A rational, probabilistic method for the development of geotechnical load and resistance factor design
This study presents a framework for the development of load and resistance factor design for geotechnical engineering based on reliability analysis. This framework is demonstrated as a tool to address different problems facing geotechnical engineering. The present methodology implements the existing structural engineering practice of resistance reduction factor calibration to a target reliability index. The crucial inputs to these calibration calculations are probability density functions that represent the uncertainty in design parameters and correlations. The uncertainties present in design are a combination of uncertainties introduced at every stage of the testing, design, and construction process, a concept known as error propagation. In contrast to previous studies, a more direct, fundamental approach to error propagation evaluation was developed. This approach allows each source of uncertainty to be identified and objectively evaluated. After applying the proposed framework to different foundation design methods, three specific applications were successfully demonstrated. (1) The framework is applicable to addressing issues of acceptable margins of safety in design. (2) The framework is applicable to establishing consistent guidelines for selecting design values of geotechnical parameters. (3) The framework is applicable to assessing the economic value of geotechnical testing programs. In general, the method produces results that confirm intuition regarding these decisions. In contrast to current practice, however, the method allows objective, quantitative assessments, facilitating communication regarding these three key issues. Therefore, the proposed framework offers the opportunity for the rational development of design guidelines. ^
Major Professor: Rodrigo Salgado, Purdue University.