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Reliability analysis of subsea pipelines under spatially varying ground motions by using subset simulation

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  • Li, Yuyin
  • Zhang, Yahui
  • Kennedy, David

Abstract

A computational framework is presented to calculate the reliability of subsea pipelines subjected to a random earthquake. This framework takes full account of the physical features of pipelines and the earthquake, and also retains high computing precision and efficiency. The pipeline and the seabed are modelled as a Timoshenko beam and a Winkler foundation, respectively, while the unilateral contact effect between them is considered. The random earthquake is described by its power spectrum density function and its spatial variation is considered. After suitable discretizations in the spatial domain by the finite element method and the time domain by the Newmark integration method, the dynamic unilateral contact problem is derived as a linear complementarity problem (LCP). Subset Simulation (SS), which is an advanced Monte Carlo simulation approach, is used to estimate the reliability of pipelines. By means of numerical examples, the accuracy and robustness of SS are demonstrated by comparing with the direct Monte Carlo simulation (DMCS). Then a sensitivity analysis of the reliability and a failure analysis are performed to identify the influential system parameters. Finally, failure probabilities of subsea pipelines are assessed for three typical cases, namely, with and without the unilateral contact effect, with different grades of spatial variations and with different free spans. The influences of these effects or parameters on the reliability are discussed qualitatively.

Suggested Citation

  • Li, Yuyin & Zhang, Yahui & Kennedy, David, 2018. "Reliability analysis of subsea pipelines under spatially varying ground motions by using subset simulation," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 74-83.
    • Handle: RePEc:eee:reensy:v:172:y:2018:i:c:p:74-83
    DOI: 10.1016/j.ress.2017.12.006
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    References listed on IDEAS

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    1. Cadini, F. & Avram, D. & Pedroni, N. & Zio, E., 2012. "Subset Simulation of a reliability model for radioactive waste repository performance assessment," Reliability Engineering and System Safety, Elsevier, vol. 100(C), pages 75-83.
    2. Tee, Kong Fah & Khan, Lutfor Rahman & Li, Hongshuang, 2014. "Application of subset simulation in reliability estimation of underground pipelines," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 125-131.
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    Cited by:

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    2. Li, Zhengbing & Feng, Huixia & Liang, Yongtu & Xu, Ning & Nie, Siming & Zhang, Haoran, 2019. "A leakage risk assessment method for hazardous liquid pipeline based on Markov chain Monte Carlo," International Journal of Critical Infrastructure Protection, Elsevier, vol. 27(C).
    3. Pang, Rui & Zai, Dezhi & Xu, Bin & Liu, Jun & Zhao, Chunfeng & Fan, Qunying & Chen, Yuting, 2023. "Stochastic dynamic and reliability analysis of AP1000 nuclear power plants via DPIM subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    4. Silva, L.M.R. & Guedes Soares, C., 2023. "Robust optimization model of an offshore oil production system for cost and pipeline risk of failure," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    5. Yu, Weichao & Huang, Weihe & Wen, Kai & Zhang, Jie & Liu, Hongfei & Wang, Kun & Gong, Jing & Qu, Chunxu, 2021. "Subset simulation-based reliability analysis of the corroding natural gas pipeline," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    6. Li, Chao & Diao, Yucheng & Li, Hong-Nan & Pan, Haiyang & Ma, Ruisheng & Han, Qiang & Xing, Yihan, 2023. "Seismic performance assessment of a sea-crossing cable-stayed bridge system considering soil spatial variability," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    7. Chuan Wang & Jun Gou & Yingcheng Tian & Hao Jin & Chao Yu & Yupeng Liu & Jiajun Ma & Yong Xia, 2022. "Reliability and availability evaluation of subsea high integrity pressure protection system using stochastic Petri net," Journal of Risk and Reliability, , vol. 236(3), pages 508-521, June.

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