Random field characterization of uniaxial compressive strength and elastic modulus for intact rocks

Rock properties exhibit spatial variabilities due to complex geological processes such as sedimentation, metamorphism, weathering, and tectogenesis. Although recognized as an important factor controlling the safety of geotechnical structures in rock engineering, the spatial variability of rock prope...

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Bibliographic Details
Main Authors: Liu, Hua-Xin, Qi, Xiao-Hui
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/87272
http://hdl.handle.net/10220/44389
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Institution: Nanyang Technological University
Language: English
Description
Summary:Rock properties exhibit spatial variabilities due to complex geological processes such as sedimentation, metamorphism, weathering, and tectogenesis. Although recognized as an important factor controlling the safety of geotechnical structures in rock engineering, the spatial variability of rock properties is rarely quantified. Hence, this study characterizes the autocorrelation structures and scales of fluctuation of two important parameters of intact rocks, i.e. uniaxial compressive strength (UCS) and elastic modulus (EM). UCS and EM data for sedimentary and igneous rock are collected. The autocorrelation structures are selected using a Bayesian model class selection approach and the scales of fluctuation for these two parameters are estimated using a Bayesian updating method. The results show that the autocorrelation structures for UCS and EM could be best described by a single exponential autocorrelation function. The scales of fluctuation for UCS and EM respectively range from 0.3 m to 8.0 m and from 0.3 m to 8.4 m. These results serve as guidelines for selecting proper autocorrelation functions and autocorrelation distances for rock properties in reliability analysis and could also be used as prior information for quantifying the spatial variability of rock properties in a Bayesian framework.