摘要
为有效评估复杂建筑人员密集区域发生突发事件时的人员疏散能力,结合人员疏散的移动速度、疏散时间、人群密度等3个方面的动力学控制方程,构建复杂建筑人员密集区域的人群疏散数学模型;以某商场突发事件为例,分别用该模型和Pathfinder软件模拟的方法,计算该商场人员疏散时间。结果表明:移动速度、疏散时间、人员密度等三者相互影响、控制,最终影响疏散效率;人群疏散数学模型与Pathfinder软件仿真模拟的疏散时间相符,并且该模型的计算结果反映出疏散时间主要与建筑物的楼层数目、人群移动速度、人群密度以及楼梯的物理参数等有关;该模型预判出疏散人员在楼梯口易发生堵塞且最占用疏散时间。
In order to effectively assess the evacuation ability in crowded place of a complex building in the event of an emergency,combined with the dynamic control equations of the evacuation speed, evacuation time,and population density,the mathematical model of crowd evacuation in a complex building was constructed. Taking a sudden event in a shopping mall as an example,the model and the Pathfinder software simulation method were used to calculate the evacuation time. The results show that the moving speed,evacuation time and personnel density influence and control each other,which ultimately affects the evacuation efficiency. The evacuation time obtained by the mathematical model is consistent with that simulated by Pathfinder software,and the calculation results of the model reflect that evacuation time correlates with the number of floors of the building,the speed of movement of the crowd,the crowd density,and physical parameters of the stairs. The model predicts that blockage is more likely to occur at the stairway and takes up most of the evacuation time.
作者
陈一洲
陈文涛
张无敌
韩晶
周欣鑫
王志伟
CHEN Yizhou;CHEN Wentao;ZHANG Wudi;HAN Jing;ZHOU Xinxin;WANG Zhiwei(Institute of Public Safety Research,China Academy of Building Research,Beijing 100013,China;China Research Center for Emergency Management,Wuhan University of Technology,WuhanHubei 430070,China;China Occupational Safety and Health Association,Beijing 100011,China;School of Energy and Mining Engineering,China University of Mining and Technology-Beijing,Beijing 100083,China;School of Civil and Resource Engineering,University of Science andTechnology Beijing,Beijing 100083,China)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2019年第5期13-18,共6页
China Safety Science Journal
基金
国家重点研发计划项目(2017YFC0803300)
中国建筑科学研究院科研基金资助(20160111330730034)
