JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2019, Vol. 36 ›› Issue (8): 90-96.DOI: 10.11988/ckyyb.20180119

• ROCK-SOIL ENGINEERING • Previous Articles     Next Articles

Determining Mechanical Parameters of Engineering Rock Mass Based on Stochastic-Associative Spatial Interpolation Method

HU Qi-jun1,YU Jun-yao1, LIU Ming2, TANG Wei1, CAI Qi-jie3   

  1. 1.School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China;
    2.Bureau of Housing and Urban-Rural Development of Luxian County, Luzhou 646000, China;
    3.School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031,China
  • Received:2018-02-01 Revised:2018-05-03 Online:2019-08-01 Published:2019-08-15

Abstract: The stochastic and associative feature of mechanical parameters of rock mass is an objective factor that affect the determination of mechanical parameters of engineering rock mass. In line with geological statistic theory, a stochastic-associative spatial interpolation method is proposed for the mechanical parameters of engineering rock mass.The stochasticity of mechanical parameters is described by replacing the parent moment with the sample moment in the condition that the probability distribution is unknown; and the associativity between sample points, sample points and interpolation point is quantified by the variation function. Kriging’s method is used to interpolate the mechanical parameters of engineering rock mass on site.The spatial distribution model of mechanical parameters of engineering rock mass with unknown probability distribution is established and verified through an engineering case.Moreover, the dependency of this method on sample number is expounded through comparative study with different effective sample numbers. With the increase of effective sample number, the relative error between model estimation and test result reduces. In the engineering case study, the relative errors between model estimations and test results of mechanical parameters of three samples are 4.2, 4.4, and 5.3, respectively. In addition, the application scope of the present method and corresponding measures for other situations are also discussed for further research.

Key words: engineering rock mass, mechanical parameters, stochastic-associative spatial interpolation, probability distribution model, variogram, geostatistics

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