On the modeling of car passenger ferryship design parameters with respect to selected sea-keeping qualities and additional resistance in waves

• Autorzy: Cepowski T.
• Języki publikacji: EN

Abstrakty

EN

This paper presents the modeling of car passenger ferryship design parameters with respect to such design criteria as selected sea-keeping qualities and additional resistance in waves. In the first part of the investigations approximations of selected statistical parameters of design criteria of ferryship were elaborated with respect to ship design parameters. The approximation functions were obtained with the use of artificial neural networks. In the second part of the investigations design solutions were searched for by applying the singleand multi-criterial optimization methods. The multi-criterial optimization was performed by using Pareto method. Such approach made it possible to present solutions in such form as to allow decision makers (shipowner, designer) to select solutions the most favourable in each individual case.

Słowa kluczowe

EN

sea-keeping qualities; roll-on/roll-off ferryship; rolling; motion sickness index; lateral accelerations; additional resistance in waves; ship design parameters; modeling; artificial neural networks; optimization; Pareto method

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2009
• Tom: nr 3
• Strony: 3--10
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Cepowski T.

• Institute of Marine Navigation, Maritime University of Szczecin Wały Chrobrego 1/2 70-500 Szczecin, POLAND,

Bibliografia

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• 2. Cepowski T.: Approximation of the index for assessing ships sea-keeping performance on the basis of ship design parameters. Polish Maritime Research, No. 3(53), Vol. 14, 2007
• 3. Chądzyński W.: Elements of contemporary design methods of floating objects (in Polish). Scientific Reports of Szczecin University of Technology, Department of Ocean Engineering and Marine System Design, Szczecin 2001
• 4. Gerritsma, J. and Beukelman, W.: Analysis of the Resistance Increase in Waves of a Fast Cargo-ship. International Shipbuilding Progress, 18(217), 1972.
• 5. Goldberg D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Publication of Pearson Education, Inc, 1989
• 6. Journee J.M.J.: Verification and Validation of Ship Motions Program SEAWAY. Report1213a, Delft University of Technology, The Netherlands, 2001.
• 7. Lasdon, L.S., Waren, A.D.: Generalized reduced gradient software for linearly and nonlinearly constrained problems. [in]: Greenberg, H.J., (Ed.) Design and Implementation of Optimization Software. Sijthoff and Noordhoff, Holland, 1978
• 8. Mesbashi E., Bertram V.: Empirical Design Formulae Using Artificial Neural Nets. 1st International EuroConference on Computer Applications and Information Technology in the Maritime Industries, COMPIT’2000, Potsdam 2000
• 9. Riola J.M., M.Garcia de Arboleya: Habitability and personal space in sea-keeping behaviour. Journal of Maritime Research, Vol. III, No. 1, 2006
• 10. Szelangiewicz T., Cepowski T.: Application of artificial neural networks to investigation of ship sea-keeping ability, Part 1, Polish Maritime Research, Vol.8, No. 3, September 2001
• 11. Szozda Z.: A Concept of Ship Stability Criteria Based on Cargo Shift Caused by Rolling due to Gust. Zeszyty Naukowe (Scientific Bulletins) No. 2 (74), Maritime University of Szczecin, 2004