机构地区:[1]Key Laboratory of Shale Gas and Geoengineering,Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing,China [2]State Key Laboratory of Lithospheric and Environmental Coevolution,Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing,China [3]University of Chinese Academy of Sciences,Beijing,China [4]POWERCHINA Chengdu Engineering Corporation Limited,Chengdu 610072,China
出 处:《Journal of Rock Mechanics and Geotechnical Engineering》2024年第12期4852-4865,共14页岩石力学与岩土工程学报(英文)
基 金:the National Natural Science Foundation of China(Nos.41825018,42141009);the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(No.2019QZKK0904).
摘 要: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.
关 键 词:ROCKBURST Brittle failure Progressive failure High in situ stress Prediction method Underground excavation
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