Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Monte Carlo simulation method of oil spill domains determination based on the probabilistic approach to the solution of this problem is proposed. A semi-Markov model of the process of changing hydro-meteorological conditions is constructed and its parameters are defined. The general stochastic model of oil spill domain movement for various hydro-meteorological conditions is described. Monte Carlo simulation procedure is created and applied to generating the process of changing hydro-meteorological conditions and the prediction of the oil spill domain movement impacted by these changes conditions.
Rocznik
Tom
Strony
59--64
Opis fizyczny
Bibliogr. 23 poz., rys.
Twórcy
autor
- Gdynia Maritime University, Gdynia, Poland
autor
- 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.
- 2. 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.
- 3. Chen, H, Li, D. & Li, X. 2007. Mathematical modeling of oil spill on the sea and application of the modeling in Daya Bay, Journal of Hydrodynamics, Ser. B: Elsevier, (19)3, 282291.
- 4. 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).
- 5. 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, 10(1), 43-58.
- 6. Dąbrowska, E. & Kołowrocki, K. 2019B. Probabilistic Approach to Determination of Oil Spill Domains at Port and Sea Water Areas, Proc. of TransNav Conference 2019
- 7. Dąbrowska, E. & Soszyńska-Budny, J. 2018. Monte Carlo simulation forecasting of maritime ferry safety and resilience, Proc. International Conference on Industrial Engineering and Engineering Management - IEEM, Bangkok, Thailand
- 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
- 9. Fingas, M. 2016. Oil Spill Science and Technology, 2nd Edition, Elsevier
- 10. Grabski, F., Jaźwiński, J. .2009. Funkcje o losowych argumentach w zagadnieniach niezawodności, bezpieczeństwa i logistyki. Wydawnictwa Komunikacji i Łączności: Warszawa.
- 11. 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
- 12. 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.
- 13. 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.
- 14. Kim, T., Yang , C.-S., Ouchi, K. & Oh, Y. 2013. Application of the method of moment and Monte-Carlo simulation to extract oil spill areas from synthetic aperture radar images, OCEANS - San Diego, 1-4.
- 15. Kołowrocki, K. 2014. Reliability of large and complex systems, Elsevier.
- 16. Kołowrocki, K. & Soszyńska-Budny, J. 2011. Reliability and Safety of Complex Technical Systems and Processes: Modelling - Identification - Prediction - Optimization, London, Dordrecht, Heildeberg, New York: Springer.
- 17. Kuligowska, E. 2017. Monte Carlo Simulation of Complex System Reliability Evaluation. Chapter in Monograph: Current research in mathematical and computer sciences. Red. A. Lecko, Wydawnictwo UWM: Olsztyn, 139-152.
- 18. Kuligowska, E. 2018. Monte Carlo simulation of climateweather change process at maritime ferry operating area, Technical Sciences, University of Warmia and Mazury in Olsztyn, 1(21), 5-17.
- 19. Law, A. M. & Kelton, W. D. 2000. Simulation Modeling and Analysis, 3rd ed., McGraw Hill.
- 20. NOAA. Trajectory Analysis Handbook. NOAA Hazardous Material Response Division. Seattle: WA, http://www.response.restoration.noaa.gov/.
- 21. Rao, M. S., & Naikan, V. N. A. 2016. Review of simulation approaches in reliability and availability modeling, International Journal of Performability Engineering, 12 (4), 369-388.
- 22. Zio, E. & Marseguerra, M. 2002. Basics of the Monte Carlo Method with Application to System Reliability, LiLoLe.
- 23. 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.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e5519f11-7a17-4744-b0cd-f8b1b4c0f7bf