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Reliability analysis using a multi-metamodel complement-basis approach

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  • Teixeira, Rui
  • Martinez-Pastor, Beatriz
  • Nogal, Maria
  • O’Connor, Alan

Abstract

The present work discusses an innovative approach to metamodeling in reliability that uses a field-transversal rationale. Adaptive metamodeling in reliability is characterized by its large spectra of models and techniques with different assumptions. As a result, the reliability engineer is frequently faced with the highly challenging task of selecting an appropriate model or technique with limited a priori knowledge about the performance function that defines the problem of reliability.

Suggested Citation

  • Teixeira, Rui & Martinez-Pastor, Beatriz & Nogal, Maria & O’Connor, Alan, 2021. "Reliability analysis using a multi-metamodel complement-basis approach," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    • Handle: RePEc:eee:reensy:v:205:y:2021:i:c:s0951832020307481
    DOI: 10.1016/j.ress.2020.107248
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    References listed on IDEAS

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    Cited by:

    1. 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).
    2. Zhou, Changcong & Zhang, Hanlin & Valdebenito, Marcos A. & Zhao, Haodong, 2022. "A general hierarchical ensemble-learning framework for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    3. Yi, Jiaxiang & Cheng, Yuansheng & Liu, Jun, 2022. "A novel fidelity selection strategy-guided multifidelity kriging algorithm for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    4. Li, Guosheng & Ma, Shuaichao & Zhang, Dequan & Yang, Leping & Zhang, Weihua & Wu, Zeping, 2024. "An efficient sequential anisotropic RBF reliability analysis method with fast cross-validation and parallelizability," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Zhang, Jian & Gong, Weijie & Yue, Xinxin & Shi, Maolin & Chen, Lei, 2022. "Efficient reliability analysis using prediction-oriented active sparse polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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