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Statistical Analyses of Model Factors in Reliability-Based Limit-State Design of Drilled Shafts under Axial Loading
Journal article   Peer reviewed

Statistical Analyses of Model Factors in Reliability-Based Limit-State Design of Drilled Shafts under Axial Loading

Chong Tang, Kok-Kwang Phoon and Yit-Jin Chen
Journal of geotechnical and geoenvironmental engineering, Vol.145(9), 04019042
01/09/2019

Abstract

Engineering Engineering, Geological Geology Geosciences, Multidisciplinary Physical Sciences Science & Technology Technology
This study compiles 320 static-load tests to quantify the model factors in reliability-based limit-state design of drilled shafts under axial loading. At ultimate limit-state, the model factor is defined as the ratio of the measured capacity to the calculated capacity. It characterizes the bias in capacity calculation. The measured capacity is interpreted from load test data by the modified Davisson offset limit, and current design methods are utilized to compute the ultimate axial capacity. The load-displacement data are simulated by two-parameter hyperbolic curves. Based on the database, the statistics and probability distributions of the capacity and load-displacement model factors are established. Several copulas are selected for goodness-of-fit tests on the observed correlation of the hyperbolic model factors. The model factor at serviceability the limit-state is then described by two correlated hyperbolic parameters. Finally, the model statistics are applied to implement the LRFD of drilled shafts under axial loading by Monte Carlo simulations. (c) 2019 American Society of Civil Engineers.

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