Quantifying the cross-correlation between effective cohesion and friction angle of soil from limited site-specific data

摘要

The effective cohesion (c') and effective friction angle (phi') of soil are important soil parameters required for evaluating stability and deformation of geotechnical structures. It is well known that there is cross-correlation between c' and phi' of soil and that this cross-correlation affects reliability analysis of geotechnical structures. Ignoring the cross-correlation between c' and phi' may lead to a biased estimation of failure probability. It is therefore important to properly quantify the cross-correlation between c' and phi' of soil for geotechnical analysis and design. However, the c' and phi' data obtained from field and/or laboratory tests for a project are usually limited and insufficient to provide a meaningful joint probability distribution of c' and phi' or quantify their cross-correlation. This poses a significant challenge in engineering practice. To address this challenge, this paper develops a Bayesian approach for characterizing the site-specific joint probability distribution of c' and phi' and quantifying the cross-correlation between c' and phi' from a limited number of c' and phi' data obtained from a project. Under a Bayesian framework, the proposed approach probabilistically integrates the limited site-specific c' and phi' data pairs with prior knowledge, and the integrated knowledge is transformed into a large number of c' and phi' sample pairs using Markov Chain Monte Carlo (MCMC) simulation. Using the generated c' and phi' sample pairs, the correlation coefficient of c' and phi' is estimated, and the marginal and joint distributions of c' and phi' are evaluated. The proposed approach is illustrated and validated using real c' and phi' data pairs obtained from direct shear tests of alluvial fine-grained soils at Paglia River alluvial plain in Central Italy. (C) 2017 The Japanese Geotechnical Society. Production and hosting by Elsevier B.V.