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Research Article | Open Access

Monitoring and early warning mechanism of flood invasion into subway tunnels based on the experimental study of flooding patterns

Wenxuan DongaHong Huanga( )Maohua ZhongaHanjun WangbFucai Huab
Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China
Beijing Urban Construction Design & Development Group Co., Limited, Beijing 100037, China
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Abstract

Subway tunnel flooding is one of the typical scenarios in urban waterlogging. When the emergency decision-making is untimely and inaccurate, it can lead to serious casualties. However, it is expected that through some responsive monitoring methods, an intelligent system can be constructed to achieve the real-time perception of the underground flood situation and to predict the process and intensity of the disaster. This study is based on a scale model experiment of flooding in straight subway tunnels. Firstly, it classified the basic patterns of the flood process. Some fitting formulas were respectively established for water depth and kinematic parameters. A calculation method for quickly predicting the flood inundation process was constructed. Secondly, this paper proposed a mode for the monitoring and early warning system. Based on the flood patterns and characteristic variables in subway tunnel flooding, the system can quickly determine the flow rate and entry position of flood and deduce the flood trend in the future at a relatively low cost. The system workflow was divided into three phases, and the mechanism for each phase of the system was sorted out. It could help to provide scientific and reliable information for emergency decision-making and gain time for the emergency response.

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Journal of Intelligent Construction
Article number: 9180011
Cite this article:
Dong W, Huang H, Zhong M, et al. Monitoring and early warning mechanism of flood invasion into subway tunnels based on the experimental study of flooding patterns. Journal of Intelligent Construction, 2024, 2(2): 9180011. https://doi.org/10.26599/JIC.2024.9180011
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Received: 01 November 2023
Revised: 22 December 2023
Accepted: 18 January 2024
Published: 16 May 2024
© The Author(s) 2024. Published by Tsinghua University Press.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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