A SOMNN Model for Transport Risk Assessment of Hazardous Materials by Rail

Abstract:

Railway siding for transport of hazardous materials is an important way in transporting of hazardous materials in China and they often result in catastrophic consequences for environment and society with a great deal of economic loss. Risk assessment for railway siding is an effective way to ensure its operational safety. This paper focuses on the application of self-organizing neural network (SOMNN) to assess the risk of the railway siding operational system and classify its risk factors. In this work, the system analysis method based on the characteristics of railway siding for hazardous materials is first used to establish the transport risk assessment index system. A comprehensive risk assessment model of railway siding has been developed with the SOMNN theory to improve present methods available for risk assessment of rail siding’s safety. A field case study about 15 railway slides for transporting of oil in Jilin broach center of China National Petroleum Corporation is undertaken so that the effectiveness of the proposed approach could be verified. The result is in line with the actual situation and indicates that this method used is feasible and rational. This model provides a new method for transport risk assessment of hazardous materials by rail. The method is also proved more efficient for both risk assessment and safety management. The work specified in this paper can be as reference to the assessment work in China.

• Periodical: Advanced Materials Research (Volume 629)
• Pages: 778-783
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.629.778
• Online since: December 2012
• Authors: Ke Pan, Shouan Guan
• Keywords: Multi-Attribute Risk Assessment, Railway Siding for Transport of Hazardous Materials, Risk Pattern Classification, SOMNN

References

[1] Adrian V. Gheorghea, Ju¨rg Birchmeiera, Dan Vamanu, et al. Comprehensive risk assessment for rail transportation of dangerous goods: a validated platform for decision support. Reliability Engineering & System Safety, 2005, 88(3): 247-272.

DOI: 10.1016/j.ress.2004.07.017

[2] S.M. Godoy, A.S.M. Santa Cruz, N.J. Scenna. STRRAP system—A software for hazardous materials risk assessment and safe distances calculation. Reliability Engineering & System Safety, 2007, 92(7): 847-857.

DOI: 10.1016/j.ress.2006.02.012

[3] Melissa T. Baysari, Carlo Caponecchia, Andrew S. McIntosh, et al. Classification of errors contributing to rail incidents and accidents: A comparison of two human error identification techniques. Safety Science, 2009, 47(7): 948-957.

DOI: 10.1016/j.ssci.2008.09.012

[4] Roberto Bubbico, Sergio Di Cave, Barbara Mazzarotta. Risk analysis for road and rail transport of hazardous materials: a simplified approach. Journal of Loss Prevention in the Process Industries, 2004, 17(6): 483-488.

DOI: 10.1016/j.jlp.2004.08.011

[5] A.V. van der Vlies, S.I. Suddle. Structural measures for a safer transport of hazardous materials by rail: The case of the basic network in The Netherlands. Safety Science, 2008, 46(1): 119-131.

DOI: 10.1016/j.ssci.2006.10.006

[6] Andrea Grassi, Rita Gamberini, Cristina Mora, Bianca Rimini. A fuzzy multi-attribute model for risk evaluation in workplaces. Safety Science, 2009, 47(5): 707-716.

DOI: 10.1016/j.ssci.2008.10.002

[7] Adam S. Markowski, M. Sam Mannan, Agata Bigoszewska. Fuzzy logic for process safety analysis. Journal of Loss Prevention in the Process Industries, 2009, 22(6): 695-702.

DOI: 10.1016/j.jlp.2008.11.011

[8] Markowski A S, Mannan M S, Kotynia A, et al. Uncertainty aspects in process safety analysis. Journal of Loss Prevention in the Process Industries, 2010, 23 (3): 446–454.

DOI: 10.1016/j.jlp.2010.02.005

[9] Ali Asgary, Ali Sadeghi Naini, Jason Levy. Modeling the risk of structural fire incidents using a self-organizing map. Fire Safety Journal, 2012, 49: 1-9.

DOI: 10.1016/j.firesaf.2011.12.007

[10] Muriel Gevrey, Sue Worner, Nikola Kasabov, et al. Estimating risk of events using SOM models: A case study on invasive species establishment . Ecological Modelling, 2006, 197（3-4）: 361-372.

DOI: 10.1016/j.ecolmodel.2006.03.032

[11] Shanyu Y, Yuxin J, Ke P. Application of SVM in Safety Evaluation for Oilery Railway Siding and Ancillary Facilities. Journal of Dalian Jiaotong University, 2010, 31(5): 86-31(in Chinese).