Risk modelling and management in large-scale, distributed transportation systems

• Autorzy: Montewka J.
• Języki publikacji: EN

Abstrakty

EN

Large-scale distributed transportation systems can pose various risks in terms of fatalities, environmental pollution, or loss of property. In particular, accident where a vehicle carrying large number of passengers is involved may pose a high risk with respect to human casualties, moreover it will immediately raise a public and political concern. This is an issue in case of maritime transportation systems (MTS), as the biggest ships nowadays can carry up to 8500 people at once (m/s Oasis of the Seas). Thereby lot of effort has been put to increase safety of ships carrying passengers; however the holistic approach to model and manage the risk existing in the MTS is still missing. This paper makes an attempt to fill this gap, by presenting a data-driven model evaluating risk level in the existing MTS and by introducing a systematic methodology for mitigating the risk. Moreover the MTS operating in the Gulf of Finland under non-ice conditions is addressed, where heavy passenger traffic is observed.

Słowa kluczowe

EN

risk; maritime transport; transportation systems; F-N; RoPax

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2012
• Tom: Vol. 3, No. 1
• Strony: 113--122
• Opis fizyczny: Bibliogr. 40 poz., rys., tab., wykr.

Twórcy

autor

Montewka J.

• Aalto University, Department of Applied Mechanics, Marine Technology, Espoo, Finland

Bibliografia

• [1] Antao, P. & Guedes-Soares C. (2006). Fault-tree models of accident scenarios of ropax vessels. International Journal of Automation and Computing 3, 107-116.
• [2] Berg, H-P. (2010). Risk management: procedures, method and experiences, RT&A 2(17) Vol.1, 79-95.
• [3] Darwiche, A. (2009). Modeling and Reasoning with Bayesian Networks. Cambridge University Press.
• [4] Drużdzel, M. & Genie, A. (1999). Development environment for graphical decision-analytic models., in: A. M. I. Association (Ed.), Proceedings of the 1999 Annual Symposium of the American Medical Informatics Association (AMIA-1999), Washington, D.C., 1206.
• [5] Drużdzel, M. & van der Gaag L. (2000). Building probabilistic networks: ”Where do the numbers come from?” guest editors’ instruction. IEEE Transactions on Knowledge and Data Engineering 12, 481-486.
• [6] Gerigk, M. (2010). A method of risk and safety assessment during the ship salvage using the hazard, release and consequence analysis. Journal of KONBIN 13, 165-176.
• [7] Goerlandt, F. & Kujala, P. (2011). Traffic simulation based ship collision probability modeling. Reliability Engineering & System Safety 96, 91-107.
• 8] Goerlandt, F., Ståhlberg, K. & Kujala, P. (2012). Influence of impact scenario models on collision risk analysis. Ocean Engineering 47, 74-87.
• [9] Grabowski, M., Merrick, J.R.W., Harrold, J.R., Mazzuchi, T.A. & van Dorp, J.D. (2000). Risk modeling in distributed, large-scale systems. IEEE Transactions on Systems Man and Cybernetics. Part A Systems and Humans 30, 651-660.
• [10] Guarin, L., Konovessis, D. & Vassalos, D. (2009). Safety level of damaged ropax ships: Risk modelling and cost-effectiveness analysis. Ocean Engineering 36, 941-951.
• [11] IMO, Guidelines for formal safety assessment (FSA) for use in the IMO rule-making process, 2002. MSC/Circ.1023; MEPC/Circ.392.
• [12] Kobylinski, L. (2008). Stability and safety of ships: holistic and risk approach. Reliability & Risk Analysis: Theory & Applications 1, 95-105.
• [13] Konovesis, D., Vassalos, D., & Mermiris, G. (2008). Risk analysis for RoPax vessels, WMU Journal of Maritime Affairs 7, 109-131.
• [14] Konovesis, D. & Vassalos, D. (2008). Risk evaluation for RoPax vessels. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 222, 13-26.
• [15] Konovesis, D. & Vassalos, D.(2007). Risk-based design for damage survivability of passenger roro vessels. International Shipbuilding Progress 54, 129-144.
• [16] Kontkanen, P., Myllymaki, P., Silander, T. & Tirri, H. Comparing predictive inference methods for discrete domains, in: Sixth International Workshop on Artificial Intelligence and Statistics, Ft. Lauderdale, USA, 311-318.
• [17] Langseth, H. & Portinale, L. (2007). Bayesian networks in reliability. Reliability Engineering and System Safety 92, 92-108.
• [18] Li S., Meng, Q. & Qu, X. (2012). An overview of maritime waterway quantitative risk assessment models. Risk Analysis 32, 496-512.
• [19] Madsen, A., Lang, M., Kjrulff, U. & Jensen, F. (2003). The hugin tool for learning Bayesian networks. iIn: T. Nielsen, N. Zhang (Eds.), ECSQARU 2003, LNAI 2711, Springer-Verlag Berlin Heidelberg, 2003, 594-605.
• [20] Mains, C. (2001). Updated damage statistics on collision and grounding. Report 1-11-D-2001-011, Germanisher Lloyd.
• [21] Mermiris, G., Konovessis, D. & Vassalos, D. (2008). First-principles collision risk analysis of a ropax vessel. Proceedings of 4th International ASRANet Colloquium.
• [22] Montewka, J., Ehlers, S., Goerlandt, F., Polic, D., Hinz, T., Tabri, K. & Kujala, P. (2012). Modelling the consequences of an accident to a RoPax vessel using a Bayesian Belief Network. Reliability Engineering and System Safety - paper accepted.
• [23] Myllymäki, P., Silander, T., Tirri, H. & Uronen, P. (2002). B-course: A web-based tool for bayesian and causal data analysis. International Journal on Artificial Intelligence Tools 11, 369-387.
• [24] Otto, S., Pedersen, P. T., Samuelides, M. & Sames, P.C. (2002). Elements of risk analysis for collision and grounding of a roro passenger ferry. Marine Structures 15, 461-474.
• [25] Papanikolaou, A.E. (2009). Risk-Based Ship Design Methods. Tools and Applications. Springer Berlin Heidelberg, 2009.
• [26] Papanikolaou, A. & Eliopoulou, E. (2008). On the development of the new harmonised damage stability regulations for dry cargo and passenger ships. Reliability Engineering and System Safety 93, 1305-1316.
• [27] Papanikolaou, A., Mains, C., Rusås, S., Szalek, R., Tsakalakis, N., Vassalos, D. & Zaraphonitis, G. (2010). Goalds - goal based damage stability. Proceedings of the 11th International Ship Stability Workshop, 2010, MARIN, Wageningen, 46-57.
• [28] Pedersen, P.T. (2010). Review and application of ship collision and grounding analysis procedures. Marine Structures 23, 241-262.
• [29] Roelen, A.L.C. (2008). Causal risk models of air transport: comparison of user needs and model capabilities. IOS Press, 2008.
• [30] SAFEDOR, Risk evaluation criteria, Deliverable D4.5.2, Det Norske Veritas AS, 2005.Available online: http://www.safedor.org/resources/SAFEDOR-D04.05.02-2005-10-21-DNV-RiskEvaluation Criteria-rev-3.pdf.
• [31] Santos, T.A. & Guedes-Soares, C. (2009). Numerical assessment of factors affeccting the survivability of damaged ro-ro ships in waves. Ocean Engineering 36, 797-809.
• [32] Skjong, R., Vanem, E, Rusås, S. & Olfusen, O. (2006). Holistic and risk based approach to collision damage stability of passenger ships. Proceedings of 9th conference on stability of ships and ocean vehicles, Rio de Janeiro.
• [33] Smid, J., Verloo, D., Barker, G. & Havelaar, A. (2010). Strengths and weaknesses of monte-carlo simulation models and Bayesian belief networks in microbial risk assessment. International Journal of Food Microbiology 139, Supplement S57-S63.
• [34] Spanos, D. & Papanikolaou, A. (2010). On the time dependent survivability of ropax ships. Proceedings of the 11th International Ship Stability Workshop, MARIN, Wageningen, 143-147.
• [35] Szwed, P. (2011). Risk factors and theory building: a study to improve passenger vessel safety. WMU Journal of Maritime Affairs 10, 183-208.
• [36] Uusitalo, L. (2007). Advantages and challenges of bayesian networks in environmental modeling. Ecological Modelling 203, 312-318.
• [37] van Dorp, J.R. & Merrick, J.R.W. (2011). On a risk management analysis of oil spill riskusing maritime transportation system simulation. Annals of Operations Research 187, 249-277.
• [38] Vanem, E. (2012). Principles for setting risk acceptance criteria for safety critical activities. Berenguer, Grall, Guedes Soares (Eds.), Advances in Safety and Risk Management, Taylor & Francis, London, 1741-1751.
• [39] Vanem, E., Rusås, S., Skjong, R. & Olufsen, O. (2007). Collision damage stability of passenger ships: Holistic and risk-based approach, International Shipbuilding Progress 54, 323-337.
• [40] Vanem, E. & Skjong, R. (2004). Collision and grounding of passenger ships - risk assessment and emergency evacuations, in: SNAJ (Ed.). Proceedings of the 3rd International Conference on Collision and Grounding of Ships, 195-202.