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Original scientific paper

https://doi.org/10.21278/brod73101

INVESTIGATION ON SOME CONVENTIONAL HULLS FORMS OF THE PREDICTIVE ACCURACY OF A PARAMETRIC SOFTWARE FOR PRELIMINARY PREDICTIONS OF RESISTANCE AND POWER

Blenard Xhaferaj ; University of Vlora “Ismail Qemali”, Albania, Department of Engineering and Marine Technology


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Abstract

Preliminary prediction of resistance and power is a fundamental aspect of the ship design process since they directly influence the developments of the design process, fuel consumption and costs, and environmental impact from the early design stage. Parametric predictions of resistance and power, based mainly on statistical regression models that are also ideal for computer programming, are often performed during initial design stages, providing rapid predictions and optimisations for minimum resistance. The paper aims to present the results of the comparative analysis on some conventional hulls of the predictive accuracy of a computer program developed by the author for parametric predictions of resistance and power of ships. The program (entitled Ship Power V 1.0) is developed in the Visual Basic 6.0 environment based on two well-known regression models Holtrop and Van Oortmerssen. The program can perform detailed predictions of resistance and power, resistance coefficients, propeller thrust, hull efficiency, wake, and trust fractions, with no restriction on the number of velocities. In this study, only the analysis of the accuracy of resistance and power prediction is considered. Results of the comparative analysis of the computational procedures of Ship Power V 1.0 versus experimental data, and against results of another well-known commercial software, performed on three models of the Ridgely-Nevitt trawler series and KCS hull have shown a good level of accuracy and reliability as other well-known commercial software.

Keywords

Resistance; power; regression models; ship design; experimental data

Hrčak ID:

271904

URI

https://hrcak.srce.hr/271904

Publication date:

1.1.2022.

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