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Stochastic multiscale modeling for quantifying statistical and model errors with application to composite materials

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  • Wang, Zhiheng
  • Hawi, Philippe
  • Masri, Sami
  • Aitharaju, Venkat
  • Ghanem, Roger

Abstract

This paper provides a coherent and efficient computational framework for stochastic multiscale analysis of material systems in the presence of parametric uncertainties and modeling errors. Uncertainty in those model parameters that are not deduced as upscaled quantities is attributed to an uncertainty “germ†. While such parameters can appear at any scale, they are predominant at the finest analysis scale. Additional uncertainties stemming from statistical estimation, attributed to lack of data and model error, are associated with each submodel contributing to the multiscale system. A robust and efficient framework based on a generalized extended polynomial chaos expansion (gEPCE) is proposed to simultaneously propagate all these uncertainties in order to provide a probabilistic representation of specific quantities of interest (QoI). We characterize the full probability distribution of the QoI and the uncertainty in the failure probability pertaining to its tails. By combining gEPCE with kernel density estimation (KDE) and directional derivatives, we construct sensitivity measures that connect these statistical metrics of QoI to the various sources of uncertainty to assess their individual and combined impacts. An illustrative problem featuring three-point bending of a composite beam is investigated to demonstrate the presented approach.

Suggested Citation

  • Wang, Zhiheng & Hawi, Philippe & Masri, Sami & Aitharaju, Venkat & Ghanem, Roger, 2023. "Stochastic multiscale modeling for quantifying statistical and model errors with application to composite materials," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
  • Handle: RePEc:eee:reensy:v:235:y:2023:i:c:s095183202300128x
    DOI: 10.1016/j.ress.2023.109213
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    References listed on IDEAS

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    1. Tabandeh, Armin & Sharma, Neetesh & Gardoni, Paolo, 2022. "Uncertainty propagation in risk and resilience analysis of hierarchical systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    2. Der Kiureghian, Armen & Song, Junho, 2008. "Multi-scale reliability analysis and updating of complex systems by use of linear programming," Reliability Engineering and System Safety, Elsevier, vol. 93(2), pages 288-297.
    3. McKeand, Austin M. & Gorguluarslan, Recep M. & Choi, Seung-Kyum, 2021. "Stochastic analysis and validation under aleatory and epistemic uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    4. Ye, Dongwei & Nikishova, Anna & Veen, Lourens & Zun, Pavel & Hoekstra, Alfons G., 2021. "Non-intrusive and semi-intrusive uncertainty quantification of a multiscale in-stent restenosis model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    5. Mullins, Joshua & Ling, You & Mahadevan, Sankaran & Sun, Lin & Strachan, Alejandro, 2016. "Separation of aleatory and epistemic uncertainty in probabilistic model validation," Reliability Engineering and System Safety, Elsevier, vol. 147(C), pages 49-59.
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    Cited by:

    1. Dasgupta, Agnimitra & Johnson, Erik A., 2024. "REIN: Reliability Estimation via Importance sampling with Normalizing flows," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

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