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Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review
Monte Carlo methods have attracted constant and even increasing attention in structural
reliability analysis with a wide variety of developments seamlessly presented over decades …
reliability analysis with a wide variety of developments seamlessly presented over decades …
Second-order reliability methods: a review and comparative study
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 …
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
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 …
describes underlying failure mechanisms of a structural system. It is necessary for a …
A single-loop kriging surrogate modeling for time-dependent reliability analysis
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 …
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
Reliability analyses still remain challenging today for many applications. First, assessing
small failure probabilities is tedious because of the very large number of calculations …
small failure probabilities is tedious because of the very large number of calculations …
Time-dependent reliability analysis through response surface method
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 …
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
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 …
product reliability in full life cycle. Discretization of stochastic process is considered one of …
The ever-increasing complexity of numerical models and associated computational
demands have challenged classical reliability analysis methods. Surrogate model-based …
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
Time-dependent reliability analysis using surrogate model has drawn much attention for
avoiding the high computational burden. But the surrogate training strategies of existing …
avoiding the high computational burden. But the surrogate training strategies of existing …