LAPSE:2023.23312
Published Article

LAPSE:2023.23312
A Microseismicity-Based Method of Rockburst Intensity Warning in Deep Tunnels in the Initial Period of Microseismic Monitoring
March 27, 2023
Abstract
Rockburst disasters in deep tunnels cause serious casualties and economic losses. It is a great challenge to make a warning for rockbursts in geotechnical engineering. In this work, a microseismicity-based rockburst intensity warning method is proposed that is suitable for use in deep tunnels in the initial period of microseismic (MS) monitoring. The method first involves collecting information on a sample of no more than five cases. Then, the event to be analyzed is combined with the sample events and subjected to cluster analysis. Finally, a rockburst intensity warning is generated according to the results of the cluster analysis or after a second cluster analysis. It is a comprehensive, multi-parameter rockburst intensity warning method that only needs a few rockburst cases for input which makes it suitable in the initial period of MS monitoring. The method also incorporates the novel idea of a second cluster analysis. An engineering application based on deep tunnels in the Jinping II hydropower station in Sichuan Province, China, shows that the rockburst intensity warning results based on the proposed method agree well with the actual situations in four tests carried out. The method will enrich the techniques used to warn of rockbursts based on microseismicity.
Rockburst disasters in deep tunnels cause serious casualties and economic losses. It is a great challenge to make a warning for rockbursts in geotechnical engineering. In this work, a microseismicity-based rockburst intensity warning method is proposed that is suitable for use in deep tunnels in the initial period of microseismic (MS) monitoring. The method first involves collecting information on a sample of no more than five cases. Then, the event to be analyzed is combined with the sample events and subjected to cluster analysis. Finally, a rockburst intensity warning is generated according to the results of the cluster analysis or after a second cluster analysis. It is a comprehensive, multi-parameter rockburst intensity warning method that only needs a few rockburst cases for input which makes it suitable in the initial period of MS monitoring. The method also incorporates the novel idea of a second cluster analysis. An engineering application based on deep tunnels in the Jinping II hydropower station in Sichuan Province, China, shows that the rockburst intensity warning results based on the proposed method agree well with the actual situations in four tests carried out. The method will enrich the techniques used to warn of rockbursts based on microseismicity.
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Keywords
clustering analysis, deep tunnel, microseismicity, rock mechanics, rockburst intensity, warning
Subject
Suggested Citation
Feng G, Lin M, Yu Y, Fu Y. A Microseismicity-Based Method of Rockburst Intensity Warning in Deep Tunnels in the Initial Period of Microseismic Monitoring. (2023). LAPSE:2023.23312
Author Affiliations
Feng G: State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China; Guangxi Key Laboratory of Disaster Prevention and Engineering Safety, Key Laboratory of Disaster Pre [ORCID]
Lin M: School of Resources and Safety Engineering, Wuhan Institute of Technology, Wuhan 430071, China
Yu Y: National Experimental Teaching Demonstration Center of Civil Engineering, East China Jiaotong University, Nanchang 330013, China
Fu Y: National Experimental Teaching Demonstration Center of Civil Engineering, East China Jiaotong University, Nanchang 330013, China
Lin M: School of Resources and Safety Engineering, Wuhan Institute of Technology, Wuhan 430071, China
Yu Y: National Experimental Teaching Demonstration Center of Civil Engineering, East China Jiaotong University, Nanchang 330013, China
Fu Y: National Experimental Teaching Demonstration Center of Civil Engineering, East China Jiaotong University, Nanchang 330013, China
Journal Name
Energies
Volume
13
Issue
11
Article Number
E2698
Year
2020
Publication Date
2020-05-27
ISSN
1996-1073
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Original Submission
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PII: en13112698, Publication Type: Journal Article
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LAPSE:2023.23312
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https://doi.org/10.3390/en13112698
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Mar 27, 2023
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