Abstract

Deterministic optimum designs that are obtained without consideration of uncertainties could lead to unreliable designs, therefore calling for reliability-based design optimization (RBDO). However, it has been reported in literatures that when RBDO involves evaluation of probabilistic constraints it is prohibitively expensive or even diverges for many large-scale applications. Therefore, the hybrid mean value (HMV) method had been proposed by authors for highly efficient and stable RBDO by evaluating the probabilistic constraint effectively. However, even with the HMV method, the RBDO process could be still expensive for large-scale applications or applications where efficient design sensitivity analysis method is unavailable. To alleviate this difficulty, a new RBDO methodology developed integrating the HMV method with a proposed response surface method, which is specifically developed for reliability analysis and optimization. A large-scale example problem is employed to demonstrate the proposed RBDO method.