Probabilistic analysis and resistance factor calibration for deep foundation design using Monte Carlo simulation

Abstract

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.

Assessment of the Probability of Exceeding the Limiting Deformations of a Building Foundation

“…The Monte Carlo method is also widely used in geotechnical engineering when considering completely different problems ( Fenton andGriffiths, 2002, 2003;Chalermyanont and Benson 2004;Vu, 2018;Pereia, 2011;Misra, 2009;Roberts, 2007, etc.). Fishman (1995) and Harr (1996) decided that since no closedform probabilistic solutions could be obtained from the elastic settlement equation, only a Monte Carlo simulation method seems to be possible.…”