LAUSR

The problems of reliability-based design optimization (RBDO) can generally be solved by double-loop methods, single-loop methods or decoupled methods. The sequence optimization and reliability assessment (SORA) method is a widely used decoupled method due to its good efficiency and stability. However, most research on SORA is the most probable point (MPP) based, which may cause the unavoidable error or even fail in convergence, especially for the problems with high nonlinearity, multiple MPPs, and nonnormally distributed variables. This paper presents a new decoupled method based on quantile instead of MPP to overcome the intrinsic shortcomings of MPP-based methods. In comparison with SORA which decouples RBDO in the design space, the proposed method decouples RBDO in the probability space. The quantile is obtained by sampling methods with the Kriging model, in which a sample updating strategy is utilized by choosing the updating samples in the region significant for solving the RBDO problem. The proposed method is compared with SORA and the performance measure approach (PMA) using several examples, and the results show that the proposed method can solve the RBDO problems efficiently and accurately with high nonlinearity, multiple MPPs, or high dimensions.