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Reliability estimation of an advanced nuclear fuel using coupled active learning, multifidelity modeling, and subset simulation
16 references·14 citing·39 second hop
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References

  • 2001Estimation of small failure probabilities in high dimensions by subset simulation2,419 cited
  • 2011AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation2,048 cited
  • 2008Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions1,141 cited
  • 2018Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization1,072 cited
  • 2015MCMC algorithms for Subset Simulation413 cited
  • 2016Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation412 cited
  • 2021Machine learning-based methods in structural reliability analysis: A review370 cited
  • 2019REIF: A novel active-learning function toward adaptive Kriging surrogate models for structural reliability analysis297 cited
  • 2016Rare Event Estimation Using Polynomial-Chaos Kriging279 cited
  • 2019An active learning reliability method combining Kriging constructed with exploration and exploitation of failure region and subset simulation153 cited
  • 2018Hamiltonian Monte Carlo methods for Subset Simulation in reliability analysis151 cited
  • 2015Multifidelity importance sampling130 cited
  • 2020Reliability analysis with stratified importance sampling based on adaptive Kriging127 cited
  • 2020A generalized approximate control variate framework for multifidelity uncertainty quantification

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112 cited
  • 2020AK-MSS: An adaptation of the AK-MCS method for small failure probabilities78 cited
  • 2021Reliability analysis using adaptive Polynomial-Chaos Kriging and probability density evolution method77 cited
  • Cited by

    • 2023Partial least squares-based polynomial chaos Kriging for high-dimensional reliability analysis29 cited
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    • 2024Aleatory uncertainty quantification based on multi-fidelity deep neural networks25 cited
    • 2024A physics and data co-driven surrogate modeling method for high-dimensional rare event simulation24 cited
    • 2023Look-ahead active learning reliability analysis based on stepwise margin reduction23 cited
    • 2024EMR-SSM: Synchronous surrogate modeling-based enhanced moving regression method for multi-response prediction and reliability evaluation20 cited
    • 2023Bi-fidelity Kriging model for reliability analysis of the ultimate strength of stiffened panels19 cited
    • 2023UQpy v4.1: Uncertainty quantification with Python19 cited
    • 2023General Multifidelity Surrogate Models: Framework and Active-Learning Strategies for Efficient Rare Event Simulation11 cited
    • 2025Adaptive proposal length scale in Subset Simulation11 cited
    • 2025Reliability assessment of offshore wind turbine gears under multiple failure modes using deeply coupled adaptive Kriging based-generalized subset simulation8 cited
    • 2025Adaptive physics-informed neural operator and subset simulation for high-dimensional reliability analysis with multiple stochastic processes in stochastic differential equations8 cited
    • 2025Accelerating subset simulation with surrogate model ensuring unbiased failure probability estimation8 cited
    • 2025Multi-fidelity modelling for uncertainty quantification of timber beam-column connections exposed to standard fire7 cited