Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments

After a decade of development, the semi-empirical SNNM (SHOPERA-NTUA-NTU-MARIC) method for the prediction of the added resistance of ships in waves (Liu & Papanikolaou, 2020) was successfully developed and is being widely used by the maritime industry (IMO, 2021; ITTC, 2021). The method is herei...

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Main Authors: Liu, Shukui, Papanikolaou, Apostolos
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/166201
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1662012023-04-22T16:48:19Z Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments Liu, Shukui Papanikolaou, Apostolos School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Added Resistance of Ships in Waves Design of Numerical Experiments After a decade of development, the semi-empirical SNNM (SHOPERA-NTUA-NTU-MARIC) method for the prediction of the added resistance of ships in waves (Liu & Papanikolaou, 2020) was successfully developed and is being widely used by the maritime industry (IMO, 2021; ITTC, 2021). The method is herein updated by use of numerical simulations for the consideration of ships with extreme dimensional ratios, for which experimental data are scarce or non-existent. Numerical experiments are designed to investigate the joint effect of the variation of CB, L/B, and B/T using well-established numerical tools for the added resistance in waves. The patterns observed in the results are then correlated to the parameters through explicit, readily useable mathematical expressions. The improved formula is benchmarked with an experimental database of 11 ships with extreme dimensional ratios of various types. The validation study shows that the improved formula achieved a higher correlation coefficient and a smaller mean percentage error. Thus, the introduced expressions can significantly improve the prediction of the added resistance of various types of ships in waves, including those with extreme dimensional ratios. This study demonstrates how to combine the merits of both numerical and physical experiments to gain insight into complex physical problems. Submitted/Accepted version 2023-04-17T02:16:34Z 2023-04-17T02:16:34Z 2023 Journal Article Liu, S. & Papanikolaou, A. (2023). Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments. Ocean Engineering, 273, 113963-. https://dx.doi.org/10.1016/j.oceaneng.2023.113963 0029-8018 https://hdl.handle.net/10356/166201 10.1016/j.oceaneng.2023.113963 2-s2.0-85149833382 273 113963 en Ocean Engineering © 2023 Elsevier Ltd. All rights reserved. This paper was published in Ocean Engineering and is made available with permission of Elsevier Ltd. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Added Resistance of Ships in Waves
Design of Numerical Experiments
spellingShingle Engineering::Mechanical engineering
Added Resistance of Ships in Waves
Design of Numerical Experiments
Liu, Shukui
Papanikolaou, Apostolos
Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
description After a decade of development, the semi-empirical SNNM (SHOPERA-NTUA-NTU-MARIC) method for the prediction of the added resistance of ships in waves (Liu & Papanikolaou, 2020) was successfully developed and is being widely used by the maritime industry (IMO, 2021; ITTC, 2021). The method is herein updated by use of numerical simulations for the consideration of ships with extreme dimensional ratios, for which experimental data are scarce or non-existent. Numerical experiments are designed to investigate the joint effect of the variation of CB, L/B, and B/T using well-established numerical tools for the added resistance in waves. The patterns observed in the results are then correlated to the parameters through explicit, readily useable mathematical expressions. The improved formula is benchmarked with an experimental database of 11 ships with extreme dimensional ratios of various types. The validation study shows that the improved formula achieved a higher correlation coefficient and a smaller mean percentage error. Thus, the introduced expressions can significantly improve the prediction of the added resistance of various types of ships in waves, including those with extreme dimensional ratios. This study demonstrates how to combine the merits of both numerical and physical experiments to gain insight into complex physical problems.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Liu, Shukui
Papanikolaou, Apostolos
format Article
author Liu, Shukui
Papanikolaou, Apostolos
author_sort Liu, Shukui
title Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
title_short Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
title_full Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
title_fullStr Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
title_full_unstemmed Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
title_sort improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
publishDate 2023
url https://hdl.handle.net/10356/166201
_version_ 1764208021431386112