The kriging-based adaptive structural reliability analysis method has become widely used,
and various learning functions have been proposed. In this study, a fast convergence …

In structural reliability analysis, Kriging-based adaptive analysis approaches considerably
improve the analysis's efficiency by utilizing proper learning strategies. However, the time …

First-passage probability estimation of high-dimensional nonlinear stochastic dynamic
systems is a significant task to be solved in many science and engineering fields, but …

In using the Kriging-based adaptive structure reliability analysis methods, the key is to select
the appropriate method of adding samples adaptively. In this study, a new parallel adaptive …

One of the important challenges in structural reliability is using only a few function calls to
obtain an accurate failure probability. To solve this problem, a combination of the adaptive …

This paper is devoted to the research on applying the deep learning method to nonlinear
structural post-disaster damage state assessment. Transformer and Informer networks with a …

In engineering practice, the evaluation of seismic reliability of high-rise reinforced concrete
structure relies on the probabilistic modelling of material properties. However, the measured …

The approximation of the probability density function (PDF) of the performance function,
especially for the tail distribution, is of paramount importance in structural reliability analysis …

Kriging-based adaptive structural reliability analysis methods can replace the structural
performance function and perform reliability analysis accurately and efficiently by using …

Polynomial chaos expansion (PCE) is widely used to build a surrogate meta-model of the
performance function for structural reliability analysis. The number of terms to be determined …