HAO Jie, SHI Ke-bin, CHEN Gong-min, et al. Grey relation analysis of deformation sensitivity based on probability distribution models of surrounding rock mechanical parameters[J]. 2015, 36(3): 854-860.
DOI:
HAO Jie, SHI Ke-bin, CHEN Gong-min, et al. Grey relation analysis of deformation sensitivity based on probability distribution models of surrounding rock mechanical parameters[J]. 2015, 36(3): 854-860.DOI: 10.16285/j.rsm.2015.03.032.
Grey relation analysis of deformation sensitivity based on probability distribution models of surrounding rock mechanical parameters
This paper provides the reliable theoretic guidance for parameters selection of surrounding rock stability analysis in Bulungl-Gongur hydropower station underground cavern. The grey relation analysis of deformation sensitivity method is proposed based on probability distribution model of surrounding rock mechanical parameters
while the spatial variability of parameters and the shortcomings of conventional sensitivity analysis are considered. Three-dimensional discrete element calculation program is used. This method regards density
elastic modulus
Poisson’s ratio
cohesion
internal friction angle and joints internal friction angle as factor array. The vault crown settlement is specified as the target array. The influence of each factor changing in defined domain on the vault crown settlement is analyzed. The results show that the density is the most sensitive influential factor among all the factors. The subordinate sensitive influential factors are the elastic modulus
cohesion and Poisson’s ratio. The internal friction angle and joints internal friction angle are the minimum sensitive influential factors. Finally
comparison of results between conventional sensitivity analysis and the proposed method is made. The results indicate that except density
internal friction angle and joints internal friction angle are consistent
the sensitivity of the rest parameters are not consistent. Therefore
this method could evaluate those parameters more accurately and reasonably based on considering the probability distribution of rock mechanical parameters.