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岩石硬性结构面粗糙度量化及其剪切试验研究
引用本文:潘凯,谭洵,吉锋,蔡国军.岩石硬性结构面粗糙度量化及其剪切试验研究[J].水利与建筑工程学报,2013,0(3):41-44.
作者姓名:潘凯  谭洵  吉锋  蔡国军
作者单位:成都理工大学环境与土木工程学院;成都理工大学地质灾害防治与地质环境保护国家重点实验室国家级地质工程试验教学示范中心;
基金项目:地质灾害防治与环境保护国家重点实验室青年人才培养基金资助项目(SKLGP2011z012)
摘    要:在前人研究的基础上,运用网格法,将结构面曲线与特定分度横向网格相叠合,得到曲线网格交点数Nr,通过数理统计和数值模拟,建立了Nr与JRC的关系预测模型,并回归分析建立了Nr-JRC函数公式,进而建立了基于结构面表面二维形态的剪切强度估算公式,进行了剪切试验反演,得出理论计算JRC值与试验获得JRC值接近,从而证明了该理论是可行的。在实际运用中为精确量化JRC提供了一种有效的新方法。更多还原

关 键 词:硬性结构面  表面粗糙度  预测模型  网格法

Research on Quantifying and Shear Test for Rock's Rigid Structure Surface Roughness
PAN Kai,TAN Xun,JI Feng,CAI Guo-jun.Research on Quantifying and Shear Test for Rock's Rigid Structure Surface Roughness[J].Journal of Water Resources Architectural Engineering,2013,0(3):41-44.
Authors:PAN Kai  TAN Xun  JI Feng  CAI Guo-jun
Affiliation:1.College of Environmental & Civil Engineering,Chengdu University of Technology,Chengdu,Sichuan 610059,China2.National Testing and Teaching Domonstration Center of Geological Engineering,State Key Laboratory of Geological Hazard Prevention and Geological Environment Protection,Chengdu University of Technology,Chengdu,Sichuan 610059,China)
Abstract:Based on previous studies,the grid method,that is,overlopping the structural plane curve with specific sub-degree horizontal grid,is used here to obtain the curvilinear grid intersection point value Nr.Then by mathematical statistics and numerical simulation,the statistical relation prediction model of Nr with JRC is establish,and the regression analysis is carried out to establish the Nr-JRC function relation.Thereby,the shear strength estimation formula is set up based on the structure surface with two-dimensional form,and shear test inversion is carried out to derived that the JRC value from theoretical calculation is close to that from test,which could prove that the theory as mentioned above is feasible and provide a new method for accurately measuring and quantifying the structure surface roughness JRC in the practical application.
Keywords:rigid structure surface  surface roughness  prediction model  grid method
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