Safety Lifetime Analysis Using Two-Phase Subset Simulation Combined with Kriging Model

Abstract

The safety lifetime analysis under the required time-dependent failure probability (R-FP) constraint is essential to ensure structure service safety, but existing methods are unaffordable for solving the safety lifetime under a small R-FP constraint. For this issue, a novel method is proposed by combining a two-phase subset simulation with an adaptive kriging model (TP-SS-AK). The innovations of the TP-SS-AK include three aspects. First, it creatively transforms the safety lifetime under a small R-FP constraint into that under a large conditional R-FP constraint by subset simulation, which can greatly improve efficiency because the large conditional R-FP constraint only needs a small candidate sample pool for searching the safety lifetime. Second, by deducing the misclassification probability of the time-dependent structure state in the first phase, the first new learning strategy is established to train the kriging model of the time-dependent performance function and further determine a reasonable lifetime search interval efficiently. Third, by deriving the misclassification probability of the first failure instant, the second new learning strategy is constructed to efficiently update the kriging model in the second phase and further search the safety lifetime. Because the proposed TP-SS-AK combines the advantages of the two-phase subset simulation and two new learning strategies, it is superior to the existing methods in efficiency, and its superiority is verified by the examples.