ISSN 2096-4498
CN 44-1745/U
Tunnel Construction ›› 2021, Vol. 41 ›› Issue (2): 212-224.DOI: 10.3973/j.issn.2096-4498.2021.02.007
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WANG Ke1, 2
Online:
Published:
Abstract: In this study, a large number of deepburied rockburst tunnel data are collected. The causes, processes, and characteristics of largearea rockburst that occurred in existing and underconstruction tunnels are statistically analyzed, and the rockburst trends, prediction methods, and disposal measures are summarized and analyzed. The drawn conclusions are presented as follows. (1) In the rockburst prediction stage, the rockburstclassification discriminant based on the physicomechanical properties is universal to a certain extent, and the criterion value can be applied to tunnels with similar lithology and depth. The accuracy and characteristics of the prediction results can be checked using multiple discriminants, and the fieldmonitoring measurement provides an important reference and validation for the establishment of the criterion. (2) The stressrelief methods of different rockburst grades in the prevention and control stage are water sprinkling for the slightrockburst section and stress release hole for the strongrockburst section. (3) The primary support parameters of surrounding rocks with different grades are summarized, and based on the comparison and summary of the drilling and blasting methods, the excavation methods, advancement length, and corresponding waiting time of the differentrock blasting sections are proposed. (4) It is recommended that the acquisition of rockburst prediction information and the entire monitoring of the displacement and strain fields in the rockburst process can be realized using the technologies of machine learning, large database, unmanned aerial vehicle, machine vision, signal acquisition, and multispectral and thermal imaging. A new simulation method for rockburst process using discreteelement energy iteration algorithm is proposed.
Key words: deep buried tunnel, rockburst characteristic, rockburst prediction, rockburst prevention, TBM
CLC Number:
U 455
WANG Ke. Overview of StateofArt of Rockburst Prediction and Prevention Techniques for Deepburied Tunnels[J]. Tunnel Construction, 2021, 41(2): 212-224.
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URL: http://www.suidaojs.com/EN/10.3973/j.issn.2096-4498.2021.02.007
http://www.suidaojs.com/EN/Y2021/V41/I2/212
Rockburst Characteristics and Prevention and Control Technologies for Tunnel Boring Machine Construction of Deepburied Tunnels