Probabilistic analysis of seasonal influence on the prediction of pile bearing capacity by CPT: A case study

Abstract

In this study, we used a probabilistic approach to evaluate the probability of failure of small diameter bored piles in unsaturated sandy soils. The prediction of the bearing capacity was based on the Cone Penetration Test (CPT). We assessed the seasonal influence by analyzing CPT data from dry and wet seasons. The LCPC and Aoki-Velloso semiempirical methods were deterministically applied, and the Aoki-Velloso method was examined using reliability theory. The first-order reliability method (FORM) was used to evaluate the probability of failure and calculate the reliability index based on random variables obtained from CPT data considering the effect of season when predicting bearing capacity. A total of 8.0 m long bored piles with diameters of 0.25, 0.30, and 0.35 m were used for both deterministic and probabilistic analyses. We also evaluated the influence of load ratio variation on the reliability index and determined the pile length required to reach a target reliability index value. Reliability analyses considering CPT campaigns conducted in different seasons showed the effect of season on the prediction of bearing capacity. For example, an 8.0 m long pile with a 0.30 m diameter and 100 kN vertical load had a probability of failure of 38.7 % in the wet season and 0.01 % in the dry season. The reliability analyses provided insights into the influence of seasonal variability on in situ tests for pile bearing capacity, affecting the design of foundation elements.