Adaptive reliability analysis for rare events evaluation with global imprecise line sampling

DOI10.1016/j.cma.2020.113344zbMath1506.62392OpenAlexW3080882994MaRDI QIDQ2020920

Pengfei Wei, Jingwen Song, Michael A. Beer, Marcos A. Valdebenito

Publication date: 26 April 2021

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2020.113344

zbMATH Keywords

sensitivity analysisactive learningimprecise probabilityuncertainty quantificationGaussian process regressionline sampling

Mathematics Subject Classification ID

Probabilistic models, generic numerical methods in probability and statistics (65C20) Reliability and life testing (62N05)

Related Items (4)

Deep reliability learning with latent adaptation for design optimization under uncertainty ⋮ Estimation of small failure probabilities by partially Bayesian active learning line sampling: theory and algorithm ⋮ Efficient structural reliability analysis based on adaptive Bayesian support vector regression ⋮ Bounds optimization of model response moments: a twin-engine Bayesian active learning method

Uses Software

• AK-MCS

Cites Work

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• Bayesian approach for inconsistent information
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• Multilevel surrogate modeling approach for optimization problems with polymorphic uncertain parameters
• Structural reliability under combined random load sequences
• Risk Analysis in Engineering and Economics
• High dimensional model representations generated from low dimensional data samples. I: mp-cut-HDMR

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