Numerical evaluation of a ship's manoeuvrability and course keeping control under various wave conditions using CFD

Kim, Daejeong; Song, Soonseok; Jeong, Byongug; Tezdogan, Tahsin

doi:10.1016/j.oceaneng.2021.109615

Cited by 31 publications

(15 citation statements)

References 29 publications

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“…This section will provide details of the research methodology used in this study. This research adopted the methodology and the Unsteady Reynolds-Averaged Navier-Stokes model developed by Kim et al (2021a), who conducted the manoeuvring analysis of the KCS in different wave length conditions. This free-running CFD model has the benefit of being easily extended to various environmental conditions for new applications.…”

Section: Methodsmentioning

confidence: 99%

“…In the fourth step, the general relationship between the ship's manoeuvrability and wave heights are presented through graphs and tables as key findings. The applied methodology will be briefly described in sub-sections (2.1 -2.4), and the details can be found in Kim et al (2021a).…”

Section: Methodsmentioning

confidence: 99%

“…In addition, Kim et al (2021b) performed free-running CFD simulations to study the manoeuvring behaviour of the KCS in waves of different propagation directions, focusing on the course-keeping and turning capabilities. Kim et al (2021a) further extended the application of the free-running CFD model to investigate the manoeuvring behaviour of the KCS in waves of different wave lengths. However, the literature reported here focused on case-specific analyses meaning that research findings from those studies had some inherent limitations in terms of providing a general understanding of the relation between wave heights and a variety of ship types.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Unsteady RANS CFD simulations of ship manoeuvrability and course keeping control under various wave height conditions

Kim

Song

Jeong

et al. 2021

Applied Ocean Research

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Unsteady RANS CFD simulations of ship manoeuvrability and course keeping control under various wave height conditions

Kim

Song

Jeong

et al. 2021

Applied Ocean Research

Self Cite

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“…During long voyages, vessels inevitably encounter extremely bad weather conditions, traffic management in busy sea areas, and navigation yaw errors (Szlapczynski and Krata, 2018). In addition, the power output of the vessel is insensitive and it has the particularity of being carried by the fluid, which makes the response time for changing the course of the vessel longer (Kim et al, 2021). If correct decisions with respect to the vessel cannot be made in a timely manner, according to the current state in the ocean-going process, the risk of life and the loss of property will greatly increase (Zhao et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

TripleConvTransformer: A deep learning vessel trajectory prediction method fusing discretized meteorological data

Huang

Chen

Wang

et al. 2022

Front. Environ. Sci.

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The shipping industry is increasingly threatened by global climate change. Reliable trajectory prediction can be used to perceive potential risks and ensure navigation efficiency. However, many existing studies have not fully considered the impact of complex ocean environmental factors and have only focused on local regions, which are difficult to extend to a global scale. To this end, we propose a deep learning vessel trajectory prediction method fusing discretized meteorological data (TripleConvTransformer). First, we clean the automatic identification system data to form a high-quality spatiotemporal trajectory dataset. Then, we fuse the trajectory data with the meteorological data after feature discretization to deeply mine the motion information of ocean-going ships. Finally, we design three modules, the global convolution, local convolution, and trend convolution modules, based on the simplified transformer model to capture multiscale features. We compare TripleConvTransformer with state-of-the-art prediction models. The experimental results show that in the prediction of the trajectory points in the next 90 min, the smallest root mean square error in terms of longitude and latitude and the highest overall prediction accuracy are achieved using TripleConvTransformer. Our method not only fully considers the influence of meteorological factors in the ocean-going process but also effectively extracts the important information hidden in the data, thus achieving accurate trajectory prediction on a global scale.

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“…The motion of ships in high sea states is related to the safety of navigation. Kim D. et al [5] studied ship maneuverability under different wave conditions based on the CFD method. The main results of this study help to improve the understanding of ship maneuverability in waves, thus as to improve the safety of navigation.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of the Motion of a Large Scale Unmanned Surface Vessel in High Sea State Waves

Huang

Liu

Luo

et al. 2021

JMSE

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The motion stability of the Unmanned Surface Vessel (USV) is threatened by the action of waves under a rough sea state. In the present paper, the motion of a large-scale USV is numerically simulated under high sea state of level 5 and 7. The overset grid method and Reynolds Averaged Navier–Stokes (RANS) approach are employed to solve Navier–Stokes (N-S) equations. For the case of wave incident angle 0° and 30°, the heave, pitch and roll motion response of a large scale USV are investigated by using the six Degrees of Freedom (6-DOF) numerical model. The effects of different sea states, as well as different wave directions, on the motion of USV are compared. The comparative results indicate that the response of this USV in waves is the periodic free-motion according to the corresponding amplitude, which does not exceed the stable range, and there are no overturning and other situations that may affect the safety, in the case of level 5 and 7 sea states. The corresponding pressure at the bottom of this USV meets the range of material strength, and no structural damage or injury to the hull occurs, although the pressure varies at different wave periods. For the case of different wave directions, the analysis of the boundary layer thickness shows that the wave direction is of great importance to the boundary layer thickness distribution, both in the level 5 and level 7 sea states.

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Numerical evaluation of a ship's manoeuvrability and course keeping control under various wave conditions using CFD

Cited by 31 publications

References 29 publications

Unsteady RANS CFD simulations of ship manoeuvrability and course keeping control under various wave height conditions

Unsteady RANS CFD simulations of ship manoeuvrability and course keeping control under various wave height conditions

TripleConvTransformer: A deep learning vessel trajectory prediction method fusing discretized meteorological data

Numerical Simulation of the Motion of a Large Scale Unmanned Surface Vessel in High Sea State Waves

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