Probabilistic approach to determination of oil spill domains at port and sea water areas

• Autorzy: Dąbrowska E. , Kołowrocki K.

Identyfikatory

DOI

10.12716/1001.14.01.05

• Języki publikacji: EN

Abstrakty

EN

Maritime safety involves minimizing error in all aspects of the marine system. Human error has received much importance, being responsible for about 80% of the maritime accident worldwide. Currently, more attention has been focused to reduce human error in marine engine maintenance. On-board marine engine maintenance activities are often complex, where seafarers conduct maintenance activities in various marine environmental (i.e. extreme weather, ship motions, noise, and vibration) and operational (i.e. work overload and stress) conditions. These environmental and operational conditions, in combination with generic human error tendencies, results in innumerable forms of error. There are numerous accidents that happened due to the human error during the maintenance activities of a marine engine. The most severe human error results in accidents due to is a loss of life. Moreover, there are other consequences too such as delaying the productivity of marine operations which results in the financial loss. This study reviews methods that are currently available for identifying, reporting and managing human error in marine engine maintenance. As a basis for this discussion, authors provide an overview of approaches for investigating human error, and a description of marine engine maintenance activities and environmental and operational characteristics.

Słowa kluczowe

EN

oil spill; oil spill domains; determination of oil spill; Semi-Markov Model; sea water areas; port area; probabilistic approach; hydro-meteorological conditions

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2020
• Tom: Vol. 14, no. 1
• Strony: 51--58
• Opis fizyczny: Bibliogr. 16 poz., rys.

Twórcy

autor

Dąbrowska E.

• Gdynia Maritime University, Gdynia, Poland

autor

Kołowrocki K.

• Gdynia Maritime University, Gdynia, Poland

Bibliografia

• 1. Al-Rabeh A. H., Cekirge H. M. & Gunay N. A. 1989. Stochastic simulation model of oil spill fate and transport, Applied Mathematical Modelling, p. 322-329. - doi:10.1016/0307-904X(89)90134-0
• 2. Blokus A. & Kwiatuszewska-Sarnecka B. 2018. Reliability analysis of the crude oil transfer system in the oil port terminal. Proc. International Conference on Industrial Engineering and Engineering Management - IEEM, Bangkok, Thailand. - doi:10.1109/IEEM.2018.8607669
• 3. Bogalecka, M. & Kołowrocki, K. 2018. Minimization of critical infrastructure accident losses of chemical releases impacted by climate-weather change, Proc. International Conference on Industrial Engineering and Engineering Management - IEEM, Bangkok, Thailand. - doi:10.1109/IEEM.2018.8607506
• 4. Bogalecka, M. 2019. Consequences of Port and Maritime Critical Infrastructure Chemical Releases: Modeling – Identification – Prediction – Optimization – Mitigation, Elsevier (to appear).
• 5. Dąbrowska, E. 2019. Monte Carlo simulation approach to reliability analysis of complex systems, PhD Thesis, System Research Institute, Polish Academy of Science, Warsaw, Poland (under examination).
• 6. Dąbrowska, E. & Kołowrocki, K. 2019A. Modelling, identification and prediction of oil spill domains at port and sea water areas, Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, Vol. Issue 1, 43-58. - doi:10.1109/DT.2019.8813446
• 7. Dąbrowska E., Kołowrocki K.: Monte Carlo Simulation Approach to Determination of Oil Spill Domains at Port and Sea Water Areas. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 14, No. 1, doi:10.12716/1001.14.01.06, pp. 59-64, 2020
• 8. Fay J. A. 1971. Physical Processes in the Spread of Oil on a Water Surface. Proceedings of Joint Conference on Prevention and Control of Oil Spills, sponsored by American Petroleum Industry, Environmental Protection Agency, and United States Coast Guard. - doi:10.7901/2169-3358-1971-1-463
• 9. Fingas, M. 2016. Oil Spill Science and Technology, 2nd Edition, Elsevier.
• 10. Guze, S., Kolowrocki, K. & Mazurek, J. 2017. Modelling spread limitations of oil spills at sea. Proc. The 17th Conference of the Applied Stochastic Models and Data Analysis – ASMDA, London, UK
• 11. Guze S., Mazurek J. & Smolarek L. 2016. Use of random walk in two-dimensional lattice graphs to describe influence of wind and sea currents on oil slick movement. Journal of KONES Powertrain and Transport, Vol. 23, No. 2. - doi:10.5604/12314005.1213583
• 12. Huang J. C. 1983. A review of the state-of-the-art of oil spill fate/behavior models. International Oil Spill Conference Proceedings: February 1983, Vol. 1983, No. 1, p. 313-322. - doi:10.7901/2169-3358-1983-1-313
• 13. Information of the Nordic Council of Ministers in Kaliningrad. 2018. Risks of oil and chemical pollution in the Baltic Sea. Results and recommendations from the HELCOM's BRISK and BRISK-RU projects. Nordic Council of Ministers in Kaliningrad http://www.helcom.fi/Lists/Publications/.
• 14. NOAA. Trajectory Analysis Handbook. NOAA Hazardous Material Response Division. Seattle: WA, http://www.response.restoration.noaa.gov/.
• 15. Reed M., Johansen Ø., Brandvik P. J., Daling P., Lewis A., Fiocco R., Mackay D. & Prentki. 1999. Oil Spill Modeling towards the Close of the 20th Century: Overview of the State of the Art. Spill Science & Technology Bulletin, 3-16. - doi:10.1016/S1353-2561(98)00029-2
• 16. Spaulding M. L. 1988. A state-of-the-art review of oil spill trajectory and fate modeling. Oil and Chemical Pollution, Vol. 4, Issue 1, 39-55 - doi:10.1016/S0269-8579(88)80009-1

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).