A rule based fuzzy synthetic evaluation method for risk assessment in pipeline transport

References

• API Standard 1160-2001. Managing System Integrity for Hazardous Liquid Pipelines.
   Google Scholar
• ASME B31.8S-2004. Managing System Integrity of Gas Pipelines.
   Google Scholar
• Bai, Y.; Bai, Q. 2005. Subsea Pipelines and Risers. 2nd edition. Elsevier Science. 840 p.
   Google Scholar
• DeWolf, G. B. 2003. Process safety management in the pipeline industry: parallels and differences between the pipeline integrity management (IMP) rule of the office of pipeline safety and the PSM/RMP approach for process facilities, Journal of Hazardous Materials 104(1–3): 169–192. http://dx.doi.org/10.1016/j.jhazmat.2003.08.008
   PubMed Web of Science ®Google Scholar
• Doremami, N.; Afshar, A; Mohammadi, A. D. 2010. Hierarchical risk assessment in gas pipelines based on fuzzy aggregation, in 2nd International Conference on Reliability, Safety & Hazard (ICRESH–2010), 14–16 December 2010, Mumbai, India, 631–636. http://dx.doi.org/10.1109/ICRESH.2010.5779626
   Google Scholar
• Kishawy, H. A.; Gabbar, H. A. 2010. Review of pipeline integrity management practices, International Journal of Pressure Vessels and Piping 87(7): 373–380. http://dx.doi.org/10.1016/j.ijpvp.2010.04.003
   Web of Science ®Google Scholar
• Liu, Y.; Hu, H. 2012. Application of fuzzy logic to improve pipeline transport management, in ICPTT 2012: Better Pipeline Infrastructure for a Better Life, 19–22 October 2012, Wuhan, China, 1227–1239. http://dx.doi.org/10.1061/9780784412619.125
   Google Scholar
• Liu, Y.; Hu, H. 2011. Functional modeling for an integrated pipeline integrity management system using IDEF0 approach, in ICTIS 2011: Multimodal Approach to Sustained Transportation System Development: Information, Technology, Implementation, 30 June – 2 July 2011, Wuhan, China, 1848–1855. http://dx.doi.org/10.1061/41177(415)233
   Google Scholar
• Liu, Y.-T.; Hu, H.; Song, Y.-B. 2011. Pipeline integrity management system based on dynamic risk assessment, Journal of Shanghai Jiaotong University (Science) 45(5): 687–690 ( in Chinese).
   Google Scholar
• Markowski, A. S.; Mannan, M. S. 2009. Fuzzy logic for piping risk assessment (pfLOPA), Journal of Loss Prevention in the Process Industries 22(6): 912–927. http://dx.doi.org/10.1016/j.jlp.2009.06.011
   Google Scholar
• Muhlbauer, W. K. 2004. Pipeline Risk Management Manual. 3rd edition. Gulf Professional Publishing. 395 p.
   Google Scholar
• Palmer-Jones, R.; Turner, S; Hopkins, P. 2006. A new approach to risk based pipeline integrity management, in Proceedings of the 2006 International Pipeline Conference, Volume 2: Integrity Management; Poster Session; Student Paper Competition, 25–29 September 2006, Calgary, Alberta, Canada, 811–823. http://dx.doi.org/10.1115/IPC2006-10535
   Google Scholar
• PHMSA. 2012. Pipeline Incidents Reports. US Department of Transportation's Pipeline and Hazardous Materials Safety Administration (PHMSA). Available from Internet: http://primis.phmsa.dot.gov/comm/reports/safety/psi.html
   Google Scholar
• Rajani, B.; Kleiner, Y.; Sadiq, R. 2006. Translation of pipe inspection results into condition ratings using the fuzzy synthetic evaluation technique, Journal of Water Supply: Research and Technology – Aqua 55(1): 11–24. http://dx.doi.org/10.2166/aqua.2005.069
   Web of Science ®Google Scholar
• Ross, T. J. 2010. Fuzzy Logic with Engineering Applications. 3rd edition. Wiley. 606 p.
   Google Scholar
• Singh, M.; Markeset, T. 2009. A methodology for risk-based inspection planning of oil and gas pipes based on fuzzy logic framework, Engineering Failure Analysis 16(7): 2098–2113. http://dx.doi.org/10.1016/j.engfailanal.2009.02.003
   Web of Science ®Google Scholar
• Wang, K.-Q.; Wang, N; Zhang, C.; Lu, Z. 2008. Risk Characteristics of urban natural gas pipeline and improvement of the Kent method, China Safety Science Journal 18(9): 152–157.
   Google Scholar
• Willcocks, J.; Bai, Y. 2000. Risk-Based inspection and integrity management of pipeline systems, in The Tenth International Offshore and Polar Engineering Conference, 28 May – 2 June 2000, Seattle, Washington, USA, 285–294.
   Google Scholar
• Yuhua, D.; Datao, Y. 2005. Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis, Journal of Loss Prevention in the Process Industries 18(2): 83–88. http://dx.doi.org/10.1016/j.jlp.2004.12.003
   Web of Science ®Google Scholar
• Zhou, Q. Q.; Purvis, M; Kasabov, N. 1997. A Membership Function Selection Method for Fuzzy Neural Networks. Information Science Discussion Papers Series No 97/15. University of Otago, New Zealand. 6 p. Available from Internet: http://otago.ourarchive.ac.nz/handle/10523/1027
   Google Scholar