Prediction of Shear Wave Velocity in Fine-grained Soils From Cone Penetration Test Data: Toward a Global Approach

Abstract

Shear wave velocity ([Formula: see text]) is often used for the calculation of the shear modulus to combat sampling issues in clays and minimize the cost of laboratory testing. Several studies reported correlations between [Formula: see text] and direct and indirect measurements of the cone penetration test (CPT), yet those proposed for fine-grained formations are generally of a local nature. This study sets out to propose a global approach for the estimation of [Formula: see text] for these soils. Seven regressions were developed using a total of 632 CPT data measurements collected from 55 different sites in 12 countries. The correlations utilizing the tip resistance and depth statistically outperform those using other CPT data. A total of 165 CPT points—collected from the state of New Jersey, USA, and Mexico City, Mexico—were used for verification. It is instrumental to analyze CPT data before building global correlations for gauging applicability and understanding limitations. The adopted approach paves the way for more methodical and rigorous global regressions.

Enhancing Pavement Sustainability: Prediction of the Pavement Condition Index in Arid Urban Climates Using the International Roughness Index

“…MAE is usually a good indicator of bias; however, it cannot tell the direction of the bias, nor does it come with a cap (upper limit). For that reason, these error norms are deemed insufficient for holistic error analysis [41]. The coefficient of determination (R 2 ) is used to measure the proportion of variance in the dependent variable.…”

“…where PCI m is measured PCI, and PCI p is predicted PCI. Model evaluation is instrumental in gauging its utility, which requires error estimation [41]. In addition to the use of R 2 for developed regressions, bias (B) and index of agreement (I a ) can provide more insight into error distribution.…”