<abstract xmlns="http://www.w3.org/1999/xhtml"><p> The article presents the mathematical function to calculate the added wave resistance transfer function for bulk carriers. Based on this function, the statistical mean added wave resistance generated by an irregular head wave with arbitrary statistical parameters can be forecasted. The input parameters are: waterplane area, waterplane coefficient, ship speed, and frequency of the regular wave. The model has been developed based on the theory of artificial neural networks. The presented function can be used in design analyses, and for planning shipping routes in situations when basic geometrical parameters of the hull are only available and not the full technical documentation. The article presents sample cases of use of this function to calculate the added wave resistance transfer function and the statistical mean added wave resistance. Another presented application refers to waterplane coefficient optimisation taking into account the added wave resistance at the stage of preliminary bulk carrier design.</p></abstract>

The article presents the mathematical function to calculate the added wave resistance transfer function for bulk carriers. Based on this function, the statistical mean added wave resistance generated by an irregular head wave with arbitrary statistical parameters can be forecasted. The input parameters are: waterplane area, waterplane coefficient, ship speed, and frequency of the regular wave. The model has been developed based on the theory of artificial neural networks. The presented function can be used in design analyses, and for planning shipping routes in situations when basic geometrical parameters of the hull are only available and not the full technical documentation. The article presents sample cases of use of this function to calculate the added wave resistance transfer function and the statistical mean added wave resistance. Another presented application refers to waterplane coefficient optimisation taking into account the added wave resistance at the stage of preliminary bulk carrier design.

Approximating the Added Resistance Coefficient for a Bulk Carrier Sailing in Head Sea Conditions Based on its Geometrical Parameters and Speed

Maritime University of Szczecin ul. Wały Chrobrego 1-2 70-500 Szczecin,

Polish Maritime Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

The article presents the mathematical function to calculate the added wave resistance transfer function for bulk carriers. Based on this function, the...

Approximating the Added Resistance Coefficient for a Bulk Carrier Sailing in Head Sea Conditions Based on its Geometrical Parameters and Speed

Data publikacji: 20 sty 2017

Zakres stron: 8 - 15

DOI: https://doi.org/10.1515/pomr-2016-0066

Słowa kluczowe
bulk carrier, resistance, added wave resistance, added resistance coefficient, regular wave, irregular wave, ship designing, preliminary design stage, artificial neural networks, approximation, forecasting, speed, waterplane area, waterplane coefficient, sample case, task, designing

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Approximating the Added Resistance Coefficient for a Bulk Carrier Sailing in Head Sea Conditions Based on its Geometrical Parameters and Speed

Data publikacji: 20 sty 2017

Zakres stron: 8 - 15

DOI: https://doi.org/10.1515/pomr-2016-0066

Słowa kluczowebulk carrier, resistance, added wave resistance, added resistance coefficient, regular wave, irregular wave, ship designing, preliminary design stage, artificial neural networks, approximation, forecasting, speed, waterplane area, waterplane coefficient, sample case, task, designing

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
bulk carrier, resistance, added wave resistance, added resistance coefficient, regular wave, irregular wave, ship designing, preliminary design stage, artificial neural networks, approximation, forecasting, speed, waterplane area, waterplane coefficient, sample case, task, designing