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Time-dependent reliability analysis of service-proven quay walls subject to corrosion-induced degradation

Author

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  • Roubos, Alfred A.
  • Allaix, Diego L.
  • Schweckendiek, Timo
  • Steenbergen, Raphael D.J.M.
  • Jonkman, Sebastiaan N.

Abstract

The assessment of service-proven quay walls subject to corrosion-induced degradation is inherently a time-dependent reliability problem. Two major challenges are the modelling of corrosion and taking into account the decrease of epistemic uncertainty throughout the quay wall's service life. The main objective of this study is to examine the probability of failure, despite successful past performance, when the quay wall is subject to corrosion and randomly imposed variable loads. The development of the annual failure rate is modelled using crude Monte Carlo and by performing a first-order system reliability analysis. The annual failure rates found for service-proven quay walls vary over time. For those with successful service histories and subject to low corrosion rates, the highest reliability indices are observed in the first year of the service life, whereas with higher corrosion rates the final year prevails. In general, it seems more practical to evaluate reliability on an annual basis rather than over longer time periods, since the latter will introduce an iterative procedure to determine the wall's remaining lifetime. The key findings of this study can be crucial for the lifetime extension of existing quay walls, and presumably also for other service-proven geotechnical structures subject to corrosion.

Suggested Citation

  • Roubos, Alfred A. & Allaix, Diego L. & Schweckendiek, Timo & Steenbergen, Raphael D.J.M. & Jonkman, Sebastiaan N., 2020. "Time-dependent reliability analysis of service-proven quay walls subject to corrosion-induced degradation," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:reensy:v:203:y:2020:i:c:s095183202030586x
    DOI: 10.1016/j.ress.2020.107085
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    References listed on IDEAS

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    1. Melchers, R.E. & Jeffrey, R.J., 2008. "Probabilistic models for steel corrosion loss and pitting of marine infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 423-432.
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    Cited by:

    1. Woloszyk, Krzysztof & Garbatov, Yordan, 2024. "A probabilistic-driven framework for enhanced corrosion estimation of ship structural components," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Yeh, Wei-Chang & Du, Chia-Ming & Tan, Shi-Yi & Forghani-elahabad, Majid, 2023. "Application of LSTM based on the BAT-MCS for binary-state network approximated time-dependent reliability problems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    3. Li, Mingyang & Wang, Zequn, 2022. "LSTM-augmented deep networks for time-variant reliability assessment of dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    4. den Heijer, Frank & Kok, Matthijs, 2024. "Risk-based portfolio planning of dike reinforcements," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    5. Cao, Runan & Sun, Zhili & Wang, Jian & Guo, Fanyi, 2022. "A single-loop reliability analysis strategy for time-dependent problems with small failure probability," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    6. Shirgir, Sina & Shamsaddinlou, Amir & Zare, Reza Najafi & Zehtabiyan, Sorour & Bonab, Masoud Hajialilue, 2023. "An efficient double-loop reliability-based optimization with metaheuristic algorithms to design soil nail walls under uncertain condition," Reliability Engineering and System Safety, Elsevier, vol. 232(C).

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