摘要
为深入探讨岩体物理力学参数对凿碎比功及刀具磨损值的影响,本文以南疆铁路吐库二线,中天山隧道为研究对象,基于隧道掘进机法(TBM),对隧道围岩进行原位及室内实验,获得纵波波速、单轴抗压强度、单轴抗拉强度、静弹性模量、黏聚力等基本力学参数。使用SPSS22软件分别对以上参数与凿碎比功及刀具磨损值进行相关性分析,结果表明其单因素相关性均较弱。而在以凿碎比功及磨损值分别作为因变量,以各物理力学参数为自变量进行多因素回归分析并对数据进行逐步法多项式拟合的条件下,得出两因变量与单轴抗压强度和岩体完整性系数均高度相关。在对拟合模型验证过程中发现,在单轴抗压强度大于100 MPa且岩体完整性系数大于0. 5的条件下,使用该模型具有更高精确度。
This paper explores the effects of rock physical mechanical parameters on the specific chiseling work and attrition value of tunnel boring machine(TBM). It is based on the Zhong Tianshan tunnel of the second line of Nan Jiang railway with TBM. A series of in-situ and laboratory experiments are carried out on the tunnel surrounding rock. The basic mechanical parameters are obtained. They include the longitudinal wave velocity,the uniaxial compressive strength,the uniaxial tensile strength,the static modulus of elasticity,and the cohesive force. Then correlation analysis between the basic mechanical parameters and those of the specific chiseling work and attrition value is carried out using the software SPSS22. The results show that the single factor correlation is weak. On the premise of taking the specific chiseling work and the attrition value as dependent variables respectively and mechanical parameters as the independent variable,we carried out multi-factor regression analysis and polynomial fitting of the data by stepwise method. The results show that the dependent variable is highly correlated with the uniaxial compressive strength and the rock mass integrity coefficient. During the validation of the fitting model,under the condition of uniaxial compressive strength greater than 100 MPa and KVgreater than 0. 5,the use of fitting model has a higher accuracy.
作者
王亚暐
吴光
WANG Yawei;WU Guang(Faculty of Geosciences and Environmental Engineering,Southwest Jiaotong University,Chengdu 610000)
出处
《工程地质学报》
CSCD
北大核心
2019年第6期1216-1226,共11页
Journal of Engineering Geology
基金
南疆铁路吐库二线SK2标中天山隧道围岩耐磨试验(R1754321101010619)资助~~
关键词
隧道掘进机法
围岩力学参数
凿碎比功
磨损值
SPSS22
TBM
Mechanical parameters of surrounding rocks
Specific chiseling work
Attrition value
SPSS22
