A new approach to constructing SPT-CPT correlation for sandy soils

ABSTRACT

The traditional approach to developing an SPT-CPT correlation is usually based on regression analysis of the collected data. This paper proposes a new approach that starts with a baseline equation derived from a selected pair of existing transformation models that use SPT and CPT, respectively. This baseline equation, considered a prior knowledge of the intended SPT-CPT correlation, is then calibrated with the collected data to yield the final correlation. In this paper, our focus is to develop the (N₁)_60,cs−q_t1N,cs correlation, where (N₁)_60,cs and q_t1N,cs are the corrected clean sand equivalence of N values and cone tip resistance, respectively. To illustrate the proposed approach, we created a high-quality database from numerous side-by-side SPT-CPT pairs. Three baseline equations for sandy soils are first derived according to the equivalence of liquefaction resistance, friction angle, and relative density, respectively. All three prior equations are then calibrated using the maximum likelihood method based on the adopted database. Finally, the three (N₁)_60,cs−q_t1N,cs correlation models are combined through a weighted average process based on the Bayesian information criterion. The new approach for constructing the SPT-CPT correlation is found on Bayes' theorem, is easy to adapt, and has the potential for developing similar geotechnical correlation.

KEYWORDS:

• Standard penetration test (SPT)
• cone penetration test (CPT)
• correlation
• liquefaction
• friction angle
• relative density

Supplemental material

The SPT-CPT database associated with this article will be made available online.

Acknowledgments

This research was supported by the Ministry of Science and Technology, ROC (Taiwan) through the Shackleton Programme (MOST108-2638-E-008-001-MY2). This financial support is greatly appreciated.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Ministry of Science and Technology, ROC (Taiwan): [Grant Number MOST108-2638-E-008-001-MY2].