Role of redundancy in simplified geotechnical reliability-based design – A quantile value method perspective

• We show that existing reliability code calibration methods are not robust for designs with variable redundancy.
• We use effective random dimension (ERD) to quantify the degree of redundancy.
• We develop ways to estimate ERD in standard normal space as well as in physical space.
• We show that the reliability code calibrated with ERD is more robust using examples.

In this study, we show that existing simplified reliability-based design methods, including the partial factor method and the quantile-based method (quantile value method; QVM), are not robust over design scenarios with variable degree of redundancy. This variable degree of redundancy is quite common in geotechnical design. For instance, a pile group has more redundancy than a single pile. Less obviously, a pile embedded in multiple soil layers has more redundancy than one embedded in a single soil layer. Implementing a fixed set of partial factors or a fixed quantile will not produce designs with uniform reliability indices. This paper shows that the degree of redundancy can be effectively quantified by the concept of an “effective random dimension” (ERD), and it proposes a practical method of estimating ERD for reliability-based design. It is shown by numerical examples that by incorporating ERD, the ERD-QVM outperforms the original QVM in achieving a more uniform reliability level across different design scenarios.