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

Citation

Jin, Y and Yiew, LJ and Zheng, Y and Magee, AR and Duffy, J and Chai, S, Dynamic manoeuvres of KCS with CFD free-running computation and system-based modelling, Ocean Engineering, 241 Article 110043. ISSN 0029-8018 (2021) [Refereed Article]

Copyright Statement

© 2021 Elsevier Ltd.

DOI: doi:10.1016/j.oceaneng.2021.110043

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 Details

Item Type:Refereed Article
Keywords:MASS, MMG Model, unsteady Reynolds-averaged Navier Stokes, KCS
Research Division:Engineering
Research Group:Maritime engineering
Research Field:Ship and platform structures (incl. maritime hydrodynamics)
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Jin, Y (Mr Yuting Jin)
UTAS Author:Duffy, J (Associate Professor Jonathan Duffy)
UTAS Author:Chai, S (Professor Shuhong Chai)
ID Code:147571
Year Published:2021
Web of Science® Times Cited:2
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2021-11-08
Last Modified:2021-12-21
Downloads:0

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