Probabilistic assignment of effective friction angles of sands and silty sands FROM CPT using quantile regression

ABSTRACT

This paper develops new probabilistic correlations for assigning design values of effective friction angle (${\phi }^{\mathrm{\prime }}$) of clean to silty sands from cone penetration test (CPT) data. New transformation models are proposed using a high-quality database of undisturbed sands. The sand samples have been collected using special methods (freezing, gel samplers, Mazier tube) and tested in the laboratory triaxial compression mode. The CPT soundings have been performed using electronic piezocone penetrometers ($q_t$, $f_s$, $u_2$) advanced at the standard rate of 20 mm/s. Two CPT normalisation schemes ($q_{t1}$, $Q_{tn}$) are investigated. Correlations are obtained through quantile regression, a statistical method which allows the assignment of regression functions which are directly and quantitatively associated with probabilities of exceedance. The derived relationships allow the geoengineer to estimate the effective stress friction angle at any desired level of conservatism. The paper concludes by demonstrating how to apply the results practically in geotechnical design.

KEYWORDS:

• Probabilistic modelling
• statistical methods
• effective friction angle
• quantile regression
• cone penetration testing

Acknowledgments

The first author acknowledges the work of Dr. Marco Zei in coding the routines for the implementation of quantile regression. The second author appreciates the support of ConeTec Group of British Columbia towards research on in-situ testing interpretation.

Disclosure statement

No potential conflict of interest was reported by the authors.