Resistance Prediction for Hard Chine Hulls in the Pre-Planing Regime

• Autorzy: Radojcic D. , Zgradic A. , Kalajdzic M. , Simic A.
• Języki publikacji: EN

Abstrakty

EN

A mathematical representation of calm-water resistance for contemporary planing hull forms based on the USCG and TUNS Series is presented. Regression analysis and artificial neural network (ANN) techniques are used to establish, respectively, Simple and Complex mathematical models. For the Simple model, resistance is the dependent variable (actually R/Δ for standard displacement of Δ = 100000 lb), while the Froude number based on volume (FnV) and slenderness ration (L/V1/3) are the independent variables. In addition to these, Complex model’s independent variables are the length beam ratio (L/B), the position of longitudinal centre of gravity (LCG/L) and the deadrise angle (β). The speed range corresponding to FnV values between 0.6 and 3.5 is analyzed. The Simple model can be used in the concept design phases, while the Complex one might be used for various numerical towing tank performance predictions during all design phases, as appropriate.

Słowa kluczowe

EN

planing craft; hard chine hulls; resistance evaluation; Artificial Neural Network (ANN); TUNS Series; USCG Series; pre-planing regime

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2014
• Tom: nr 2
• Strony: 9--26
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Radojcic D.

• University of Belgrade, Faculty of Mechanical Engineering, Dept. of Naval Architecture, Belgrade, SERBIA

autor

Zgradic A.

• NAVAR, Herceg Novi, MONTENEGRO

autor

Kalajdzic M.

• University of Belgrade, Faculty of Mechanical Engineering, Dept. of Naval Architecture, Belgrade, SERBIA

autor

Simic A.

• University of Belgrade, Faculty of Mechanical Engineering, Dept. of Naval Architecture, Belgrade, SERBIA

Bibliografia

• 1. Blount D. L., Fox D. L.: Small Craft Power Prediction, Marine Technology, Vol. 13, No.1, 1976
• 2. Blount D.: Prospects for Hard Chine, Monohull Vessels, Proceedings of the Second Int. Conf. on Fast Sea Transportation - FAST ’93, Yokohama, 1993
• 3. Clement P. E.: Analyzing the Stepless Planing Boat, Int. Shipbuilding Progress, No. 33, 1957
• 4. Clement P. E., Blount D.: Resistance Tests of a Systematic Series of Planing Hull Forms, Trans. SNAME, Vol. 71, 1963
• 5. Delgado-Saldivar G.: Experimental Investigation of a New Series of Planing Hulls, M.Sc. Thesis, Technical University of Nova Scotia, Halifax, Nova Scotia, 1993
• 6. Garo R., Datla R., Imas L.: Numerical Simulation of Planing Hull Hydrodynamics, SNAME’s Third Chesapeake Powerboat Symposium, Annapolis, 2012
• 7. Hubble E. N.: Resistance of Hard-Chine Stepless Planing Craft with Systematic Variation of Hull Form, Longitudinal Centre of Gravity and Loading, DTNSRDC R&D Report 4307, 1974
• 8. Keuning, J. A., Gerritsma, J.: Resistance Tests of a Series of Planing Hull Forms with 25 Degrees Deadrise Angle, Int. Shipbuilding Progress, Vol. 29, No. 337, 1982
• 9. Keuning J. A., Gerritsma J., Terwisga P. F.: Resistance Tests of a Series Planing Hull Forma With 30o Deadrise Angle, and a Calculation Model Based on This and Similar Systematic Series, Int. Shipbuilding Progress, Vol. 40, No. 424, 1993
• 10. Kowalyshyn D. H., Metclaf B.: A USCG Systematic Series of High Speed Planing Hulls, Trans. SNAME, Vol. 114, 2006
• 11. Macpherson D.: Ten Commandments of Reliable Speed Prediction, Proceedings of Small Craft Resistance and Propulsion Symposium, Michigan, 1996
• 12. Miljkovic, Z.: Systems of Artificial Neural Networks in Production Technologies, University of Belgrade, Faculty of Mechanical Engineering, Belgrade, ISBN 86-7083-455-3 (in Serbian), 2003
• 13. Moore W., Hawkins F.: Planing Boat Scale Effects on Trim and Drag (TMB Series 56), NSRDC Technical Note No. 128, 1969
• 14. Morabito M., Snodgrass J.: The Use of Small Model Testing and Full Scale Trials in the Design of Motor Yacht, SNAME’s Third Chesapeake Powerboat Symposium, Annapolis, 2012
• 15. Radojcic D.: An Approximate Method for Calculation of Resistance and Trim of the Planing Hulls, Ship Science Report No 23, Faculty of Engineering and Applied Science, University of Southampton, Southampton, 1985
• 16. Radojcic, D.: An Engineering Approach to Predicting the Hydrodynamic Performance of Planing Craft Using Computer Techniques, Trans. RINA, Vol. 133, 1991
• 17. Radojcic D., Rodic T., Kostic N.: Resistance and Trim Predictions for the NPL High Speed Round Bilge Displacement Hull Series, RINA’s Int. Conf. on Power, Performance & Operability of Small Craft, Southampton, 1997
• 18. Rojas R.: Neural Networks - A Systematic Introduction, Springer-Velrag, Berlin, 1996
• 19. Savander B. R., Maki K. J., Land J.: The Effects of Deadrise Variation on Steady Planing Hull Performance, SNAME’s Second Chesapeake Powerboat Symp., Annapolis, 2010
• 20. Savitsky D.: Hydrodynamic Design of Planing Hulls, Marine Technology, Vol. 1, No. 1, 1964
• 21. Savitsky D., Delorme M., Datla R.: Inclusion of Whisper-Spray Drag in Performance Prediction Method for Planing Hulls, New York Metropolitan Section of SNAME, 2006
• 22. Savitsky D.: The Effect of Bottom Warp on the Performance of Planing Hulls, SNAME’s Third Chesapeake Powerboat Symposium, Annapolis, 2012
• 23. Schleicher D., Bowles B.: Two Speed Gears, Professional Boat Builder, No. 80, Dec/Jan, 2003
• 24. Simic A.: Energy Efficiency of Inland Self-Propelled Cargo Vessels, Doctoral dissertation, University of Belgrade, Faculty of Mechanical Engineering, Belgrade (in Serbian), 2012
• 25. SNAME Small Craft Data Sheets – Technical and Research Bulletin
• 26. Tanaka H., Nakato M., Nakatake K., Ueda T., Araki S.: Cooperative Resistance Tests with Geosim Models of a High-Speed Semi-displacement Craft, Journal of SNAJ, Vol. 169, 1991.
• 27. Taunton D. J., Hudson D. A., Shenoi R. A.: Characteristics of a Series of High Speed Hard Chine Planing Hulls – Part 1: Performance in Calm Water, Trans. RINA, Vol. 152, Part B2, 2010
• 28. Zurek S.: LabVIEW as a tool for measurements, batch data manipulations and artificial neural network predictions, National Instruments, Curriculum Paper Contest, Przegląd Elektrotechniczny, Nr 4/2007, 2007.