Statistical characteristics of rock mass deformation modulus and weight analysis of parameters based on Monte Carlo method

被引：0

作者：

Yang Z. ^{[1
]}

Qiao C.-S. ^{[1
]}

Chen S. ^{[1
]}

机构：

[1] School of Civil Engineering, Beijing Jiaotong University, Beijing

来源：

Yantu Lixue/Rock and Soil Mechanics | 2020年 / 41卷

基金：

中国国家自然科学基金;

关键词：

Empirical method; Monte Carlo; Rock deformation modulus; Statistical distribution; Weight analysis;

D O I：

10.16285/j.rsm.2019.1196

中图分类号：

学科分类号：

摘要：

The deformation modulus of rock mass is often estimated by empirical formulas in rock mass engineering. There are many empirical formulas in rock mass classification system, but few studies are found on the statistical characteristics of the results using different empirical estimation formulas and the weight analysis of independent variables. In this paper, the Monte Carlo method is used to analyze the statistical distribution of the deformation modulus estimated by different emperical formula and the weight of the independent variables based on GSI system. Besides, impacts of different disturbance factors are discussed. The results show that the disturbance factors play different roles in the statistical distribution modes of rock mass deformation modulus. The disturbance factor has the greatest impact on the statistical models of rock mass deformation modulus obtained by Hoek formula and the high quality rock mass is less affected compared with that of poor quality rock mass. © 2020, Science Press. All right reserved.

引用

页码：271 / 278and336

共 22 条

[1]

LIU Chao, TANG Xi-bin, DENG Dong-mei, Et al., Prediction of rock mass deformation modulus based on support vector machine regression, Geological Science and Technology Information, 37, 5, pp. 275-280, (2008)

[2]

BIENIAWSKI Z T., Determining rock mass deformability: Experience from case histories, International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 15, 5, pp. 237-247, (1978)

[3]

SERAFIM J L, PEREIRA J P., Consideration of the geomechanical classification of Bieniawski, Proceeding of International Symposium on Engineering Geology and Underground Consteuction, 1, 2, pp. 33-44, (1983)

[4]

MITRI H S, EDRISSI R, HENNING J., Finite element modeling of cable bolted stopes in hard rock ground mines, Presented at the SME Annual Meeting, pp. 94-116, (1994)

[5]

BARTON N., Some new Q-value correlations to assist in site characterisation and tunnel design, International Journal of Rock Mechanics & Mining Sciences, 39, 2, pp. 185-216, (2002)

[6]

SONMEZ H, GOKCEOGLUC, ULUSAY R., Indirect determination of the modulus of deformation of rock masses based on the GSI system, International Journal of Rock Mechanics & Mining Sciences, 41, 5, pp. 849-857, (2004)

[7]

CARVALHO J., Estimation of rock mass modulus, (2004)

[8]

HOEK E, DIEDERICHS M S., Empirical estimation of rock mass modulus, International Journal of Rock Mechanics and Mining Sciences, 43, 2, pp. 203-215, (2006)

[9]

GB/T 50218-2014 Engineering rock mass classification standard, (2014)

[10]

ZHANG Zhan-rong, YANG Yan-shuang, ZHAO Xin-yi, Et al., Empirical method research on rock mass deformation parameter determination, Journal of Rock Mechanics and Engineering, 35, pp. 3195-3202, (2016)

← 1 2 3 →