Reliability-based structural optimization using improved two-point adaptive nonlinear approximations
Finite Elements in Analysis and Design
An outer approximation approach to reliability-based optimal design of structures
Journal of Optimization Theory and Applications
A survey on approaches for reliability-based optimization
Structural and Multidisciplinary Optimization
A local adaptive sampling method for reliability-based design optimization using Kriging model
Structural and Multidisciplinary Optimization
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The application of reliability-based design optimization (RBDO) is hindered by the unbearable computational cost in the structure reliability evaluating process. This study proposes an optimal shifting vector (OSV) approach to enhance the efficiency of RBDO. In OSV, the idea of using an optimal shifting vector in the decoupled method and the notation of conducting reliability analysis in the super-sphere design space are proposed. The shifted limit state function, instead of the specific performance function, is used to identify the inverse most probable point (IMPP) and derive the optimal shifting vector for accelerating the optimization process. The super-sphere design space is applied to reduce the number of constraints and design variables for the novel reliability analysis model. OSV is very efficient for highly nonlinear problems, especially when the contour lines of the performance functions vary widely. The computation capability of the proposed method is demonstrated and compared to existing RBDO methods using four mathematical and engineering examples. The comparison results show that the proposed OSV approach is very efficient.