Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/166201
Title: Improvement of the prediction of the added resistance in waves of ships with extreme main dimensional ratios through numerical experiments
Authors: Liu, Shukui
Papanikolaou, Apostolos
Keywords: Engineering::Mechanical engineering
Issue Date: 2023
Source: 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
Journal: Ocean Engineering 
Abstract: 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.
URI: https://hdl.handle.net/10356/166201
ISSN: 0029-8018
DOI: 10.1016/j.oceaneng.2023.113963
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2023 Elsevier Ltd. All rights reserved. This paper was published in Ocean Engineering and is made available with permission of Elsevier Ltd.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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