Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review

C Song, R Kawai - Probabilistic Engineering Mechanics, 2023‏ - Elsevier
Monte Carlo methods have attracted constant and even increasing attention in structural
reliability analysis with a wide variety of developments seamlessly presented over decades …

Second-order reliability methods: a review and comparative study

Z Hu, R Mansour, M Olsson, X Du - Structural and multidisciplinary …, 2021‏ - Springer
Second-order reliability methods are commonly used for the computation of reliability,
defined as the probability of satisfying an intended function in the presence of uncertainties …

REIF: a novel active-learning function toward adaptive Kriging surrogate models for structural reliability analysis

X Zhang, L Wang, JD Sørensen - Reliability Engineering & System Safety, 2019‏ - Elsevier
Structural reliability analysis is typically evaluated based on a multivariate function that
describes underlying failure mechanisms of a structural system. It is necessary for a …

A single-loop kriging surrogate modeling for time-dependent reliability analysis

Z Hu, S Mahadevan - Journal of Mechanical Design, 2016‏ - asmedigitalcollection.asme.org
Current surrogate modeling methods for time-dependent reliability analysis implement a
double-loop procedure, with the computation of extreme value response in the outer loop …

AK-MCSi: A Kriging-based method to deal with small failure probabilities and time-consuming models

N Lelièvre, P Beaurepaire, C Mattrand, N Gayton - Structural Safety, 2018‏ - Elsevier
Reliability analyses still remain challenging today for many applications. First, assessing
small failure probabilities is tedious because of the very large number of calculations …

Time-dependent reliability analysis through response surface method

D Zhang, X Han, C Jiang, J Liu… - Journal of …, 2017‏ - asmedigitalcollection.asme.org
In time-dependent reliability analysis, the first-passage method has been extensively used to
evaluate structural reliability under time-variant service circumstances. To avoid computing …

A stochastic process discretization method combing active learning Kriging model for efficient time-variant reliability analysis

D Zhang, P Zhou, C Jiang, M Yang, X Han… - Computer Methods in …, 2021‏ - Elsevier
Time-variant reliability analysis (TRA) has attracted tremendous interest for evaluating
product reliability in full life cycle. Discretization of stochastic process is considered one of …
Z Wang, A Shafieezadeh - Structural and Multidisciplinary Optimization, 2019‏ - Springer
The ever-increasing complexity of numerical models and associated computational
demands have challenged classical reliability analysis methods. Surrogate model-based …

[HTML][HTML] Real-time estimation error-guided active learning Kriging method for time-dependent reliability analysis

C Jiang, H Qiu, L Gao, D Wang, Z Yang… - Applied Mathematical …, 2020‏ - Elsevier
Time-dependent reliability analysis using surrogate model has drawn much attention for
avoiding the high computational burden. But the surrogate training strategies of existing …