A time-dependent reliability analysis method based on multi-level meta-models for problems involving interval variables

This paper proposes a new time-dependent reliability analysis method based on a two-level meta-models technique for problems with interval variables, through which the upper and lower bounds of reliability indexes of structures within a given design lifetime period can be obtained efficiently. Firstly, the time parameter, interval and stochastic process parameters in the performance function are transformed into the corresponding random variables. Secondly, the polynomial chaos expansion (PCE) approach is adopted for using an approximate polynomial expression to accurately surrogate the complex original performance function. Thirdly, the Kriging meta-model of time-dependent reliability index about the interval variables is constructed based on the approximate expression, and the upper and lower bounds of the reliability index are calculated with the efficient global optimization (EGO) method. Finally, the effectiveness of the proposed method is verified by investigating three numerical examples.

Automated summary

This paper proposes a new time-dependent reliability analysis method based on a two-level meta-models technique for problems with interval variables, to efficiently obtain upper and lower bounds of reliability indexes of structures within a given design lifetime period. The method includes steps such as parameter transformation, polynomial chaos expansion, and meta-model construction, and its effectiveness is verified through three numerical examples.