Site characterization with multiple measurement profiles from different tests: A Bayesian approach

Uncertainty studies and reliability assessments have become important topics/areas in geotechnical engineering, and different site-characterization approaches have been developed in an attempt to incorporate the sources of uncertainty into the analysis. Focusing on a target problem with multiple measurement profiles (with depth) from different testing procedures, this paper presents a site-characterization modeling to estimate the probability distribution of soil properties for a given site, considering the uncertainties from site-specific test-data scatter and from inherent soil variability in space (or in horizontal direction). More specifically, the modeling adopts the Bayesian approach to integrate the multiple sources of data, by using one as prior and the other as the so-called likelihood function. In addition to the algorithms, the approach was applied to a site with two sources of undrained shear strength from laboratory triaxial tests and in-situ plate bearing tests, and suggested a series of characteristic values for undrained shear strength for the site, corresponding to a given depth of interest, and to a given level of inherent soil variability in the horizontal direction.