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Proposal of new measures for risk assessment in navigation – a case study of the M/V Cosco Busan accident

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study discusses the marine accident involving the Cosco Busan, the container ship that hit the base of the Delta Tower of the San Francisco-Oakland Bay Bridge in November 2007. An analysis of the elements resulting in the accident and its consequences has been carried out, followed by an analysis of the navigational risk using mathematical and tabular values. Mathematical values refer to the navigational risk in a specific sailing area, while tabular values refer to the navigational risk using a risk assessment. The main goal of this research was to identify and propose new measures that are correlated with a risk assessment. These measures should be applied in areas where an accident takes place so that future marine accidents can be reduced.
Rocznik
Strony
9--15
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
  • University of Split, Faculty of Maritime Studies
  • University of Zagreb; Faculty of Transport and Traffic Science
autor
  • University of Split, Faculty of Maritime Studies
  • University of Split, Faculty of Maritime Studies
Bibliografia
  • 1. Brčić, D., Kos, S. & Žuškin, S. (2015) Navigation with ECDIS: Choosing the Proper Secondary Positioning Source. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation 9, 3, doi: 10.12716/1001.09.03.03.
  • 2. Coraddu, A., Oneto, L., Navas De Maya, B. & Kurt, R. (2020) Determining the most influential human factors in maritime accidents: A data-driven approach. Ocean Engineering 211, 1, doi: 10.1016/j.oceaneng.2020.107588.
  • 3. Eliopoulou, E., Papanikolaou, A. & Voulgarellis, M. (2016) Statistical analysis of ship accidents and review of safety level. Safety Science 85, pp. 282–292, doi: 10.1016/j. ssci.2016.02.001.
  • 4. Fan, S., Blanco-Davis, E., Yang, Z., Zhang, J. & Yan, X. (2020) Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network. Reliability Engineering and System Safety 203, doi: 10.1016/j. ress.2020.107070.
  • 5. Fan, S., Zhang, J., Blanco-Davis, E., Yang, Z. & Yan, X. (2020) Maritime accident prevention strategy formulation from a human factor perspective using Bayesian Networks and TOPSIS. Ocean Engineering 210, doi: 10.1016/j. oceaneng.2020.107544.
  • 6. Felski, A. & Jaskolski, K. (2013) The Integrity of Information Received by Means of AIS During Anti-collision Manoeuvring. TransNav, The International Journal on Marine Navigation and Safety of Sea Transportation 7, 1, pp. 95– 100, doi: 10.12716/1001.07.01.12.
  • 7. Grech, M.R. (2018) Risk perception. In: Oltedal, H.A. & Lützhöft, M. (eds) Managing Maritime Safety. London: Routledge, doi: 10.4324/9780203712979.
  • 8. He, J. & Feng, M. (2016) Based on ECDIS and AIS Ship Collision Avoidance Warning System Research. In: Proceedings – 8th International Conference on Intelligent Computation Technology and Automation, ICICTA 2015, doi: 10.1109/ICICTA.2015.69.
  • 9. Heikkilä, M. (2006) HFS06Heikkila. Marine Accident Investigation, Maritime Safety Through Investigations and Co-Operation, Human Factors & Safety Seminar in Espoo, 13th February 2006. Available at: https://www.scribd.com/ document/201932852/HFS06Heikkila [Accessed: October 20, 2020].
  • 10. IMO (2004a) Annex 26 Draft MSC-MEPC Circular [MSC-MEPC.2/Circ.12/Rev.2] [Date of Approval] Revised Guidelines for Formal Safety Assessment (FSA) for Use in the IMO Rule-Making Process.
  • 11. IMO (2004b) Casualty Analysis Procedure; FSI 17/WP.1, annex 2. Available from: https://wwwcdn.imo.org/localre sources/en/OurWork/MSAS/Documents/CASUALTY%20 ANALYSIS%20PROCEDURE.pdf [Accessed: October 20, 2020].
  • 12. Kuehmayer, J.R. (2008) Marine Accident and Casualty Investigation Boards. Available from: www.amem.at/pdf/ AMEM_Marine_Accidents.pdf [Accessed: October 20, 2020].
  • 13. Macduff, T. (1974) The Probability of Vessel Collisions. Ocean Industry 9, 9, pp. 144–148.
  • 14. Mao, S., Tu, E., Zhang, G., Rachmawati, L., Rajabally, E. & Huang, G.-B. (2018) An Automatic Identification System (AIS) Database for Maritime Trajectory Prediction and Data Mining. In: Cao, J., Cambria, E., Lendasse, A., Miche, Y. & Vong, C. (eds) Proceedings of ELM-2016. Proceedings in Adaptation, Learning and Optimization, vol 9. Springer, Cham, https://doi.org/10.1007/978-3-319-57421-9_20.
  • 15. Medić, D., Lušić, Z. & Bošnjak, R. (2019) Comparative Analysis of the Maritime Venture Risk and the Cost of Averting a Fatality in the Republic of Croatia. Nase More 66(2), pp. 62–69, doi: 10.17818/NM/2019/2.3.
  • 16. National Transportation Safety Board (2009) Allision of Hong Kong-Registered Containership M/V Cosco Busan with the Delta Tower of the San Francisco-Oakland Bay Bridge. San Francisco, California, November 7, 2007. Accident Report, NTSB/MAR-09/01, PB2009-916401.
  • 17. Navas de Maya, B. & Kurt, R.E. (2020) Marine accident learning with Fuzzy Cognitive Maps: A method to model and weight human-related contributing factors into maritime accidents. Ships and Offshore Structures, doi: 10.1080/17445302.2020.1843843.
  • 18. Rutkowski, G. (2018) ECDIS Limitations, Data Reliability, Alarm Management and Safety Settings Recommended for Passage Planning and Route Monitoring on VLCC Tankers. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation 12, 3, pp. 483–490, doi: 10.12716/1001.12.03.06.
  • 19. Salihoglu, E. & Bal Beşikçi, E. (2021) The use of Functional Resonance Analysis Method (FRAM) in a maritime accident: A case study of Prestige. Ocean Engineering 219, doi: 10.1016/j.oceaneng.2020.108223.
  • 20. Wennink, C.J. (1992) Collision and Grounding Risk Analysis for Ships Navigating in Confined Waters. Journal of Navigation, 45(1), pp. 80–90. doi: 10.1017/S0373463300010493.
  • 21. Zhang, W., Goerlandt, F., Montewka, J. & Kujala, P. (2015) A method for detecting possible near miss ship collisions from AIS data. Ocean Engineering 107, pp. 60–69, doi: 10.1016/j.oceaneng.2015.07.046.
  • 22. Zhang, Y., Sun, X., Chen, J. & Cheng, C. (2021) Spatial patterns and characteristics of global maritime accidents. Reliability Engineering & System Safety 206, doi: 10.1016/j. ress.2020.107310.
  • 23. Zhao, J., Price, W.G., Wilson, P.A. & Tan, M. (1995) The Uncertainty and Uncoordination of Mariners’ Behaviour in Collision Avoidance at Sea. Journal of Navigation 48, 3, pp. 425–435, doi: 10.1017/S0373463300012911.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6f96a68d-6e00-46de-a341-7a8c9b926264
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