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FORM-based global reliability sensitivity analysis of systems with multiple failure modes

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  • Papaioannou, Iason
  • Straub, Daniel

Abstract

Global variance-based reliability sensitivity indices arise from a variance decomposition of the indicator function describing the failure event. The first-order indices reflect the main effect of each variable on the variance of the failure event and can be used for variable prioritization; the total-effect indices represent the total effect of each variable, including its interaction with other variables, and can be used for variable fixing. This contribution derives expressions for the variance-based reliability sensitivity indices of systems with multiple failure modes that are based on the first-order reliability method (FORM). The derived expressions are a function of the FORM results and, hence, do not require additional expensive model evaluations. They do involve the evaluation of multinormal integrals, for which effective solutions are available. We demonstrate that the derived expressions enable an accurate estimation of variance-based reliability sensitivities for general system problems to which FORM is applicable.

Suggested Citation

  • Papaioannou, Iason & Straub, Daniel, 2025. "FORM-based global reliability sensitivity analysis of systems with multiple failure modes," Reliability Engineering and System Safety, Elsevier, vol. 260(C).
    • Handle: RePEc:eee:reensy:v:260:y:2025:i:c:s0951832025001772
    DOI: 10.1016/j.ress.2025.110974
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    References listed on IDEAS

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    1. Fauriat, W. & Gayton, N., 2014. "AK-SYS: An adaptation of the AK-MCS method for system reliability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 137-144.
    2. Z. I. Botev, 2017. "The normal law under linear restrictions: simulation and estimation via minimax tilting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 125-148, January.
    3. Papaioannou, Iason & Straub, Daniel, 2021. "Variance-based reliability sensitivity analysis and the FORM α-factors," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    4. Ehre, Max & Papaioannou, Iason & Straub, Daniel, 2020. "Global sensitivity analysis in high dimensions with PLS-PCE," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    5. Xiao, Ning-Cong & Yuan, Kai & Zhan, Hongyou, 2022. "System reliability analysis based on dependent Kriging predictions and parallel learning strategy," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    6. Kim, Taeyong & Song, Junho, 2018. "Generalized Reliability Importance Measure (GRIM) using Gaussian mixture," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 105-115.
    7. Straub, Daniel & Ehre, Max & Papaioannou, Iason, 2022. "Decision-theoretic reliability sensitivity," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    8. Yuan, Kai & Xiao, Ning-Cong & Wang, Zhonglai & Shang, Kun, 2020. "System reliability analysis by combining structure function and active learning kriging model," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    9. Ma, Yuan-Zhuo & Jin, Xiang-Xiang & Zhao, Xiang & Li, Hong-Shuang & Zhao, Zhen-Zhou & Xu, Chang, 2024. "Reliability-oriented global sensitivity analysis using subset simulation and space partition," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    10. Yang, Xufeng & Liu, Yongshou & Mi, Caiying & Tang, Chenghu, 2018. "System reliability analysis through active learning Kriging model with truncated candidate region," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 235-241.
    11. Ehre, Max & Papaioannou, Iason & Straub, Daniel, 2020. "A framework for global reliability sensitivity analysis in the presence of multi-uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    12. Song, Shufang & Lu, Zhenzhou & Qiao, Hongwei, 2009. "Subset simulation for structural reliability sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 658-665.
    13. Papaioannou, Iason & Geyer, Sebastian & Straub, Daniel, 2019. "Improved cross entropy-based importance sampling with a flexible mixture model," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    14. Wei, Pengfei & Lu, Zhenzhou & Ruan, Wenbin & Song, Jingwen, 2014. "Regional sensitivity analysis using revised mean and variance ratio functions," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 121-135.
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