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Dynamic manoeuvres of KCS with CFD free-running computation and system-based modelling

Jin, Y ORCID: 0000-0002-4336-2680, Yiew, LJ, Zheng, Y, Magee, AR, Duffy, J ORCID: 0000-0003-3484-1345 and Chai, S ORCID: 0000-0001-5186-4456 2021 , 'Dynamic manoeuvres of KCS with CFD free-running computation and system-based modelling' , Ocean Engineering, vol. 241 , pp. 1-15 , doi: https://doi.org/10.1016/j.oceaneng.2021.110043.

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Abstract

Future state projection is an important prerequisite for the maritime autonomous surface ships (MASS) to initiate a collision-avoidance manoeuvre. Forecasts of MASS′ trajectories and motions are fundamentally based on the vessel's mathematical manoeuvring model, which is also referred to as the hydrodynamic digital twin nowadays. Using the benchmark container ship KCS as an object of study, this paper adopts a 3-DOF modular-type manoeuvring (MMG) model to predict the vessel trajectories in calm water and under the presence of steady current and regular waves. The current effects are treated as additional ship over water speed, while the wave effects are considered by superimposing the mean second-order wave drift loads to the calm water hull hydrodynamics. Concurrently, selected manoeuvring cases including turning circle and zig-zag are solved using the unsteady Reynolds-averaged Navier-Stokes (uRANS) equations based CFD method, where a hierarchy of overset grids is utilised to allow self-propulsion and active rudder steering. The computed vessel trajectories and velocities are compared with that predicted by the MMG model and show reasonable agreement. The wave loads experienced by the vessel when turning in waves are also analysed and discussed.

Item Type: Article
Authors/Creators:Jin, Y and Yiew, LJ and Zheng, Y and Magee, AR and Duffy, J and Chai, S
Keywords: MASS, MMG Model, unsteady Reynolds-averaged Navier Stokes, KCS
Journal or Publication Title: Ocean Engineering
Publisher: Pergamon-Elsevier Science Ltd
ISSN: 0029-8018
DOI / ID Number: https://doi.org/10.1016/j.oceaneng.2021.110043
Copyright Information:

© 2021 Elsevier Ltd.

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