A combined projection-outline-based active learning Kriging and adaptive importance sampling method for hybrid reliability analysis with small failure probabilities

DOI10.1016/j.cma.2018.10.003zbMath1440.65009OpenAlexW2896845269WikidataQ129091556 ScholiaQ129091556MaRDI QIDQ1986678

Mi Xiao, Jinhao Zhang, Sheng Chu, Liang Gao

Publication date: 9 April 2020

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.2018.10.003

zbMATH Keywords

Krigingadaptive importance samplinghybrid reliability analysisprojection-outline-based active learningsmall failure probabilities

Mathematics Subject Classification ID

Monte Carlo methods (65C05) General methods in interval analysis (65G40) Sequential statistical design (62L05) Reliability and life testing (62N05) Prediction theory (aspects of stochastic processes) (60G25)

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Uses Software

• AK-MCS

Cites Work

• Structural reliability analysis using non-probabilistic convex model
• Vertex method for computing functions of fuzzy variables
• A novel projection outline based active learning method and its combination with Kriging metamodel for hybrid reliability analysis with random and interval variables
• An efficient reliability method combining adaptive importance sampling and kriging metamodel
• Computational methods in optimization considering uncertainties - An overview
• Interval uncertain method for multibody mechanical systems using Chebyshev inclusion functions
• Reliability sensitivity analysis with random and interval variables
• Does Finasteride Affect the Severity of Prostate Cancer? A Causal Sensitivity Analysis
• Remarks on a Multivariate Transformation

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