Application of numerical modeling and genetic programming to estimate rock mass modulus of deformation

被引：0

作者：

Ebrahim Ghotbi Ravandi ^{[1
]}

Reza Rahmannejad ^{[2
]}

Amir Ehsan Feili Monfared ^{[3
]}

Esmaeil Ghotbi Ravandi ^{[4
]}

机构：

[1] Mineral Industries Research Center,Shahid Bahonar University of Kerman

[2] Mining Engineering Department,Shahid Bahonar University of Kerman

[3] Chemical Engineering Department,Shahid Bahonar University of Kerman

[4] Civil Engineering Department,Shahid Bahonar University of Kerman

来源：

International Journal of Mining Science and Technology | 2013年 / 23卷 / 05期

关键词：

Modulus of deformation(Em); Displacement; Numerical modeling; Genetic programming(GP); Back analysis;

D O I：

暂无

中图分类号：

TU458 [室内岩石试验];

学科分类号：

0801 ; 080104 ; 0815 ;

摘要：

Estimation of the rock mass modulus of deformation(Em)is one of the most important design parameters in designing many structures in and on rock.This parameter can be obtained by in situ tests,empirical relations between deformation modulus and rock mass classifcation,and estimating from laboratory tests results.In this paper,a back analysis calculation is performed to present an equation for estimation of the rock mass modulus of deformation using genetic programming(GP)and numerical modeling.A database of 40,960 datasets,including vertical stress(rz),horizontal to vertical stresses ratio(k),Poisson’s ratio(m),radius of circular tunnel(r)and wall displacement of circular tunnel on the horizontal diameter(d)for input parameters and modulus of deformation for output,was established.The selected parameters are easy to determine and rock mass modulus of deformation can be obtained from instrumentation data of any size circular galleries.The resulting RMSE of 0.86 and correlation coeffcient of97%of the proposed equation demonstrated the capability of the computer program(CP)generated by GP.

引用

页码：733 / 737

页数：5

共 18 条

[1]

Evaluating the strength of intact rocks through genetic programming[J] . Mojtaba Asadi,Mehdi Eftekhari,Mohammad Hossein Bagheripour.Applied Soft Computing Journal . 2010 (2)

[2] Genetic programming approach for estimating the deformation modulus of rock mass using sensitivity analysis by neural network [J].

Beiki, Morteza ;

Bashari, Ali ;

Majdi, Abbas .

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES, 2010, 47 (07) :1091-1103

[3]

Numerical simulation of rock deformation for support design in tunnel intersection area[J] . F.Y. Hsiao,C.L. Wang,J.C. Chern.Tunnelling and Underground Space Technology incorporating Trenchless Technology Research . 2008 (1)

[4]

Prediction of compressive and tensile strength of limestone via genetic programming[J] . Expert Systems With Applications . 2007 (1)

[5]

Numerical evaluation of the effective elastic moduli of rocks[J] . S.G. Mogilevskaya,J. Wang,S.L. Crouch.International Journal of Rock Mechanics and Mining Sciences . 2006 (3)

[6]

Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining[J] . Shuhua Zhai,Qian Gao,Jianguo Song.Journal of China University of Geosciences . 2006 (4)

[7]

Estimation of rock modulus: For intact rocks with an artificial neural network and for rock masses with a new empirical equation[J] . H. Sonmez,C. Gokceoglu,H.A. Nefeslioglu,A. Kayabasi.International Journal of Rock Mechanics and Mining Sciences . 2005 (2)

[8]

A displacement-based back-analysis method for rock mass modulus and horizontal in situ stress in tunneling – Illustrated with a case study[J] . L.Q. Zhang,Z.Q. Yue,Z.F. Yang,J.X. Qi,F.C. Liu.Tunnelling and Underground Space Technology incorporating Trenchless Technology Research . 2005 (6)

[9] Development of a back analysis algorithm using FLAC [J].

Jeon, YS ;

Yang, HS .

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES, 2004, 41 (03) :441-442

[10]

Numerical back analysis for estimation of soil parameters in the Resalat Tunnel project[J] . A. Fakhimi,D. Salehi,N. Mojtabai.Tunnelling and Underground Space Technology incorporating Trenchless Technology Research . 2003 (1)

← 1 2 →