Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …

This paper reviews the mathematical foundation of the importance sampling technique and
discusses two general classes of methods to construct the importance sampling density (or …

The accurate estimations of the failure probability with low-computational burden play a vital
role in structural reliability analyses. Due to high-calculation cost and time-consuming Monte …

Metaheuristic algorithms have been widely concerned by scholars because of their global
optimization ability that does not depend on gradient information. In this study, Water Cycle …

Computing the sensitivity vector in the traditional first order reliability method may provide
inaccurate reliability outcomes for discrete performance functions and inefficient …

For structural reliability analysis with low failure probability, traditional simulation methods
are time consuming approaches, which is a great challenge for estimating the failure …

This article introduces a simple and effective adaptive surrogate model to structural reliability
analysis using deep neural network (DNN). In this paradigm, initial design of experiments …

This paper proposes a system active learning Kriging (SALK) method to handle system
reliability-based design optimization (SRBDO) problems, where responses of all constraints …

The reliability analysis of structural systems with multiple failure modes and mixed variables
is a critical problem because of complex nonlinear correlations among failure modes (or …

Abstract Design of experiment and active learning strategy are vital for the surrogate-based
reliability analysis. However, the existing sampling and modeling methods usually ignore …