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A Study on the Estimating Burst Pressure Distributions for Reliability Assessment of API 5L X65 Pipes

API 5L X65 배관의 신뢰도 평가를 위한 파열압력 분포 추정에 관한 연구

  • Kim, Seong-Jun (Department of Industrial Engineering, Gangneung-Wonju National University) ;
  • Kim, Dohyun (Department of Industrial Engineering, Myongji University) ;
  • Kim, Cheolman (Research Institute, Korea Gas Corporation) ;
  • Kim, Woosik (Research Institute, Korea Gas Corporation)
  • 김성준 (강릉원주대학교 산업경영공학과) ;
  • 김도현 (명지대학교 산업경영공학과) ;
  • 김철만 (한국가스공사 가스연구원) ;
  • 김우식 (한국가스공사 가스연구원)
  • Received : 2020.10.30
  • Accepted : 2020.12.07
  • Published : 2020.12.31

Abstract

Purpose: The purpose of this paper is to present a probability distribution of the burst pressure of API 5L X65 pipes for the reliability assessment of corroded gas pipelines. Methods: Corrosion is a major cause of weakening the residual strength of the pipe. The mean residual strength on the corrosion defect can be obtained using the burst pressure code. However, in order to obtain the pipe reliability, a probability distribution of the burst pressure should be provided. This study is concerned with estimating the burst pressure distribution using Monte Carlo simulation. A response surface method is employed to represent the distribution parameter as a model of the corrosion defect size. Results: The experimental results suggest that the normal or Weibull distribution should be suitable as the probability distribution of the burst pressure. In particular, it was shown that the probability distribution parameters can be well predicted by using the depth and length of the corrosion defect. Conclusion: Given a corrosion defect on the pipe, its corresponding burst pressure distribution can be provided at instant. Subsequently, a reliability assessment of the pipe is conducted as well.

Keywords

References

  1. Caleyo, F., Conzalez, J. and J. Hallen. 2002. A study on the reliability methodology for pipelines with active corrosion defects. International Journal of Pressure Vessels and Piping 79:77-86. https://doi.org/10.1016/S0308-0161(01)00124-7
  2. Caleyo, F., Velazquez, J., Valor, A. and J. Hallen. 2009. Probability distribution of pitting corrosion depth and rate in underground pipelines: A Monte Carlo study. Corrosion Science 51:1925-1934. https://doi.org/10.1016/j.corsci.2009.05.019
  3. Cosham, A., Hopkins, P., and McDonald, K. 2007. Best practice for the assessment of defects in pipelines. Engineering Failure Analysis 14:1245-1265. https://doi.org/10.1016/j.engfailanal.2006.11.035
  4. CSA Z662-2007. Oil and Gas Pipeline System, Canadian Standards Association.
  5. Dundulis, G., Zutautaitee, I., Janulionis, R., Usspuras, E., Rimkeviccius, S., and Eid, M. 2016. Integrated failure probability estimation based on structural integrity analysis and failure data: Natural gas pipeline case. Reliability Engineering and System Safety 156:195-202. https://doi.org/10.1016/j.ress.2016.08.003
  6. Hasan, S., Khan, F., and Kenny, S. 2012. Probability assessment of burst limit state due to internal corrosion. International Journal of Pressure Vessels and Piping 89:48-58. https://doi.org/10.1016/j.ijpvp.2011.09.005
  7. ISO 16708-2006. Reliability-based limit state methods for pipeline transportation systems in petroleum and natural gas industries, International Standard Organization.
  8. Kim, S. J., Choi, B. and Kim, W. 2017. Prognostics for Industry 4.0 and its application to fitness-for-service assess- ment of corroded gas pipelines. Journal of the Korean Society of Quality Management 45:649-664. https://doi.org/10.7469/JKSQM.2017.45.4.649
  9. Kim, S. J., Kim, D., Kim, W., Kim Y. P., and Kim, C. 2019. An assessment of the gas pipeline reliability using corrosion based composite failure. Journal of the Korean Society of Quality Management 47:739-754.
  10. Kim, S. I., Lee, S. B., Lim, Y. B., and Jang, D. H. 2016. Literature review on the experimental designs in KSQM for 50 years. Journal of the Korean Society of Quality Management 44:245-264. https://doi.org/10.7469/JKSQM.2016.44.2.245
  11. Ossai, C., Boswell, B, and Davies, I. 2015. Pipeline failures in corrosive environments - A conceptual analysis of trends and effects. Engineering Failure Analysis 53:36-58. https://doi.org/10.1016/j.engfailanal.2015.03.004
  12. Qian, G., Niffenegger, M., Zhou, W., and Li, S. 2013. Effect of correlated input parameters on the failure probability of pipelines with corrosion defects by using FITNET FFS procedure. International Journal of Pressure Vessels and Piping 105:1-10. https://doi.org/10.1016/j.ijpvp.2013.02.002
  13. Zhang, P., Su, L., Qin, G., Kong, X., and Peng, Y. 2019. Failure probability of corroded pipeline considering the correlation of random variables. Engineering Failure Analysis 99:34-45. https://doi.org/10.1016/j.engfailanal.2019.02.002