摘要
为了解决岩石隧道掘进机可掘性预估不准导致隧道施工工期和成本失控的问题,针对国内外5个TBM法隧道工程267组数据,统计分析了TBM可掘性指标与岩体质量参数的回归关系.统计结果表明:贯入度指数与准岩体单轴抗压强度的关系建议采用线性回归关系,岩体基本质量指标与准岩体单轴抗压强度呈对数函数关系,贯入度指数与岩体基本质量指标呈二次函数关系.基于岩体基本指标、准岩体单轴抗压强度、TBM贯入度指数三个指标,建立了不同级别围岩TBM可掘性评价方法,并给出了不同级别围岩条件下TBM掘进参数的控制策略.研究结果可指导不同围岩条件下TBM掘进参数调控和高效掘进.
In order to solve the problem of tunnel construction period and cost out of control caused by inaccurate prediction of rock tunnel boring machine boreability,the regression relationship between TBM boring indexes and rock mass quality parameters is statistically analyzed based on 267 sets of data from 5 TBM tunnel projects at home and abroad.The statistical results show that the relationship between the penetration index and the uniaxial compressive strength of the quasi-rock mass is suggested to be linear regression.The relationship between the basic quality index of the rock mass and the uniaxial compressive strength of the quasi-rock mass is logarithmic function,and the relationship between the penetration index and the basic quality index of the rock mass is quadratic function.Based on the three indexes of basic index of rock mass,uniaxial compressive strength of quasi-rock mass and penetration index of TBM,the evaluation method of TBM boreability for different grades of surrounding rock is established,and the control strategy of TBM parameters under different grades of surrounding rock is given.The research results can guide the control of TBM tunneling parameter and efficient tunneling under different surrounding rock conditions.
作者
温时雨
杨延栋
王天一
卢高明
许自文
WEN Shiyu;YANG Yandong;WANG Tianyi;LU Gaoming;XU Ziwen(China Railway Development and Investment Group Co.Ltd.,Kunming 650200,China;State Key Laboratory of Shield Machine and Boring Technology,Zhengzhou 450001,China;China Railway Tunnel Bureau Group Co.Ltd.,Guangzhou 511458,China;North China University of Water Resources and Electric Power,Zhengzhou 450046,China)
出处
《河南科学》
2023年第1期18-23,共6页
Henan Science
基金
中国中铁科研开发计划(2020-重大专项-04)
国家重点研发计划(2020YFB2006803)。
关键词
可掘性
评价方法
预测模型
隧道掘进机(TBM)
回归分析
boreability
evaluation method
predictive model
tunnel boring machine(TBM)
regression analysis
