Engineering analysis with probability boxes: A review on computational methods
The consideration of imprecise probability in engineering analysis to account for missing,
vague or incomplete data in the description of model uncertainties is a fast-growing field of …
vague or incomplete data in the description of model uncertainties is a fast-growing field of …
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 …
reliability analysis with a wide variety of developments seamlessly presented over decades …
Estimation of small failure probabilities by partially Bayesian active learning line sampling: Theory and algorithm
Line sampling (LS) has proved to be a highly promising advanced simulation technique for
assessing small failure probabilities. Despite the great interest in practical engineering …
assessing small failure probabilities. Despite the great interest in practical engineering …
[HTML][HTML] Bayesian active learning line sampling with log-normal process for rare-event probability estimation
Line sampling (LS) stands as a powerful stochastic simulation method for structural reliability
analysis, especially for assessing small failure probabilities. To further improve the …
analysis, especially for assessing small failure probabilities. To further improve the …
Active learning line sampling for rare event analysis
Line Sampling (LS) has been widely recognized as one of the most appealing stochastic
simulation algorithms for rare event analysis, but when applying it to many real-world …
simulation algorithms for rare event analysis, but when applying it to many real-world …
Estimation of failure probability function under imprecise probabilities by active learning–augmented probabilistic integration
Imprecise probabilities have gained increasing popularity for quantitatively modeling
uncertainty under incomplete information in various fields. However, it is still a …
uncertainty under incomplete information in various fields. However, it is still a …
Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm
This paper presents a novel decoupling approach to efficiently solve a class of reliability-
based design optimization (RBDO) problems by means of augmented Line Sampling. The …
based design optimization (RBDO) problems by means of augmented Line Sampling. The …
Reliability analysis with cross-entropy based adaptive Markov chain importance sampling and control variates
MB Mehni, MB Mehni - Reliability Engineering & System Safety, 2023 - Elsevier
In reliability analysis, high dimensional problems pose challenges to many existing
sampling methods. Cross-entropy based Gaussian mixture importance sampling has …
sampling methods. Cross-entropy based Gaussian mixture importance sampling has …
Fully decoupled reliability-based design optimization of structural systems subject to uncertain loads
Reliability-based optimization (RBO) offers the possibility of finding the best design for a
system according to a prescribed criterion while explicitly taking into account the effects of …
system according to a prescribed criterion while explicitly taking into account the effects of …
[HTML][HTML] Efficient reliability analysis of complex systems in consideration of imprecision
In this work, the reliability of complex systems under consideration of imprecision is
addressed. By joining two methods coming from different fields, namely, structural reliability …
addressed. By joining two methods coming from different fields, namely, structural reliability …