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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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Key factor analysis and model establishment of variation of rock face temperature in a deep open-pit mine 被引量:5
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作者 WANG Yuan DU Cui-feng +1 位作者 JIN Wen-bo WANG Pu-yu 《Journal of Central South University》 SCIE EI CAS CSCD 2018年第7期1786-1798,共13页
In recent years, with the increase of the depth of open-pit mining, the pollution level has been on the rise due to harmful gases and dust occurring in the process of mining. In order to accelerate the diffusion of th... In recent years, with the increase of the depth of open-pit mining, the pollution level has been on the rise due to harmful gases and dust occurring in the process of mining. In order to accelerate the diffusion of these air pollutants, the distributed regularity of the rock face temperature which is directly related to the air ventilation in deep open-pit mines should be studied. Here, we establish the key factors influencing the rock face temperature in a deep open-pit mine. We also present an empirical model of the rock face temperature variation in the deep open-pit mine, of which the performance is interestingly high compared with that of the field test. This study lays a foundation to study the ventilation thermodynamic theory in the deep open-pit mine, which is of great importance for theoretical studies and engineering applications of solving air pollution problem in deep open-pit mines. 展开更多
关键词 deep open-pit mine distributed regularity of rock face temperature dimensional analysis nonlinear regression analysis
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