TY - JOUR
T1 - Quasi-site-specific prediction for deformation modulus of rock mass
AU - Ching, Jianye
AU - Phoon, Kok Kwang
AU - Ho, Yuan Hsun
AU - Weng, Meng-Chia
N1 - Publisher Copyright:
© Canadian Science Publishing. All rights reserved.
PY - 2021/7
Y1 - 2021/7
N2 - A generic rock mass database consisting of nine parameters is compiled from 225 studies. The nine parameters are the deformation modulus, elastic modulus, dynamic modulus, rock quality designation, rock mass rating, Q-system, geological strength index of a rock mass, as well as intact-rock Young’s modulus and intact-rock uniaxial compressive strength. This generic database, labeled as ROCKMass/9/5876, consists of 5876 rock mass cases. The goal of this paper is to examine how an existing transformation model such as deformation modulus versus rock mass rating can be made more unbiased and more precise for a specific site by combining sparse site data with ROCKMass/9/5876 in a manner sensitive to site-specific differences. The outcome is a quasi-site-specific transformation model. Four methods are studied to construct a quasi-site-specific transformation model for the deformation modulus of a rock mass: probabilistic multiple regression (cur-rent state of practice), hybridization method, hierarchical Bayesian model, and similarity method. The results from two case studies in Turkey show that the hierarchical Bayesian model is the most effective.
AB - A generic rock mass database consisting of nine parameters is compiled from 225 studies. The nine parameters are the deformation modulus, elastic modulus, dynamic modulus, rock quality designation, rock mass rating, Q-system, geological strength index of a rock mass, as well as intact-rock Young’s modulus and intact-rock uniaxial compressive strength. This generic database, labeled as ROCKMass/9/5876, consists of 5876 rock mass cases. The goal of this paper is to examine how an existing transformation model such as deformation modulus versus rock mass rating can be made more unbiased and more precise for a specific site by combining sparse site data with ROCKMass/9/5876 in a manner sensitive to site-specific differences. The outcome is a quasi-site-specific transformation model. Four methods are studied to construct a quasi-site-specific transformation model for the deformation modulus of a rock mass: probabilistic multiple regression (cur-rent state of practice), hybridization method, hierarchical Bayesian model, and similarity method. The results from two case studies in Turkey show that the hierarchical Bayesian model is the most effective.
KW - Deformation modulus
KW - Hierarchical Bayesian model
KW - Quasi-site-specific transformation model
KW - ROCKMass/9/5876
KW - Rock mass properties
KW - Site recognition challenge
UR - http://www.scopus.com/inward/record.url?scp=85098585898&partnerID=8YFLogxK
U2 - 10.1139/cgj-2020-0168
DO - 10.1139/cgj-2020-0168
M3 - Article
AN - SCOPUS:85098585898
SN - 0008-3674
VL - 58
SP - 936
EP - 951
JO - Canadian Geotechnical Journal
JF - Canadian Geotechnical Journal
IS - 7
ER -