Predicting the bearing capacity of pile installed into cohesive soil concerning the spatial variability of SPT data (A case study)

Abstract

Nowadays, in situ tests have played a viable role in geotechnical engineering and construction technology. Besides lab tests conducted on undisturbed soil samples, many different kinds of in-situ tests were used and proved to be more efficient in foundation design such as pressuremeter PMT, cone penetration test CPT, standard SPT, etc. Among them, a standard penetration test (SPT for short) is easy to carry out at the site. For decades, it has proved reliable to sandy soil, but many viewpoints and opinions argued that the test was not appropriately applicable to cohesive soil because of scattered and dispersed data of SPT blow counts through different layers. This paper firstly studies how reliable the SPT data can predict the physical and mechanical properties; secondly, the soil strength is determined in terms of corrected N-SPT values, and finally the bearing capacity of a pile penetrating cohesion soil. By analyzing data from 40 boreholes located in 18 projects in Ho Chi Minh City, South VietNam, coefficients of determination between SPT numbers and physical and mechanical properties of different soil kinds are not the same: R2 = 0.623 for sand, =0.363 for sandy clay and =0.189 for clay. The spatial variability of soil properties is taken into account by calculating the scale of fluctuation θ=4.65m beside the statistically-based data in horizontal directions. Finally, the results from two theoretical approaches of predicting pile bearing capacity were compared to those of finite element program Plaxis 3D and static load test at site. Correlation between the capacity computed by using corrected N-values instead of soil strength and results of static load test has proved to be well suitable in evaluating the bearing capacity of driven and jack-in piles, particularly installing in the cohesive soil using the SPT blows.

Keywords

• standard penetration test (spt)
• cohesive soil
• spatial variability
• variance reduction factor
• the scale of fluctuation
• bearing capacity of pile