施工阶段隧道围岩快速分级法

Rapid Classification Method of Tunnel Surrounding Rock in Construction Stage

现阶段隧道围岩分级工作主要在勘察设计阶段进行,但由于受周边环境及勘察手段的限制,分级结果往往与围岩实际情况不符。为准确获得隧道围岩等级,基于声波-回弹联合测试法,建立“BP神经网络模型”在施工阶段快速预测岩石强度(Rc),利用掌子面炮孔进行岩体纵波波速测试并通过公式计算完整性系数(Kv)后,得到基于岩体基本质量指标(BQ)的施工阶段围岩快速分级法,并以宝汉高速石门隧道为依托在施工阶段对围岩进行分级。结果表明:建立的BP神经网络预测模型可实现岩石强度的现场快速无损预测,预测结果具有较高准确度;根据岩体纵波波速测试结果,可实现岩体完整性系数的定量计算,进而完成石门隧道施工阶段围岩快速分级,对比勘察阶段的分级结果,施工阶段所获得的分级结果更加精确。

At present,the surrounding rock classification in tunnels is mainly carried out in the survey and design stage.However,due to the influence of surrounding environment and exploration methods,the classification results often do not match the actual quality of surrounding rock.In order to accurately obtain the surrounding rock grade of tunnel,a“BP neural network model”for rapid prediction of Rc in construction was established based on the combined ultrasonic-rebound test method.After P-wave velocity of rock mass was tested by blasting tunnel face holes,the value of integrity coefficient,(Kv)was computed by formula.Thus,a rapid classification method was obtained by the BQ value.Based on the Shimen Tunnel of Baoji-Hanzhong Expressway,surrounding rock was classified in construction stage.Results show that the BP neural network prediction model can realize fast and non-destructive prediction of rock strength,and the prediction results have high accuracy.Meanwhile,according to the measuring results of P-wave velocity of rock mass,the quantitative calculation of rock mass integrity index can be realized,whichcan be used as a good reference for the support,evaluation and later treatmentof lining design of the exit section of the tunnel,and the rapid classification of surrounding rock in construction stage of the Shimen Tunnel can be accomplished.Finally,compared with the classification results of prospecting stage in the Shimen tunnel,the classification results obtained in construction stage are more accurate.