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Short-term forecasting of accidental oil spill movement in harbours

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Konferencja
15th Summer Safety & Reliability Seminars - SSARS 2021, 5-12 September 2021, Ciechocinek, Poland
Języki publikacji
EN
Abstrakty
EN
The general model of oil spill movement forecasting based on a probabilistic approach is proposed. A semi-Markov model of the process of changing hydro-meteorological conditions is constructed. The method of oil spill domain determination for various hydro-meteorological conditions is recommended. Moreover, Monte Carlo simulation procedure for predicting the oil spill domain movement is proposed. The procedure is practically applied for Gdynia and Karlskrona ports' water areas.
Twórcy
Bibliografia
  • Bogalecka, M. 2020. Consequences of Maritime Critical Infrastructure Accidents. Environmental Impacts. Modeling - Identification - Prediction - Optimization - Mitigation. Elsevier, Amsterdam - Oxford - Cambridge.
  • Bogalecka, M. & Kołowrocki, K. 2015a. Modelling, identification and prediction of environment degradation initial events process generated by critical infrastructure accidents. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars 6(1), 47-66.
  • Bogalecka, M. & Kołowrocki, K. 2015b. The process of sea environment threats generated by hazardous chemicals release. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars 6(1), 67-74.
  • Bogalecka, M. & Kołowrocki, K. 2018. Prediction of critical infrastructure accident losses of chemical releases impacted by climate-weather change. Proceeding of 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Institute of Electrical and Electronics Engineers, Bangkok, 788-792.
  • Dąbrowska, E. 2020. Safety analysis of car wheel system impacted by operation process. K. Kołowrocki et al. (Eds.). Safety and Reliability of Systems and Processes, Summer Safety and Reliability Seminar 2020. Gdynia Maritime University, Gdynia, 61–76.
  • Dąbrowska, E. & Kołowrocki, K. 2019.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 Seminars10(1), 43-58.
  • Fingas, M. 2016. Oil Spill Science and Technology. Elsevier.
  • GMU (Gdynia Maritime University) Safety Interactive Platform, http://gmu.safety.umg.edu.pl/ (accessed 13 Feb 2020).
  • Grabski, F. 2014. Semi-Markov Processes: Application in System Reliability and Maintenance. Elsevier, Amsterdam - Boston - Heidelberg - London - New York - Oxford - Paris - San Francisco - Sydney - Tokyo.
  • Kołowrocki, K. 2014. Reliability of Large and Complex Systems, Elsevier, Amsterdam - Boston - Heidelberg - London - New York - Oxford - Paris - San Francisco - Sydney - Tokyo.
  • Kuligowska, E. 2018. Monte Carlo simulation of climate-weather change process at maritime ferry operating area.Technical Sciences, University of Warmia and Mazury in Olsztyn 1(21), 5-17.
  • Limnios, N. & Oprisan, G. 2001. Semi-Markov Processes and Reliability. Birkhauser, Boston.
  • Marseguerra, M. & Zio, E. 2002. Basics of the Monte Carlo Method with Application to System Reliability. LiLoLe.
  • 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.
  • Torbicki, M. 2018. Longtime prediction of climate-weather change influence on critical infrastructure safety and resilience. Proceeding of 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Institute of Electrical and Electronics Engineers, Bangkok, 996-1000.
  • Xue, J. 1985. On multi-state system analysis. IEEE Transactions on Reliability 34, 329-337.
  • Xue J. & Yang, K. 1995a. Dynamic reliability analysis of coherent multi-state systems. IEEE Transactions on Reliability 4(44), 683-688.
  • Xue J. & Yang, K. 1995b. Symmetric relations in multi-state systems. IEEE Transactions on Reliability 4(44), 689-693.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-1b93b3e5-33d4-4460-9154-6424b2872949
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