Reliability analysis of piles in spatially varying soils considering multiple failure modes |
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| Institution: | 1. K.N. Toosi University of Technology, Department of Civil Engineering, Tehran, Iran;2. Earthquake Engineering Research Facility, Department of Civil Engineering, The University of British Columbia, Vancouver, BC V6T-1Z4, Canada;1. Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Department of Geotechnical Engineering, Tongji University, Siping Road 1239, Shanghai 200092, China;2. Glenn Department of Civil Engineering, Clemson University, Clemson, SC 29634, USA |
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| Abstract: | In most limit state design codes, the serviceability limit checks for drilled shafts still use deterministic approaches. Moreover, different limit states are usually considered separately. This paper develops a probabilistic framework to assess the serviceability performance with the consideration of soil spatial variability in reliability analysis. Specifically, the performance of a drilled shaft is defined in terms of the vertical settlement, lateral deflection, and angular distortion at the top of the shaft, corresponding to three limit states in the reliability analysis. Failure is defined as the event that the displacements exceed the corresponding tolerable displacements. The spatial variability of soil properties is considered using random field modeling. To illustrate the proposed framework, this study assesses the reliability of each limit state and the system reliability of a numerical example of a drilled shaft. The results show the system reliability should be considered for the serviceability performance. The importance measures of the random variables indicate that the external loads, the performance criteria, the model errors of load transfer curves and soil strength parameter are the most important factors in reliability analysis. Moreover, it is shown that the correlation length and coefficient of variation of soil strength can exert significant impacts on the calculated failure probability. |
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| Keywords: | Piles Spatial variability Reliability Monte Carlo method Importance measure |
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