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Support pressure assessment for deep buried railway tunnels using BQ-index 被引量:6
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作者 WANG Ming-nian WANG Zhi-long +3 位作者 TONG Jian-jun ZHANG Xiao DONG Yu-cang LIU Da-gang 《Journal of Central South University》 SCIE EI CAS CSCD 2021年第1期247-263,共17页
Estimation of support pressure is extremely important to the support system design and the construction safety of tunnels.At present,there are many methods for the estimation of support pressure based on different roc... Estimation of support pressure is extremely important to the support system design and the construction safety of tunnels.At present,there are many methods for the estimation of support pressure based on different rock mass classification systems,such as Q system,GSI system and RMR system.However,various rock mass classification systems are based on different tunnel geologic conditions in various regions.Therefore,each rock mass classification system has a certain regionality.In China,the BQ-Inex(BQ system)has been widely used in the field of rock engineering ever since its development.Unfortunately,there is still no estimation method of support pressure with BQ-index as parameters.Based on the field test data from 54 tunnels in China,a new empirical method considering BQ-Inex,tunnel span and rock weight is proposed to estimate the support pressure using multiple nonlinear regression analysis methods.And then the significance and necessity of support pressure estimation method for the safety of tunnel construction in China is explained through the comparison and analysis with the existing internationally widely used support pressure estimation methods of RMR system,Q system and GSI system.Finally,the empirical method of estimating the support pressure based on BQ-index was applied to designing the support system in the China’s high-speed railway tunnel—Zhengwan high-speed railway and the rationality of this method has been verified through the data of field test. 展开更多
关键词 rock mass classification support pressure deep buried tunnel field test multiple nonlinear regression analysis BQ-Index
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