An efficient sequential Kriging model for structure safety lifetime analysis considering uncertain degradation

Abstract

Safety lifetime analysis performs a crucial role in ensuring structural safety in service and developing effective maintenance strategies, which also places higher demands on calculation. However, existing safety lifetime analysis methods generally suffer from inefficiency, which is more prominent for complex engineering structures. In this paper, a novel sequential single-loop Kriging (SSK) surrogate modeling approach is proposed to calculate the safety lifetime in an efficient and accurate manner. To reduce the computational cost, a single-loop safety lifetime analysis framework is proposed. In this framework, there is no need to accurately calculate the time-dependent failure probability (TDFP) in any sub-time interval. By searching the safety lifetime in the process of time-dependent reliability analysis (TRA) and dynamically adjusting the interest time interval, the safety lifetime can be quickly determined by constructing only one Kriging model. To maximize the utilization of sample information, SSK employs a modified learning function that allows most of the training points to be added before the safety lifetime. For accuracy, a convergence criterion that includes two Kriging models is proposed. Mathematical engineering examples are used to illustrate the accuracy and efficiency of SSK. The proposed method offers a promising approach for efficient safety lifetime analysis of engineering problems.