Predictive model for uniaxial compressive strength for Grade III granitic rocks from Macao

被引:59
作者
Ng, Iok-Tong [1 ]
Yuen, Ka-Veng [1 ]
Lau, Chi-Hou [1 ]
机构
[1] Univ Macau, Fac Sci & Technol, Dept Civil & Environm Engn, Macau, Peoples R China
关键词
Bayesian analysis; Predictive model; Grade III granites; Uniaxial compressive strength; POINT LOAD; MECHANICAL-PROPERTIES; DEFORMATION MODULUS; BEARING CAPACITY; NEURAL-NETWORKS; SELECTION; FUZZY; INDEX; IDENTIFICATION; VARIABILITY;
D O I
10.1016/j.enggeo.2015.10.008
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
Determination of the uniaxial compressive strength (UCS) of rocks is an important task for rock and geotechnical engineering applications. Direct measurement is expensive, time consuming and even infeasible in some circumstances due to the difficulty in obtaining core samples. Therefore, empirical models are particularly favorable to engineers especially in the preliminary design stage. However, there is a lack of predictive UCS model for granite of weathering Grade III but it is well recognized to be crucial to the design of pile foundations on granitic bedrocks. In this study, a reliable predictive model will be developed under the Bayesian framework. An extensive experimental program was performed in this study to construct a comprehensive database of the measurements of uniaxial compressive strength, point load index, Schmidt rebound hammer value, P-wave velocity, effective porosity, specific gravity and dry density. It has been proven that the proposed model possesses satisfactory predictive performance. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:28 / 37
页数:10
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