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Time-dependent finite element reliability assessment of cast-iron water pipes subjected to spatio-temporal correlated corrosion process

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  • Aryai, Vahid
  • Baji, Hassan
  • Mahmoodian, Mojtaba
  • Li, Chun-Qing

Abstract

Reliable prediction of the service-life of water pipes is of great importance for asset managers and decision makers. This paper introduces a framework for evaluating the reliability of corroded pipelines. Incorporating the random field representation of corrosion into a finite-element analysis have always been a daunting task especially when the time-dependent reliability analysis is intended. This research addresses the issue by representing the cross-section reduction of a buried pipe due to corrosion through a combination of the Gamma process concept and copula. Moreover, spatial and temporal evolutions of the correlation structure that exists among the corrosion pits over the pipe surface are considered using a time-dependent correlation length model recently introduced by the authors. A three-dimensional non-linear finite element analysis is used to model the residual strength of pipes in terms of time. The method is applied to a case study for estimating the failure probability of a corrosion-affected cast iron water pipe. Furthermore, the impact of the correlation structure of the corrosion depths on the estimated probability of failure is investigated. The research concludes that the proposed method is able to predict the service life of corroding buried pipeline efficiently.

Suggested Citation

  • Aryai, Vahid & Baji, Hassan & Mahmoodian, Mojtaba & Li, Chun-Qing, 2020. "Time-dependent finite element reliability assessment of cast-iron water pipes subjected to spatio-temporal correlated corrosion process," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:reensy:v:197:y:2020:i:c:s0951832018309037
    DOI: 10.1016/j.ress.2020.106802
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    References listed on IDEAS

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    1. van Noortwijk, J.M. & van der Weide, J.A.M. & Kallen, M.J. & Pandey, M.D., 2007. "Gamma processes and peaks-over-threshold distributions for time-dependent reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1651-1658.
    2. Li, C.Q. & Mahmoodian, M., 2013. "Risk based service life prediction of underground cast iron pipes subjected to corrosion," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 102-108.
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    Citations

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    Cited by:

    1. Amaya-Gómez, Rafael & Schoefs, Franck & Sánchez-Silva, Mauricio & Muñoz, Felipe & Bastidas-Arteaga, Emilio, 2022. "Matching of corroded defects in onshore pipelines based on In-Line Inspections and Voronoi partitions," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    2. Lee, Dongkyu & Song, Junho, 2023. "Risk-informed operation and maintenance of complex lifeline systems using parallelized multi-agent deep Q-network," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    3. Nguyen, Hung & Abdel-Mottaleb, Noha & Uddin, Shihab & Zhang, Qiong & Lu, Qing & Zhang, He & Li, Mingyang, 2022. "Joint maintenance planning of deteriorating co-located road and water infrastructures with interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    4. Fan, Xudong & Wang, Xiaowei & Zhang, Xijin & ASCE Xiong (Bill) Yu, P.E.F., 2022. "Machine learning based water pipe failure prediction: The effects of engineering, geology, climate and socio-economic factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Hao, Peng & Tang, Hao & Wang, Yu & Wu, Tao & Feng, Shaojun & Wang, Bo, 2023. "Stochastic isogeometric buckling analysis of composite shell considering multiple uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    6. Su, Yue & Li, Jingfa & Yu, Bo & Zhao, Yanlin & Yao, Jun, 2021. "Fast and accurate prediction of failure pressure of oil and gas defective pipelines using the deep learning model," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

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