摘要
全断面硬岩隧道掘进机(tunnel boring machine,TBM)对岩体条件极其敏感,且其前期投入较大,准确地评估岩体可掘性、预测TBM掘进性能对TBM隧道施工至关重要。基于来自中国、伊朗两国涵盖3种不同岩性的5条TBM施工引水隧洞约300组现场数据,以现场贯入度指数FPI为岩体可掘性评价指标,分析了岩石单轴抗压强度UCS、岩体完整性指数K_v、岩体主要结构面与洞轴线的夹角α、隧洞直径D等与岩体可掘性之间的关系;探讨了适用于岩体可掘性研究的岩体参数统一方法,进一步建立了精度较高的(相关系数为0.768)岩体可掘性经验预测方法。基于该预测方法,运用K中心聚类分析方法,将岩体可掘性分为6类,探讨了不同岩体可掘性条件下TBM平均单刀推力、刀盘转速分布规律,相应成果可为实际工程中TBM施工隧洞岩体可掘性评估、掘进参数的选择、施工进度的安排提供一定的指导。
Due to the extremely high sensitivity of tunnel boring mechine(TBM)performance to rock mass conditions and its huge early investment, it is of great value to evaluate the rock mass boreability and predict the TBM performance. In this study, about 300 sets of field data from China and Iran are collected, covering three different rock types and 5 TBM tunnels. FPI(field penetration index) is selected as the evaluation index of rock mass boreability. Specifically, the relationships between rock uniaxial compressive strength(UCS), rock mass integrity index K_v, angle between main structural plane of rock mass and axis of the tunnel α, tunnel diameter, D and rock mass boreability are systematically analyzed. In addition, a unified approach of rock mass parameters which is suitable for the study of rock mass boreability is discussed in detail, and an empirical prediction model of rock mass boreability with relatively high accuracy(R^2=0.768) is further established. Based on this model and supplemented by K-center clustering method, the boreability of rock mass are classified into 6 groups, which are then applied to the exploration of the distribution of average cutter thrust and cutterhead speed under various of rock mass boreability conditions. The findings in our work shed light on the evaluation of rock mass boreability, the selection of operational parameters as well as the arrangement of TBM tunnel construction schedule.
作者
吴鑫林
张晓平
刘泉声
李伟伟
黄继敏
WU Xin-lin;ZHANG Xiao-ping;LIU Quan-sheng;LI Wei-wei;HUANG Ji-min(School of Civil Engineering,Wuhan University,Wuhan,Hubei 430072,China;Key Laboratory of Geotechnical and Structural Engineering Safety of Hubei Province,Wuhan University,Wuhan,Hubei 430072,China;Manufacturing and Installation Branch Sinohyaro Bureau 3 Co.,Ltd,Xi’an,Shaanxi 710024,China)
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2020年第5期1721-1729,1739,共10页
Rock and Soil Mechanics
基金
国家自然科学基金面上项目资助(No.51978541,No.41941018,No.51839009)。
关键词
隧道掘进机(TBM)
可掘性预测
围岩分级
掘进参数
tunnel boring mechine(TBM)
boreability prediction
rock mass classification
boring parameters
