Interim fuel consumption estimation based on ship service parameters in real weather conditions with the use of ndCurveMaster curve fitting software

• Autorzy: Cepowski T. , Drozd A.

Identyfikatory

DOI

10.17402/213

• Języki publikacji: EN

Abstrakty

EN

This paper deals with fuel consumption estimations relating to container ships on the basis of ship service and wave parameters. Data, on which to base estimations, was measured and recorded from a container ship during 96 months at sea. Approximating functions were calculated by the use of curve fitting techniques and regression methods, utilizing newly developed software named ndCurveMaster. The approximation function presented in this paper could have practical application for the estimation of container ship fuel consumption, while considering weather routing. In addition the study clearly shows the relationship between the fuel consumption of a container ship and the number of months since its last docking. These results may form the basis for further research in this direction.

Słowa kluczowe

EN

ship; fuel consumption; ndCurveMaster; weather routing; curve fitting; regression; hull fouling

• Wydawca: Wydawnictwo Naukowe Akademii Morskiej w Szczecinie
• Czasopismo: Zeszyty Naukowe Akademii Morskiej w Szczecinie
• Rocznik: 2017
• Tom: nr 50 (122)
• Strony: 30--35
• Opis fizyczny: Bibliogr. 9 poz., rys., tab.

Twórcy

autor

Cepowski T.

• Maritime University of Szczecin, Faculty of Navigation 1–2 Wały Chrobrego St., 70-500 Szczecin, Poland

autor

Drozd A.

Bibliografia

• 1. Aligne, F., Papageorgiou, M. & Ramos, J. (1997) Fuel Minimisation for Ship Weather Routing. Preprints of the 8th IFAC/IFIP/IFORS Symposium, Greece.
• 2. Cepowski, T. (2015) Initial considerations for operational parameters intended to minimize fuel consumption by ships in real weather conditions. Scientific Journals of the Maritime University of Szczecin 43 (115), pp. 9–14.
• 3. Christiansen, M. (1999) Decomposition of a Combined Inventory and Time Constrained Ship Routing Problem. Transportation Science 33, 1, pp. 3–16.
• 4. Drozd, A. (2006) Ship’s fuzzy speed curve. IV International Conference Explo-Ship 2006. Maritime University of Szczecin, pp. 39–50.
• 5. Szelangiewicz, T., Wiśniewski, B. & Żelazny, K. (2014) The influence of wind, wave and loading condition on total resistance and speed of the vessel. Polish Maritime Research 21, 3. pp. 61–67.
• 6. TCSOFTWARE (2017) ndCurveMaster [Online copy] Available from: https://www.ndcurvemaster.com [Accessed: April 4, 2017]
• 7. Wiśniewski, B. Medyna, P. & Chomski, J. (2009) Application of the 1-2-3 Rule for Calculations of a Vessel’s Route Using Evolutionary Algorithms. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation 3(2), pp 143–146.
• 8. Wiśniewski, B., Medyna, P. & Chomski, J. (2013) Adjusting the Speed Characteristic of a Ship during a Voyage with Tropical Cyclone Avoidance. Communications in Computer and Information Science 395, pp 346–352.
• 9. Yiyo, K. (2010) Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Computers & Industrial Engineering 59, 1, pp 157–165.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)