Master of Science in Civil Engineering (MSCE)
Civil and Environmental Engineering
This report presents the reliability-based analysis of the calibration of resistance factors for the Load and Resistance Factor Design (LRFD) of axially loaded drilled shafts. AASHTO’s 2012 LRFD Bridge Design Specifications recommends various resistance factors for the design of deep foundations; however, since these values are not specific to any one region, they are very conservative. For Louisiana or Mississippi, the adoption of such recommended resistance factors could substantially increase foundation sizes. Therefore, it is necessary to develop a database of drilled shaft load tests performed in the regions of Louisiana, Mississippi, and surrounding states with similar soil conditions. Sixty-nine drilled shaft load tests were collected from the Louisiana and Mississippi Departments of Transportation to develop this database. The measured nominal resistances of the drilled shafts were determined at various settlement criteria using the provided static load test data, and the predicted resistances were calculated from soil boring data using both the 1999 Federal Highway Administration (FHWA) drilled shaft design method (Brown et al.) and the 2010 FHWA design method (O’Neill and Reese). The performance of each design method is evaluated through statistical analyses of the predicted resistances versus the measured resistances, and FOSM and the Monte Carlo simulation method are utilized to perform the LRFD calibration of the resistance factors for the Strength I Limit State as defined by AASHTO. The calibration performed in this study confirms that the Monte Carlo simulation method is a more accurate and reliable method in determining the resistance factors; it also shows that while the 2010 FHWA drilled shaft design method is a more accurate method, it produces smaller total resistance factors than the 1999 FHWA design method.
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Fortier, Alicia Rae, "Calibration of Resistance Factors Needed in the LRFD Design of Drilled Shafts" (2016). LSU Master's Theses. 3342.