Small failure probability: principles, progress and perspectives
Abstract Design of structural and multidisciplinary systems under uncertainties requires
estimation of their reliability or equivalently the probability of failure under the given …
estimation of their reliability or equivalently the probability of failure under the given …
Parallel adaptive Bayesian quadrature for rare event estimation
Various numerical methods have been extensively studied and used for reliability analysis
over the past several decades. However, how to understand the effect of numerical …
over the past several decades. However, how to understand the effect of numerical …
Structural reliability analysis: A Bayesian perspective
Numerical methods play a dominant role in structural reliability analysis, and the goal has
long been to produce a failure probability estimate with a desired level of accuracy using a …
long been to produce a failure probability estimate with a desired level of accuracy using a …
Parallel Bayesian probabilistic integration for structural reliability analysis with small failure probabilities
Bayesian active learning methods have emerged for structural reliability analysis and shown
more attractive features than existing active learning methods. However, it remains a …
more attractive features than existing active learning methods. However, it remains a …
[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 …
[HTML][HTML] Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities
The Bayesian failure probability inference (BFPI) framework provides a well-established
Bayesian approach to quantifying our epistemic uncertainty about the failure probability …
Bayesian approach to quantifying our epistemic uncertainty about the failure probability …
Bayesian probabilistic propagation of hybrid uncertainties: Estimation of response expectation function, its variable importance and bounds
Uncertainties existing in physical and engineering systems can be characterized by different
kinds of mathematical models according to their respective features. However, efficient …
kinds of mathematical models according to their respective features. However, efficient …
Bayesian reinforcement learning reliability analysis
A Bayesian reinforcement learning reliability method that combines Bayesian inference for
the failure probability estimation and reinforcement learning-guided sequential experimental …
the failure probability estimation and reinforcement learning-guided sequential experimental …
[HTML][HTML] Semi-Bayesian active learning quadrature for estimating extremely low failure probabilities
The Bayesian failure probability inference (BFPI) framework provides a sound basis for
developing new Bayesian active learning reliability analysis methods. However, it is still …
developing new Bayesian active learning reliability analysis methods. However, it is still …
An improved adaptive Kriging model for importance sampling reliability and reliability global sensitivity analysis
DW Jia, ZY Wu - Structural Safety, 2024 - Elsevier
An improved adaptive Kriging model for importance sampling (IS) reliability and reliability
global sensitivity analysis is proposed by introducing the IS density function into learning …
global sensitivity analysis is proposed by introducing the IS density function into learning …