Manoeuvring prediction based on CFD generated derivatives

He, Shi and Kellett, Paula and Yuan, Zhiming and Incecik, Atilla and Turan, Osman and Boulougouris, Evangelos (2016) Manoeuvring prediction based on CFD generated derivatives. Journal of Hydrodynamics, 28 (2). 284–292. ISSN 1001-6058 (https://doi.org/10.1016/S1001-6058(16)60630-3)

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Abstract

This paper presents numerical predictions of ship manoeuvring motions with the help of computational fluid dynamics (CFD) techniques. A program applying the modular concept proposed by the Japanese ship manoeuvring mathematical modelling group (MMG) to simulate the standard manoeuvring motions of ships has been initially developed for 3 degrees of freedom manoeu- vring motions in deep water with regression formulae to derive the hydrodynamic derivatives of the vessels. For higher accuracy, several CFD generated derivatives had been substituted to replace the empirical ones. This allows for the prediction of the maneuve- rability of a vessel in a variety of scenarios such as shallow water with expected good results in practice, which may be significantly more time-consuming if performed using a fully CFD approach. The MOERI KVLCC2 tanker vessel was selected as the sample ship for prediction. Model scale aligned and oblique resistance and Planar Motion Mechanism (PMM) simulations were carried out using the commercial CFD software StarCCM+. The PMM simulations included pure sway and pure yaw to obtain the linear manoeuvring derivatives required by the computational model of the program. Simulations of the standard free running manoeuvers were carried out on the vessel in deep water and compared with published results available for validation. Finally, simulations in shallow water were also presented based on the CFD results from existing publications and compared with model test results. The challenges of using a coupled CFD approach in this manner are outlined and discussed.

ORCID iDs

He, Shi ORCID logoORCID: https://orcid.org/0000-0002-9686-3382, Kellett, Paula ORCID logoORCID: https://orcid.org/0000-0001-8162-3397, Yuan, Zhiming ORCID logoORCID: https://orcid.org/0000-0001-9908-1813, Incecik, Atilla, Turan, Osman and Boulougouris, Evangelos ORCID logoORCID: https://orcid.org/0000-0001-5730-007X;
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