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Global sensitivity analysis of the impact of impurities on CO2 pipeline failure

Author

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  • Brown, S.
  • Beck, J.
  • Mahgerefteh, H.
  • Fraga, E.S.

Abstract

This paper describes the testing, comparison and application of global sensitivity techniques for the study of the impact of the stream impurities on CO2 pipeline failure. Global sensitivity analysis through non-intrusive generalised polynomial chaos expansion with sparse grids is compared to more common techniques and is found to achieve superior convergence rate to crude Monte Carlo, quasi-Monte Carlo and EFAST for functions with up to a moderate level of “roughness†. This methodology is then applied to the hypothetical full bore rupture of a 1km CO2 pipeline at 150bara and 283.15K. The sensitivity of the ensuing outflow to the composition of a quaternary mixture of CO2 with N2, CH4 and O2 as representative stream impurities. The results indicate that the outflow rate is highly sensitive to the composition during the early stages of depressurisation, where the effect of the impurities on phase equilibria has a significant impact on the outflow.

Suggested Citation

  • Brown, S. & Beck, J. & Mahgerefteh, H. & Fraga, E.S., 2013. "Global sensitivity analysis of the impact of impurities on CO2 pipeline failure," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 43-54.
    • Handle: RePEc:eee:reensy:v:115:y:2013:i:c:p:43-54
    DOI: 10.1016/j.ress.2013.02.006
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    References listed on IDEAS

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    1. Sudret, Bruno, 2008. "Global sensitivity analysis using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 964-979.
    2. Crestaux, Thierry & Le Maıˆtre, Olivier & Martinez, Jean-Marc, 2009. "Polynomial chaos expansion for sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1161-1172.
    3. Saltelli, Andrea & Bolado, Ricardo, 1998. "An alternative way to compute Fourier amplitude sensitivity test (FAST)," Computational Statistics & Data Analysis, Elsevier, vol. 26(4), pages 445-460, February.
    4. Buzzard, Gregery T., 2012. "Global sensitivity analysis using sparse grid interpolation and polynomial chaos," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 82-89.
    5. Blatman, Géraud & Sudret, Bruno, 2010. "Efficient computation of global sensitivity indices using sparse polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1216-1229.
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    Cited by:

    1. Munkejord, Svend Tollak & Hammer, Morten & Løvseth, Sigurd W., 2016. "CO2 transport: Data and models – A review," Applied Energy, Elsevier, vol. 169(C), pages 499-523.
    2. Guo, Xiaolu & Yan, Xingqing & Zheng, Yangguang & Yu, Jianliang & Zhang, Yongchun & Chen, Shaoyun & Chen, Lin & Mahgerefteh, Haroun & Martynov, Sergey & Collard, Alexander & Brown, Solomon, 2017. "Under-expanded jets and dispersion in high pressure CO2 releases from an industrial scale pipeline," Energy, Elsevier, vol. 119(C), pages 53-66.
    3. Onyebuchi, V.E. & Kolios, A. & Hanak, D.P. & Biliyok, C. & Manovic, V., 2018. "A systematic review of key challenges of CO2 transport via pipelines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2563-2583.
    4. Guo, Xiaolu & Yan, Xingqing & Yu, Jianliang & Zhang, Yongchun & Chen, Shaoyun & Mahgerefteh, Haroun & Martynov, Sergey & Collard, Alexander & Proust, Christophe, 2016. "Under-expanded jets and dispersion in supercritical CO2 releases from a large-scale pipeline," Applied Energy, Elsevier, vol. 183(C), pages 1279-1291.
    5. Medeiros, C.P. & Alencar, M.H. & de Almeida, A.T., 2017. "Multidimensional risk evaluation of natural gas pipelines based on a multicriteria decision model using visualization tools and statistical tests for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 268-276.

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