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Multidimensional risk evaluation of natural gas pipelines based on a multicriteria decision model using visualization tools and statistical tests for global sensitivity analysis

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  • Medeiros, C.P.
  • Alencar, M.H.
  • de Almeida, A.T.

Abstract

Multidimensional risk analysis in pipelines has been addressed in the literature in recent years which has led to a greater understanding of risk in the decision context. A risk assessment model based on different perspectives becomes attractive to decision-makers (DMs) who are responsible for the maintenance of pipelines, and can help to prioritize maintenance efforts, and therefore optimize the use of human financial and other resources. As to the transportation of gas by pipeline, efforts at risk analysis must consider the physical and operational characteristics of the product, failure modes and their consequences, based on each accidental scenario considered. Different parameters are collected and/or estimated in order to produce a recommendation for the DM. Therefore, this paper enhances previous suggestions for a multicriteria decision model that evaluates multidimensional risk by using visualization tools and statistical tests as part of global sensitivity analysis. Simulations are made considering patterns which provide the DM with information about the uncertainty of different groups of parameters for the model. Furthermore, the output of the disturbance can be checked based on Kendall's correlation coefficient. Finally an evaluation can be made graphically of the different rankings of sections, thereby making a more assertive recommendation to the DM.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:reensy:v:165:y:2017:i:c:p:268-276
    DOI: 10.1016/j.ress.2017.04.002
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    1. Estecahandy, M. & Bordes, L. & Collas, S. & Paroissin, C., 2015. "Some acceleration methods for Monte Carlo simulation of rare events," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 296-310.
    2. Suzana de Suzana Dantas Daher & Adiel Teixeira Almeida, 2012. "The Use of Ranking Veto Concept to Mitigate the Compensatory Effects of Additive Aggregation in Group Decisions on a Water Utility Automation Investment," Group Decision and Negotiation, Springer, vol. 21(2), pages 185-204, March.
    3. Tang, Zhang-Chun & Zuo, Ming J. & Xiao, Ningcong, 2016. "An efficient method for evaluating the effect of input parameters on the integrity of safety systems," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 111-123.
    4. Shields, Michael D. & Teferra, Kirubel & Hapij, Adam & Daddazio, Raymond P., 2015. "Refined Stratified Sampling for efficient Monte Carlo based uncertainty quantification," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 310-325.
    5. Cheng, Lei & Lu, Zhenzhou & Zhang, Leigang, 2015. "Application of Rejection Sampling based methodology to variance based parametric sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 9-18.
    6. Marco Ratto, 2008. "Analysing DSGE Models with Global Sensitivity Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 31(2), pages 115-139, March.
    7. Bedford, Tim & Wilson, Kevin J. & Daneshkhah, Alireza, 2014. "Assessing parameter uncertainty on coupled models using minimum information methods," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 3-12.
    8. Di Maio, Francesco & Rai, Ajit & Zio, Enrico, 2016. "A dynamic probabilistic safety margin characterization approach in support of Integrated Deterministic and Probabilistic Safety Analysis," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 9-18.
    9. 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.
    10. Brito, A.J. & de Almeida, A.T., 2009. "Multi-attribute risk assessment for risk ranking of natural gas pipelines," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 187-198.
    11. Santosh, a & Vinod, Gopika & Shrivastava, O.P. & Saraf, R.K. & Ghosh, A.K. & Kushwaha, H.S., 2006. "Reliability analysis of pipelines carrying H2S for risk based inspection of heavy water plants," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 163-170.
    12. Mohsin, R. & Majid, Z.A. & Yusof, M.Z., 2014. "Safety distance between underground natural gas and water pipeline facilities," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 53-60.
    13. Noh, Yeelyong & Chang, Kwangpil & Seo, Yutaek & Chang, Daejun, 2014. "Risk-based determination of design pressure of LNG fuel storage tanks based on dynamic process simulation combined with Monte Carlo method," Reliability Engineering and System Safety, Elsevier, vol. 129(C), pages 76-82.
    14. Gomes, Wellison J.S. & Beck, André T. & Haukaas, Terje, 2013. "Optimal inspection planning for onshore pipelines subject to external corrosion," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 18-27.
    15. Rocco Sanseverino, Claudio M. & Ramirez-Marquez, José Emmanuel, 2014. "Uncertainty propagation and sensitivity analysis in system reliability assessment via unscented transformation," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 176-185.
    16. Brito, Anderson J. & de Almeida, Adiel Teixeira & Mota, Caroline M.M., 2010. "A multicriteria model for risk sorting of natural gas pipelines based on ELECTRE TRI integrating Utility Theory," European Journal of Operational Research, Elsevier, vol. 200(3), pages 812-821, February.
    17. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.
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    2. Henriques de Gusmão, Ana Paula & Mendonça Silva, Maisa & Poleto, Thiago & Camara e Silva, Lúcio & Cabral Seixas Costa, Ana Paula, 2018. "Cybersecurity risk analysis model using fault tree analysis and fuzzy decision theory," International Journal of Information Management, Elsevier, vol. 43(C), pages 248-260.
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    4. 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).
    5. Medeiros, Cristina Pereira & da Silva, Lucas Borges Leal & Alencar, Marcelo Hazin & de Almeida, Adiel Teixeira, 2021. "A new method for managing multidimensional risks in Natural Gas Pipelines based on non-Expected Utility," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    6. Yang, Yang & Li, Suzhen & Zhang, Pengcheng, 2022. "Data-driven accident consequence assessment on urban gas pipeline network based on machine learning," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    7. Thalles Vitelli Garcez & Helder Tenório Cavalcanti & Adiel Teixeira de Almeida, 2021. "A hybrid decision support model using Grey Relational Analysis and the Additive-Veto Model for solving multicriteria decision-making problems: an approach to supplier selection," Annals of Operations Research, Springer, vol. 304(1), pages 199-231, September.

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