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Subset simulation-based reliability analysis of the corroding natural gas pipeline

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  • Yu, Weichao
  • Huang, Weihe
  • Wen, Kai
  • Zhang, Jie
  • Liu, Hongfei
  • Wang, Kun
  • Gong, Jing
  • Qu, Chunxu

Abstract

In this study, a subset simulation-based methodology is developed to evaluate the time-dependent reliability of the corroding pipeline with multiple correlated corrosion defects. Two competing failure modes, namely small leak and burst, are considered in the methodology. Firstly, the time-dependent structural reliability model of the two competing failure modes is established. Then, the computational framework for implementing subset simulation for failure probability estimation of the individual corrosion defect is presented. Thereafter, a procedure to calculate the system reliability of the entire pipeline with correlated corrosion defects is proposed. Moreover, a numerical example based on a real natural gas pipeline is proposed, and the time-dependent failure probabilities of both the small leak and burst are predicted, which are compared with the evaluation results produced by the direct Monte Carlo simulation and Kriging method. By means of numerical example, the accuracy and efficiency of our methodology are demonstrated. Furthermore, a sensitivity analysis is performed to investigated the effect of the correlation of the corrosion defects on the system reliability, and the results indicate that the correlation exert great impact on system reliability.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021002027
    DOI: 10.1016/j.ress.2021.107661
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    1. 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.
    2. Yu, Weichao & Wen, Kai & Min, Yuan & He, Lei & Huang, Weihe & Gong, Jing, 2018. "A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 128-141.
    3. Yu, Weichao & Gong, Jing & Song, Shangfei & Huang, Weihe & Li, Yichen & Zhang, Jie & Hong, Bingyuan & Zhang, Ye & Wen, Kai & Duan, Xu, 2019. "Gas supply reliability analysis of a natural gas pipeline system considering the effects of underground gas storages," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    4. Jian, Wang & Zhili, Sun & Qiang, Yang & Rui, Li, 2017. "Two accuracy measures of the Kriging model for structural reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 494-505.
    5. Gaspar, B. & Teixeira, A.P. & Guedes Soares, C., 2017. "Adaptive surrogate model with active refinement combining Kriging and a trust region method," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 277-291.
    6. 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.
    7. Yu, Weichao & Song, Shangfei & Li, Yichen & Min, Yuan & Huang, Weihe & Wen, Kai & Gong, Jing, 2018. "Gas supply reliability assessment of natural gas transmission pipeline systems," Energy, Elsevier, vol. 162(C), pages 853-870.
    8. Gong, C. & Zhou, W., 2018. "Importance sampling-based system reliability analysis of corroding pipelines considering multiple failure modes," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 199-208.
    9. Dann, Markus R. & Maes, Marc A., 2018. "Stochastic corrosion growth modeling for pipelines using mass inspection data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 245-254.
    10. 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.
    11. Chen, Weidong & Xu, Chunlong & Shi, Yaqin & Ma, Jingxin & Lu, Shengzhuo, 2019. "A hybrid Kriging-based reliability method for small failure probabilities," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 31-41.
    12. Zhou, W. & Xiang, W. & Hong, H.P., 2017. "Sensitivity of system reliability of corroding pipelines to modeling of stochastic growth of corrosion defects," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 428-438.
    13. Song, Shufang & Lu, Zhenzhou & Qiao, Hongwei, 2009. "Subset simulation for structural reliability sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 658-665.
    14. Dana Kelly & Curtis Smith, 2011. "Bayesian Inference for Probabilistic Risk Assessment," Springer Series in Reliability Engineering, Springer, number 978-1-84996-187-5, February.
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    5. Mohamed El Amine Ben Seghier & Panagiotis Spyridis & Jafar Jafari-Asl & Sima Ohadi & Xinhong Li, 2022. "Comparative Study on the Efficiency of Simulation and Meta-Model-Based Monte Carlo Techniques for Accurate Reliability Analysis of Corroded Pipelines," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    6. Yin, Yuanbo & Yang, Hao & Duan, Pengfei & Li, Luling & Zio, Enrico & Liu, Cuiwei & Li, Yuxing, 2022. "Improved quantitative risk assessment of a natural gas pipeline considering high-consequence areas," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    7. Mathpati, Yogesh Chandrakant & More, Kalpesh Sanjay & Tripura, Tapas & Nayek, Rajdip & Chakraborty, Souvik, 2023. "MAntRA: A framework for model agnostic reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
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    9. Chan, Jianpeng & Papaioannou, Iason & Straub, Daniel, 2022. "An adaptive subset simulation algorithm for system reliability analysis with discontinuous limit states," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    10. Xiao, Rui & Zayed, Tarek & Meguid, Mohamed A. & Sushama, Laxmi, 2024. "Improving failure modeling for gas transmission pipelines: A survival analysis and machine learning integrated approach," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
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