Prediction and classification of rock mass boreability in TBM tunnel

WU Xin-lin; ZHANG Xiao-ping; LIU Quan-sheng; LI Wei-wei; HUANG Ji-min

doi:10.16285/j.rsm.2019.0963

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Prediction and classification of rock mass boreability in TBM tunnel

更新时间：2026-06-25

- Prediction and classification of rock mass boreability in TBM tunnel
- Vol. 41, Issue 5, Pages: 1721-1729(2020)
- 作者机构：
  
  1. 武汉大学土木建筑工程学院,湖北,武汉,430072
  2. 武汉大学岩土与结构工程安全湖北省重点实验室,湖北,武汉,430072
  3. 中国水利水电第三工程局有限公司,陕西,西安,710024
- 作者简介：
- 基金信息：
- DOI：10.16285/j.rsm.2019.0963
  CLC： U455.31
- Online First：07 July 2020，
  
  Published：2020
- 稿件说明：
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WU Xin-lin, ZHANG Xiao-ping, LIU Quan-sheng, et al. Prediction and classification of rock mass boreability in TBM tunnel[J]. 2020, 41(5): 1721-1729.
DOI：

WU Xin-lin, ZHANG Xiao-ping, LIU Quan-sheng, et al. Prediction and classification of rock mass boreability in TBM tunnel[J]. 2020, 41(5): 1721-1729. DOI： 10.16285/j.rsm.2019.0963.

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、岩体主要结构面与洞轴线的夹角?、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。

Abstract

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

angle between main structural plane of rock mass and axis of the tunnel ?

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 ( 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.

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Related Institution

Faculty of Engineering, China University of Geosciences

State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences

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