JRMGE / Vol 16 / Issue 12

Article

Prediction of brittle rock failure severity: An approach based on rock mass failure progress

Shengwen Qi, Songfeng Guo, Muhammad Faisal Waqar, Guangming Luo, Shishu Zhang

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a Key Laboratory of Shale Gas and Geoengineering, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China
b State Key Laboratory of Lithospheric and Environmental Coevolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China
c University of Chinese Academy of Sciences, Beijing, China
d POWERCHINA Chengdu Engineering Corporation Limited, Chengdu 610072, China


2024, 16(12): 4852-4865. doi:10.1016/j.jrmge.2024.03.005


Received: 2023-12-03 / Revised: 2024-03-18 / Accepted: 2024-03-31 / Available online: 2024-04-04

2024, 16(12): 4852-4865.

doi:10.1016/j.jrmge.2024.03.005


Received: 2023-12-03

Revised: 2024-03-18

Accepted: 2024-03-31

Available online: 2024-04-04


Abstract:

This study presents the classification and prediction of severity for brittle rock failure, focusing on failure behaviors and excessive determination based on damage depth. The research utilizes extensive field survey data from the Shuangjiangkou Hydropower Station and previous research findings. Based on field surveys and previous studies, four types of brittle rock failure with different failure mechanisms are classified, and then a prediction method is proposed. This method incorporates two variables, i.e. Kv (modified rock mass integrity coefficient) and GSI (geological strength index). The prediction method is applied to the first layer excavation of the powerhouse cavern of Shuangjiangkou Hydropower Station. The results show that the predicted brittle rock failure area agrees with the actual failure area, demonstrating the method's applicability. Next, it extends to investigate brittle rock failure in two locations. The first is the k0+890 m section of the traffic cavern, and the second one is at K0-64 m of the main powerhouse. The criterion-based prediction indicates a severity brittle rock failure in the K0+890 m section, and a moderate brittle rock failure in the K0-64 m section, which agrees with the actual occurrence of brittle rock failure in the field. The understanding and application of the prediction method using Kv and GSI are vital for implementing a comprehensive brittle rock failure prediction process in geological engineering. To validate the adaptability of this criterion across diverse tunnel projects, a rigorous verification process using statistical findings was conducted. The assessment outcomes demonstrate high accuracy for various tunnel projects, allowing establishment of the correlations that enable valuable conclusions regarding brittle rock failure occurrence. Further validation and refinement through field and laboratory testing, as well as simulations, can broaden the contribution of this method to safer and more resilient underground construction.

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Keywords: Rockburst, Brittle failure, Progressive failure, High in situ stress, Prediction method, Underground excavation

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Shengwen Qi, Songfeng Guo, Muhammad Faisal Waqar, Guangming Luo, Shishu Zhang, 2024. Prediction of brittle rock failure severity: An approach based on rock mass failure progress. J. Rock Mech. Geotech. Eng. 16 (12), 4852-4865.

Author(s) Information

Shengwen Qi

✉️ qishengwen@mail.iggcas.ac.cn

Shengwen Qi obtained his PhD in Geological Engineering from Institute of Geology and Geophysics, Chinese Academy of Sciences in 2002. He was affiliated as post-doctor and assistant research staff in Institute of Geology and Geophysics, Chinese Academy of Sciences from 2002 to 2007, Research Associate in the University of Hong Kong from 2007 to 2008, Associate Professor and Professor in Key Laboratory of Engineering Geomechanics, Chinese Academy of Sciences from 2008 to 2014, Visiting Professor of University of Alberta from 2012 to 2013, and 2014–2017, respectively. He acts as director of Key Laboratory of Shale Gas and Geoengineering (Key Laboratory of Engineering Geomechanics), Chinese Academy of Sciences since 2017. His research interests include (1) characterization of rock mass structure and related dynamic behavior; (2) seismic response of rock slope and related geohazards; (3) deformation and failure of underground engineering rock mass in high geostress area, and (4) induced earthquake by CO2 sequestration, hot dry rock exploitation. He has been participated in many mega projects such as Jinping Hydropower Station, Xiaowan Hydropower Station, and Lanzhou-Chongqing Railway Tunnel.