Fuzzy logic for pipelines risk assessment


Ali Alidoosti, Ali Jamshidi, Siamak Haji Yakhchali, Mohammad Hossein Basiri, Ramin Azizi and Abdolreza Yazdani-Chamzini


Pipelines systems are identified to be the safest way of transporting oil and natural gas. One of the most important aspects in developing pipeline systems is determining the potential risks that implementers may encounter. Therefore, risk analysis can determine critical risk items to allocate the limited resources and time. Risk Analysis and Management for Critical Asset Protection (RAMCAP) is one of the best methodologies for assessing the security risks. However, the most challenging problem in this method is uncertainty. Therefore, fuzzy set theory is used to model the uncertainty. Thus, Fuzzy RAMCAP is introduced in order to risk analysis and management for pipeline systems. Finally, a notional example from pipeline systems is provided to demonstrate an application of the proposed methodology.


DOI: j.msl.2012.04.017

Keywords: RAMCAP ,Risk management ,Fuzzy logic ,Pipeline

How to cite this paper:

Alidoosti, A., Jamshidi, A., Yakhchali, S., Basiri, M., Azizi, R & Yazdani-Chamzini, A. (2012). Fuzzy logic for pipelines risk assessment.Management Science Letters, 2(5), 1707-1716.


References

Acosta, H., Wu, D., & Forrest, B. M. (2010). Fuzzy experts on recreational vessels. risk modelling approach for marine invasions. Ecological Modelling, 221, 850–863.

Alidoosti, A., Yazdani, M., & Basiri, M., (2011). Risk assessment of critical asset using fuzzy inference system. Risk Management, 14, 77-91.

American Petroleum Institute (API), (2004). National Petrochemical and Refiners Association (NPRA). Security Vulnerability Assessment Methodology for the Petroleum and Petrochemical Industries (Second Edition). American Petroleum Institute.

ASME Innovative Technologies Institute, (2009). All-Hazards risk and resilience. ASME, New York.

Aydin, A. (2004). Fuzzy set approaches to classification of rock masses. Engineering Geology, 74, 227–245.Azadeh, A., Fam, I., M., Khoshnoud, M., & Nikafrouz, M. (2008). Design and implementation of a fuzzy expert system for performance assessment of an integrated health, safety, environment (HSE) and ergonomics system: The case of a gas refinery. Information Sciences, 178, 4280–4300.

Bajpai, Sh., Sachdeva, A., & Gupta, J. P. (2010). Security risk assessment: Applying the concepts of fuzzy logic. Journal of Hazardous Materials, 173, 258–264.

Baker, A. B., Eagan, R. J., Falcone, P. K., & Harris, J. M. (2002). A Scalable Systems Approach for Critical Infrastructure Security. Sandia National Laboratories.Bartenev, A.M., Gelfand, B.E., Makhviladze, G.M., & Roberts, J.P. (1996). Statistical analysis of accidents on the Middle Asia-Centre gas pipelines. Journal of Hazardous Materials, 46, 57–69.

Buyukbingol, E., Sisman, A., Akyildiz, M., Alparslan, A., & Adejare, A. (2007). Adaptive neuro-fuzzy inference system (ANFIS): A new approach to predictive modeling in QSAR applications: A study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists. Bioorganic & Medicinal Chemistry, 15, 4265–4282.

Cagno, E., Caron, F., Mancini, M., & Ruggeri, F. (2000). Using AHP in determining the prior distributions on gas pipeline failures in a robust Bayesian approach. Reliability Engineering & System Safety, 67, 275–84.Celikyilmaz, A., & Türksen, I. B. (2009). Modeling Uncertainty with Fuzzy Logic; With Recent Theory and Applications. Springer-Verlag Berlin Heidelberg.

Chen, Sh. M., & Chen, J. H. (2009). Fuzzy risk analysis based on ranking generalized fuzzy numbers with different heights and different spreads. Expert Systems with Applications, 36, 6833–6842.

Cox, L.A.J. (2009). Risk Analysis of Complex and Uncertain Systems. Springer Science. Business Media, LLC.

Douglas, J. L. (2006). The Security Risk Assessment Handbook; A Complete Guide for Performing Security Risk Assessments, Taylor & Francis Group. LLC.Dziubnski, M., Fratczak, M., & Markowski, A.S. (2006). Aspects of risk analysis associated with major failures of fuel pipelines. Journal of Loss Prevention Process Industries,19,399–408.

Elsayed, T. (2009). Fuzzy inference system for the risk assessment of liquefied natural gas carriers during loading/ off loading at terminals. Applied Ocean Research, 31, 179_185.Executive Order 13010. Critical Infrastructure Protection-Federal register. 61(138), 37347-37350.

Feng, L. H., & Luo, G.Y. (2009). Analysis on fuzzy risk of landfall typhoon in Zhejiang province of China. Mathematics and Computers in Simulation, 79, 3258–3266.

Flores, W. C., Mombello, E., Jardini, J. A., & Rattá, G. (2009). Fuzzy risk index for power transformer failures due to external short-circuits. Electric Power Systems Research, 79, 539–549.

Fouladgar, M.M., Yazdani-Chamzini, A., & Zavadskas, E.K. (2012b). Risk Evaluation of Tunneling Projects. Archives of civil and mechanical engineering, 12, 1-12.

Henselwood, F., & Phillips, G. (2006). A matrix-based risk assessment approach for addressing linear hazards such as pipelines. Journal of Loss Prevention Process Industry,19, 433–41.

Horgby, P. (1998). Risk Classification by Fuzzy Inference. The Geneva Papers on Risk and Insurance Theory, 23, 63–82.

Jo, Y.D., & Ahn, B.J. (2002). Analysis of hazard areas associated with high- pressure natural-gas pipelines. Journal of Loss Prevention Process Industries, 15, 179–88.Jo, Y.D., & Ahn, B.J. (2005). A method of quantitative risk assessment for transmission pipeline carrying natural gas. Journal of Hazardous Materials, 123, 1–12.

Liu, K., Hao, J., & Pang, Y. (2009). Algorithm Research on Project Risk Fuzzy Evaluation. The First International Workshop on Database Technology and Applications, 160-164.

Markowski, A. S., & Mannan, M. S. (2008) Fuzzy risk matrix. Journal of Hazardous Materials. 159, 152–157.

Markowski, A. S., & Mannan, M. S. (2009). Fuzzy logic for piping risk assessment (pfLOPA). Journal of Loss Prevention in the Process Industries, 22, 921–927.

Moore, D., Fuller, B., Hazzan, M., William, J., (2007). Development of a security vulnerability assessment process for the RAMCAP chemical sector. Journal of Hazardous Materials, 142, 689–694.

Nieto-Morote, A., & Ruz-Vila, A. (2011). Fuzzy approach to construction project risk assessment. International Journal of Project Management, 29(2), 220-231.

Papadakis, GA., Porter, S., & Wettig J. EU, (1999). initiative on the control of major accident hazards arising from pipelines. Journal of Loss Prevention in the Process Industries,12, 85–90.

Rehana, S., & Mujumdar, P., P., (2009). An imprecise fuzzy risk approach for water quality management of a river system. Journal of Environmental Management, 90, 3653–3664.

Ross, J. T. (1995). Fuzzy Logic with Engineering Applications. McGraw-Hill Inc, New York.

Sadiq, R., & Husain, T. (2005). A fuzzy-based methodology for an aggregative environmental risk assessment: a case study of drilling waste. Environmental Modelling & Software, 20, 33-46.

Sadiq, R., Kleiner, Y., & Rajani, B., (2007). Risk analysis using fuzzy logic and evidential reasoning. Water quality failures in distribution networks. Risk Analysis, 27, 1381-1394.

Sklavounos, S., Rigas, F., (2006). Estimation of safety distances in the vicinity of fuel gas pipelines. Journal of Loss Prevention in the Process Industries, 19, 24–31.

Vesely, W. E. (1983). The Façade of Probabilistic Risk Analysis: Sophisticated Computation Does Not Necessarily Imply Credibility. Proceeding annual reliability and maintainability symposium.Wang, X. (1994). Adaptive Fuzzy Systems and Control – Design and Stability Analysis. Prentice Hall.Wang, Y. M., & Elhag, T. (2007). A fuzzy group decision making approach for bridge risk assessment. Computers & Industrial Engineering, 53, 137–148.

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, 83–88.

Zhao Y, Xihong L, & Jianbo L. (2007). Analysis on the diffusion hazards of dynamic leakage of gas pipeline. Reliability Engineering & System Safety, 92, 47–53.