Zhulin;Qu Lu;Han Ce(School of Geology Engineering and Geomatics,Chang'an University,Xi'an 710064,P.R.China)
出处
《地下空间与工程学报》
北大核心
2025年第6期2217-2226,共10页
Chinese Journal of Underground Space and Engineering
基金
国家自然科学基金(52008030)
陕西省创新人才推进计划-科技创新团队(2021TD-55)
陕西省秦创原“科学家+工程师”队伍建设(2022KXJ-107)。
关键词
地下停车场
人车混行
火灾疏散
元胞自动机
仿真模拟
underground parking lot
pedestrian-vehicle mixed flow
fire evacuation
cellular automata
simulation
