A fire risk pre-warning framework for high-rise buildings based on unascertained method

被引:0
|
作者
Zhang, Li-Ning [1 ]
Wang, Xiang-Ming [2 ]
An, Jing [3 ]
Li, Hong Xian [4 ]
Guo, Jiao-Qian [1 ]
Han, Guo-Bo [1 ]
Gou, Peng-Fei [5 ]
机构
[1] School of Architecture Engineering, North China Institute of Science and Technology, Beijing
[2] School of Project Management, The University of Sydney, Sydney, 2006, NSW
[3] School of Electronic Information Engineering, North China Institute of Science and Technology, Beijing
[4] School of Architecture and Built Environment, Deakin University, Geelong
[5] School of Mechanical and Electrical Engineering, Beijing University of Technology, Beijing
基金
新加坡国家研究基金会;
关键词
Case study; High-rise buildings; Pre-warning tree for fire prevention risk; Unascertained pre-warning modeling;
D O I
10.1007/s11356-024-35396-y
中图分类号
学科分类号
摘要
The growing global interest in preventing and controlling fires in high-rise buildings reflects the increasing significance of this issue today. This research aims to establish an early warning framework for fire risk in high-rise buildings. Firstly, considering the importance of a scientific indicator system for the application of the model, this study combines the event analysis method with the building design fire code to identify 11 key risk factors that have a far-reaching impact on the prevention of fires in high-rise buildings. Based on identifying the risk factors, a high-rise building fire risk warning tree is also established, which scientifically solves the problem of the indicator system of the warning object. Subsequently, in response to the various complex issues arising from the uncertainty of fire occurrence in high-rise buildings, this study adopts the unascertained method to model the fire risk of high-rise buildings for early warning. In addition, the developed methodology was empirically validated through case studies and analyses of empirical data on fire risks in nine representative high-rise buildings. The results of the unascertained method were also compared with the results of the K-means method, from which it was concluded that the unascertained method can predict building fires more accurately. The research results provide a reliable decision support system for fire disaster prevention and control in high-rise buildings. © The Author(s) 2024.
引用
收藏
页码:61912 / 61926
页数:14
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