Probabilistic classification of soils based on Local Average Subdivision method and CPT data

A random field generator based on Local Average Subdivision (LAS) method is proposed in this study in order to achieve probabilistic soil classification and quantify the uncertainty of the generated most probable geological cross section. CPT data and Robertson’s soil classification chart (1990) are adopted to classify the soil. The sole...

Machine learning for prediction of undrained shear strength from cone penetration test data

The need of shear strength measurements of soil in the design phase of geotechnical engineering is almost indispensable. Many methods have been applied to estimate the shear strength of soil, including various laboratory test, in-situ test and analytical methods. As an in-situ test method, cone penetration test (CPT) is a powerful and cost...

Probabilistic identification of soil stratigraphy using CPT data

The deterministic approach for interpreting CPT soil profiles poses the serious limitation of not taking data uncertainty into account. Therefore, a Bayesian model was developed by Wang et al. (2013) that, for a given CPT profile, determines the most probable number of soil layers and most probable soil layer thicknesses by simulating and...