DFI Journal - The Journal of the Deep Foundations Institute

Volume 7, Issue 2, January 2013

Papers are only available to members. If you are a member, please click on the "Login" link at the top of the site. You may use your DFI login.

If you are not a member, click here join.

Please click here to complete purchase by clicking on the PDF $25 icon and completing the payment form. The paper will be emailed to you within 48 hours.

Factors Affecting the Reliability of Augered Cast-In-Place Piles in Granular Soil at the Serviceability Limit State (DFI 2013 Young Professor Paper Competition Winner)

Armin W. Stuedlein, Ph.D., P.E. and Seth C. Reddy, E.I.


"Owing to an increasing demand to manage risk and maximize cost-effectiveness, preference for reliability-based design (RBD) over traditional deterministic design procedures has increased for deep foundation elements. In this study, factors affecting the reliability of augered cast-in-place (ACIP) piles under axial compression at the serviceability limit state (SLS) are addressed using a simple probabilistic hyperbolic model and a database of static loading tests conducted on ACIP piles in cohesionless soils. The aleatory and model uncertainty in a selected two-parameter load-displacement model is statistically characterized for use in reliability simulations. Reliability simulations incorporating the correlated bivariate model parameter distribution were generated using a statistical translational model and various parametric and non-parametric correlation coefficients to assess the effect of correlation coefficient type on the reliability simulations. The first-order reliability method (FORM) was used to determine the effect of sample size on the stability and uncertainty of the serviceability limit state reliability index. Sample sizes greater than about 40 provided relatively consistent estimates of the reliability index; however, its uncertainty continued to decrease with increasing sample sizes. A parametric study was conducted in order to determine the variables (i.e. allowable displacement, predicted pile capacity, slenderness ratio) which govern reliability. In general, the uncertainty in the model used to predict pile capacity had a more significant impact on foundation reliability compared to the uncertainty in allowable displacement; this finding illustrates one advantage of having an accurate capacity prediction model. The slenderness ratio had the largest effect on foundation reliability at the SLS, and illustrates the importance for accounting for the pile geometry in reliability assessments."