Abstract
This paper presents new time-dependent concurrent reliability-based design optimization methods for improving the confidence of design results with reduced experimental cost and increased computational efficiency. The sensitive time-dependent design parameters are first selected through the developed functional Analysis of Variance. The sensitive design parameters are then validated by constructing the experimental error function based on experimental data, and the function of the mean between experiments and computer models. The sub-domains are next determined, and the time-dependent concurrent reliability-based design optimization is finally constructed and solved based on the MCS method. A case study is used to illustrate and testify our proposed methods.
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