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Języki publikacji
Abstrakty
The great-circle is the shortest distance between two points on the surface of the earth. When planning a ship’s sailing route (waypoints and forward speeds) for a specific voyage, the great circle route is commonly considered as a reference route, especially for ocean-crossing seaborne transport. During the planning process, the upcoming sea weather condition is one of the most important factors affecting the ship’s route optimization/planning results. To avoid encountering harsh conditions, conventional routing optimization algorithms, such as Isochrone method and Dynamic Programming method, have been developed/implemented to schedule a ship’s optimal routes by selecting waypoints around the great circle reference route based on the ship’s operational performances at sea. Due to large uncertainties in sea weather forecast that used as inputs of these optimization algorithms, the optimized routes may have worse performances than the traditional great circle sailing. In addition, some shipping companies are still sailing in or making charting contracts based on the great circle routes. Therefore, in this study, a new optimization algorithm is proposed to consider the voluntary speed reduction with optimal speed configuration along the great circle course. The efficiency of this method is investigated by comparing these two methods for optimal route planning with respect to ETA and minimum fuel consumption. A container ship sailing in the North Atlantic with full-scale performance measurements are employed as the case study vessels for the comparison.
Rocznik
Tom
Strony
301--308
Opis fizyczny
Bibliogr. 16 poz., rys., tab.
Twórcy
autor
- Chalmers University of Technology, Gothenburg, Sweden
autor
- Chalmers University of Technology, Gothenburg, Sweden
autor
- Chalmers University of Technology, Gothenburg, Sweden
Bibliografia
- 1. De Wit C. (1990). Proposal for low cost ocean weather routeing, Journal of Navigation, Vol.43(3), pp.428-439
- 2. Dijkstra, E.W. (1959). A note on two problems in connexion with graphs, Numerische Mathematik, Vol.1, p.269–271.
- 3. Hagiwara H. (1989). Weather routing of (sail-assisted) motor vessels, PhD thesis, Delft University of Technology, the Netherlands.
- 4. Klompstra M.B, Olsde GJ, Van Brunschot Pkgm (1992). The isopone method in optimal control, Dynamics and Control, Vol.2(3), pp.281-301. Maersk (2014). Glossary of terms.
- 5. Mao, W., Lenaers, P., Salomonsson H., and Brandolm, P. (2016). Machine learning for modelling of actual fuel consumption in ships, Prads 2016, Copenhagen, Denmark.
- 6. Mao, W., Li, Z., Ringsberg, J. and Rychlik, I. (2012) Application of a ship-routing fatigue model to case studies of 2800 TEU and 4400 TEU container vessels, Journal of engineering for maritime environment, Vol. 226 (3), pp. 222-234.
- 7. Mao, W., Ringsberg, JW, Rychlik, I., Storhaug, G. (2010). Development of a fatigue model useful in ship routing design, Journal of Ship Research, Vol. 54 (4), pp.281-293
- 8. Mao, W., Ringsberg, J., Rychlik, I., Storhaug, G. (2010). Development of a fatigue model useful in ship routing design, Journal of Ship Research, Vol.54 (4), pp.281-293.
- 9. Mao, W., Li, Z., Ringsberg, J., Rychlik, I. (2012). Application of a ship-routing fatigue model to case studies of 2800 TEU and 4400 TEU container vessels, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, Vol.226(3), pp. 222-234.
- 10. Mao, W., Ringsberg, J., Rychlik, I. (2012). What is the potential of using ship fatigue routing in terms of fatigue life extension? Proceeding of The Twenty-second International Offshore and Polar Engineering Conference.
- 11. Simonsen, M.H., Larsson, E., Mao, W., Ringsberg, J. (2015). State-of-the-art within ship weather routing, Proceeding of the 34th International Conference on Ocean, Offshore and Arctic Engineering.
- 12. Mao, W., Rychlik, I., Wallin, J., Storhaug, G. (2016). Statistical models for the speed prediction of a container ship, Ocean Engineering, Vol.126, pp.152-162
- 13. Shao, W. and Zhou, P. (2012). Development of a 3D Dynamic Programming Method for Weather Routing, TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 6 (1).
- 14. Wang. H, Mao. W. (2017). Benchmark Study of Five Optimisation Algorithms for Weather Routing, OMAE conference, 2017-61022
- 15. Weiser, Alan, and Sergio E. Zarantonello. “A note on piecewise linear and multilinear table interpolation in many dimensions.” MATH. COMPUT. 50.181 (1988): 189-196.
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-266f51bd-9849-49e9-a893-6981b33a7d7e
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