摘要
为了充分保障大规模人群疏散安全目标的实现,进行Revit二次开发,构建建筑物节点状态数据智能提取系统,自动生成建筑物节点初始状态数据库,利用自适应蚁群算法,以全体待疏散人群完成安全疏散时间最短为优化目标,开发人群应急疏散路径优化及智能诱导模型。通过对有无疏散诱导情况下某医院火灾中人员完成疏散所需时间及各出口人员滞留情况的对比,结果表明,基于Revit的数据智能提取系统,改善了医院火灾人员疏散路径优化算法初始状态和边界条件的处理方案,显著提高了疏散优化算法的运行效率,在保障医患人员安全疏散的同时,有效避免了从众现象造成的个别出口拥堵现象。
In order to fully guarantee the goal of achieving the safety of large-scale crowd evacuation, the Revit software was re-developed to build an intelligent extraction system for building node state data, automatically generate the initial state database of building nodes, and use adaptive ant colony algorithm. The optimization goal is to minimize the time required for all evacuated people to complete a safe evacuation, and develop a model based on crowd emergency evacuation route optimization and intelligent guidance. In a hospital fire, by comparing the evacuation time and the detention of personnel at various exits with or without evacuation induction, the results show that the data intelligent extraction system based on Revit can improve the initial state and boundary conditions of the hospital fire personnel evacuation route optimization algorithm treatment plan, significantly improve the efficiency of the evacuation optimization algorithm, and effectively avoid the congestion of individual exits caused by the herd phenomenon while ensuring the safe evacuation of the medical and patient population.
作者
宋嘉宝
姜雪
张培红
SONG Jiabao;JIANG Xue;ZHANG Peihong(College of Resources and Civil Engineering, Northeastern University Shenyang 110819)
出处
《工业安全与环保》
2021年第4期1-5,共5页
Industrial Safety and Environmental Protection
基金
国家重点研发计划项目(2017YFC0804900)。
关键词
大型医院火灾
疏散路径优化
Revit二次开发
数据库建立
large hospital fire
evacuation route optimization
Revit secondary development
database establishment
