Simplified reliability-based design method for geotechnical structures —modified quantile value method
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Graphical Abstract
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Abstract
Currently, the partial factor design method is recommended by most international design codes as a semi-probability design method. This popularity might be partly because the partial factor design method shares a similar design procedure as that of the conventional allowable-stress-design method and therefore is likely to be accepted by practical geotechnical engineers. However, the partial factor design method might produce significantly biased design schemes especially when the design condition (e.g., statistical and probabilistic distributions of soil properties) is different from that used in the code for partial factor calibrations. The quantile value method (i.e., effective random dimension-quantile value method, ERD-QVM) shares a similar design procedure as the partial factor design method. But it needs to calibrate the relationship between ERD and design parameters, which is tedious and computationally expensive. Consequently, it is not feasible to apply this method when the time schedule of the engineering is tight. This study proposes a simplified reliability-based design method for geotechnical structures, namely modified quantile value method (MQVM). The original ERD-QVM and the quantile first-order second-moment method (QFOSM) are reviewed. Based on the QFOSM, the MQVM is developed. A pile foundation example and a pad footing example are employed to illustrate the performance of the proposed method. It is shown that the proposed method can provide an effective tool for rapid reliability-based designs. The proposed MQVM can avoid the calibration procedure of the relationship between ERD and design parameters and yield rational design schemes. The original ERD-QVM might produce an unsafe design scheme, which poses an enormous threat to geotechnical structures. By contrast, the design scheme of MQVM is relatively conservative. Moreover, the MQVM has a robustness similar to that of ERD-QVM.
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