Urban risk assessment model to quantify earthquake-induced elevator passenger entrapment with population heatmap

被引:0
|
作者
Gu, Donglian [1 ]
Zhang, Ning [1 ]
Xu, Zhen [1 ]
Wu, Yongjingbang [2 ,3 ]
Tian, Yuan [1 ]
机构
[1] Univ Sci & Technol Beijing, Res Inst Urbanizat & Urban Safety, Beijing, Peoples R China
[2] Shenzhen Urban Publ Safety & Technol Inst, Shenzhen, Peoples R China
[3] Emergency Management Dept, Key Lab Urban Safety Risk Monitoring & Early Warni, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
VIBRATION CONTROL; FRAGILITY; ALGORITHM;
D O I
10.1111/mice.13287
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The seismic resilience of cities plays a crucial role in achieving the United Nations Sustainability Development Goal. However, despite the occurrence of elevator passenger entrapment in numerous earthquakes, there is a notable lack of studies addressing this sophisticated issue. This study aims to bridge this gap by proposing a novel urban risk assessment model designed to evaluate city-scale earthquake-induced elevator passenger entrapment. The model integrates big data and physics-based approaches. A novel mapping method was developed to estimate city-scale elevator traffic level based on population heatmap data and deep learning. A process-based parallel computing scheme was designed to accelerate the assessment. The applicability was demonstrated based on a real-world urban area comprising 619 buildings. The findings reveal that as the time of the earthquake varies, the risk exhibits significant fluctuations. Additionally, this study highlights that a simplistic correspondence between seismic intensity and passenger entrapment risk can lead to erroneous estimations.
引用
收藏
页码:2204 / 2222
页数:19
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