Transformations and correlations among some parameters of cohesionless soils

Comparing with safety factor method, reliability-based design method can quantify the uncertainty to design geotechnical structure in a more systematical and economical way. In this study, a multivariate probability distribution model for seven parameters of cohesionless soils is constructured based on the SAND/7/2794 database. These seven parameters are: (1)coefficient of uniformity (Cu); (2)mean particle size (D50); (3)relative density (Dr); (4)normalized vertical effective stress (''v/Pa); (5)effective friction angle (ϕ''); (6)corrected CPT cone tip resistance (qt1); (7)corrected SPT-N value [(N1)60]. Consistency is shown that the multivariate probability distribution captures the correlation behaviors in the database among the seven parameters. According to the conditioning concept of Bayesian analysis, the original distributions of the design soil parameters (Dr, ϕ'') serve as prior distributions and can be updated into the posterior distributions by using different multivariate site-specific information. The forms of posterior distributions were summarized into tables so that detailed Bayesian analysis would not be conducted. From the results, the transformation uncertainty of predicted posterior distribution can be effectively reduced as the multivariate site-specific information increases. With smaller uncertainty, reliability-based design can deduce more economical design.