A new service limit state (SLS) design procedure for drilled shafts is described, which utilizes strength resistance factors calibrated to achieve a target probability of failure. The new procedure can be used for varying values of the target probability of failure, and allows the shaft dimensions, soil strength, variability of soil strength, loads, and allowable settlement to be adjusted freely in the design. The procedure eliminates the need to establish resistance factors for the SLS on a case-by-case basis, which is a current practical issue for load and resistance factor design (LRFD). Sensitivity analyses presented indicate that resistance factors for a broad set of SLS design conditions can be reasonably established considering four parameters: the target probability of failure, normalized load, normalized shaft dimension, and the variability of soil/rock strength. Calibrated resistance factors are presented as a function of these four parameters in the form of resistance factor charts, as well as in the form of analytical equations developed through regression of the rigorously calibrated resistance factors. The proposed resistance factors range from 0.1 to 0.4, primarily because of the significant variability and uncertainty associated with side resistance for drilled shafts in shale.

Reinforced concrete piles installed by impact hammers have been used as a common solution for deep foundations because they are cost effective and require less time for construction. Driven piles are often used in large volumes for infrastructure and industrial projects in rural areas. Unlike other installation methods, installing piles using impact hammers can generate tensile stress during construction, which can result in pile failures. Induced tensile stress occurs when piles are being driven through a hard soil layer to a softer soil layer, and transverse cracks happen when induced tensile stress exceeds the pile tensile strength. This issue is not explicitly stated in most standards; the rare code that mentions this issue is AASHTO 2014. AASHTO 2014 uses correlations between the concrete tensile and compressive strengths to obtain the pile tensile strength. However, data collected from more than 1300 tests on the correlations between the concrete tensile and compressive strengths show that the concrete pile tensile strengths obtained using AASHTO 2014 are significantly conservative. This paper provides an adjustment in the correlation for the tensile strength based on previous data, and it proposes an approach to estimate the tensile strength for concrete-driven piles. A case study of the effects of pile failures on the tensile strength is also presented to verify the approach. The obtained tensile strength from the proposed approach agrees well with the measured field data. For the case study, the pile tensile strength obtained using the proposed approach is 38% and 59% higher than the tensile strength obtained using AASHTO 2014. These quantities are significant but may vary, depending on the compression strength of the concrete used and the pile configurations. The proposed approach better predicts the tensile strength of concrete piles and can lead to cost savings.

The method of incorporating the sources of parameter uncertainty is crucial when conducting probabilistic analysis for service limit state (SLS) design of a deep foundation. This paper describes the method of using Monte Carlo simulation for probabilistic analyses and for calibration of resistance factors of drilled shafts at SLS. The paper presents discussions on the finding of an impossible case, where the different combinations of load, variability of soil strength and target probability of failure made it impossible to calibrate the SLS resistance factors. Resistance factors for drilled shafts in shale are introduced, and were found to be responsive to load levels. The higher load level, the lower the resistance factor. These findings help smooth the transition from allowable stress design to load and resistance factor design for geotechnical engineers.

Side resistance factors and tip resistance factors were calibrated for use in service limit state (SLS) designs of side friction shafts and end bearing shafts in shales. The SLS design procedure utilizes the t-z method and adopts the factored strength approach to account for variability and uncertainty in the design and associated input parameters. The variability and uncertainty considered for calibration of the resistance factors were derived from full-scale load tests performed on drilled shafts embedded in shales in the central United States. Monte-Carlo simulations were used to calibrate the resistance factors. The range for side resistance factors is 0.05–0.2, and the range for tip resistance factors is 0.1–0.5, depending upon shale uniaxial compressive strength coefficient of variation, normalized loads, and probability of failure. Under the same conditions, side resistance factors are smaller than tip resistance factors. The obtained resistance factors are substantially low but reasonably reflect the collective variability and uncertainty presented in the design of drilled shafts in shales.