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Published in: Bulletin of Engineering Geology and the Environment 5/2019

23-06-2018 | Original Paper

Predicting the Young’s Modulus of granites using the Bayesian model selection approach

Authors: Lingqiang Yang, Xianda Feng, Yang Sun

Published in: Bulletin of Engineering Geology and the Environment | Issue 5/2019

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Abstract

The value of Young’s modulus (E) is critical to the design of geotechnical engineering projects. Although E can be directly measured by laboratory tests, high-quality core samples and expensive sophisticated instruments are required. Therefore, a method for the indirect estimation of E is an appealing possibility. This study develops a model for predicting the E of intact granite based on the Bayesian model class selection approach. An experimental database of granite rock properties that includes the value E, point load strength index (Is50), L-type Schmidt hammer rebound number (RL), P-wave velocity (Vp), porosity (η), and uniaxial compressive strength, is applied to develop the most suitable model. The proposed model is then compared to existing approaches. The results indicate that the proposed models provide satisfactory predictions and good practicality in application.

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Metadata
Title
Predicting the Young’s Modulus of granites using the Bayesian model selection approach
Authors
Lingqiang Yang
Xianda Feng
Yang Sun
Publication date
23-06-2018
Publisher
Springer Berlin Heidelberg
Published in
Bulletin of Engineering Geology and the Environment / Issue 5/2019
Print ISSN: 1435-9529
Electronic ISSN: 1435-9537
DOI
https://doi.org/10.1007/s10064-018-1326-2

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