Load Transfer of Drilled Shafts: Modeling and Simulating for Probability Analysis

Modeling and simulating load transfer data is essential when conducting probabilistic analyses for service limit state design of deep foundations. Before the research presented herein, there are no available records of a functional load transfer model or a quantified uncertainty for drilled shafts in shales (cohesive intermediate geomaterials). In addition, there were no methodologies for incorporating and simulating the variability and uncertainties of a load transfer model for probabilistic analyses. Based on a large data collection from full-scaled load testing on drilled shafts in shales, regression analyses were carried out to find the best fit model that reflects data, as well as their variability and uncertainty. Intensive nonlinear regression analyses were performed using constant standard deviation and constant coefficient of variation assumptions. Five different functional models and two approaches (collective and individual) were utilized. Accordingly, two methods to simulate the load transfer data are proposed for Monte Carlo simulation to incorporate the uncertainty of the models in probabilistic analyses. Recommendations were made to use non-weighted least square regression and collective approach of analysis to analyze the load transfer data. For the first time, quantified variability of the load transfer data, as well as the method to simulate the load transfer data, is available for probabilistic analysis for service limit state of drilled shafts in shales.

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  • English

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  • Accession Number: 01685955
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 23 2018 9:08AM