Structural reliability analysis poses significant challenges in engineering practices, leading
to the development of various state-of-the-art approximation methods. Active learning …

The reliability analysis of complex structures usually involves implicit performance function
and expensive-to-evaluate computational models, which pose a great challenge for the …

The active learning Kriging methodology is widely employed in structural reliability analyses,
but there are disadvantages in existing studies concerning computational efficiency and …

Recently, numerous studies have focused on structural reliability analysis, with the Kriging-
based active learning method being particularly popular. A variety of Kriging-based learning …

The prevalence of highly nonlinear and implicit performance functions in structural reliability
analysis has increased the computational effort significantly. To solve this problem, an …

Recently, numerous studies have focused on structural reliability analysis, 9 with the Kriging-
based active learning method being particularly popular. A variety of 10 Kriging-based …

Even though extensive efforts have been made, structural reliability analysis method with
both efficiency and robustness is still infrequent in engineering especially when time …

The Kriging-based reliability analysis is extensively adopted in engineering structural
reliability analysis for its capacity to achieve accurate failure probability estimation with high …

Active-learning surrogate model–based reliability analysis is widely employed in
engineering structural reliability analysis to alleviate the computational burden of the Monte …

In recent years, the active learning reliability method that combines the Kriging model and
Monte Carlo simulation (AK-MCS) has emerged as a promising approach due to its …