• Journal of Ship and Ocean Technology
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• v.12 no.2
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• pp.41-52
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• 2008

The development of a high-lift rudder is needed because low speed full ships such as the VLCC(Very Large Crude oil Carrier) have difficulty for obtaining enough lifting force from a common rudder. The rudder of a ship is generally positioned behind the hull and propeller. Therefore, rudder design should consider the interactions between hull, propeller, and rudder. In the present study, the FLUENT code and body fitted mesh systems generated by the GRIDGEN program are adopted for the numerical simulations of flow characteristics around a rudder that is interacting with hull and propeller. Sliding mesh model(SMM) is adopted to analyze the interaction between propeller rotation and wake flow behind hull. Several numerical simulations are performed to compare the interactions such as hull-rudder, propeller-rudder, and hull-propeller-rudder. Also, we consider relationships between the interactions. The results of present numerical simulations show the variation of flow characteristics by the interaction between hull, propeller, and rudder, and these results are compared with an existing experimental result. The present study demonstrates that numerical simulations can be used effectively in the design of high-lift rudder behind low speed full ship.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.291-297
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• 2013

Generally, form factor is determined through ITTC method. Determining the form factor from ITTC method includes the assumption that the form factor of a full-scale ship is the same value as its model ship. In other words, the form factor is independent on Reynolds number. However, for the more appropriate prediction of the resistance performance of a full-scale ship, the form factor must be determined with the consideration of the variation attendant on Reynolds number. In this research, several Geosim ship models are adopted to investigate the scale effect, and correlation lines of form factor are improved to suggest the better extrapolation method for the prediction of the form factor of full-scale ship. The corrected form factors using the correlation lines are compared with those determined from the results of low-speed resistance tests. To consider the influence of hull form, the correlation lines are determined for the group of high-speed ships and the group of low-speed ships, respectively. The corrected form factors have shown good agreement among the prediction results from each Geosim ship model to the full-scale ship.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1274-1280
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• 2022

The resistance performance evaluation of general ships using computational fluid dynamics requires a lot of time and cost, and various methods are being studied to reduce the time and cost. Existing methods using main particulars or cross sections of ships have limitations in estimating resistance performance that is greatly dependent on the shape of the ship. In this paper, we propose a deep neural network model that can quickly predict the resistance performance of the hull surface by inputting the geometric information of the hullform mesh. The proposed deep neural network model based on Perceiver IO can immediately predict resistance performance, unlike computational fluid dynamics techniques that require calculation in each time step. It shows the result of estimating the resistance performance with an average error of less than 1% in the data set for a 50 K tanker ship, a type of low-speed full ship.

• Journal of the Korean Institute of Navigation
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• v.21 no.4
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• pp.21-28
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• 1997

Along with the rapid growth of shipping and transportation , the size of a ship larger and larger. Low speed maneuverabililty of a full ship has been received a great deal of attention concerting about the navigation safety, especially in the harbour area of waterway. And, the iperation of the full ship in harbour area is one fo tehmost difficult technique. Usually highly experienced experts can make a suitable decision considering various propeller ,rudder actions and environmental conditions. The Artificial Neural Network is applied to the automatic berthing control of a ship. The teaching data are made by the berthing simulation of a ship on the computer. And, the layer neural network is used and the 'Error Back-Propagation Algorithm' is used to teach the neural network. Finally, it is shown that the berthing control is successfully done by the established neural network.

• Journal of the Korean Institute of Navigation
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• v.15 no.4
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• pp.27-39
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• 1991

One practical method has already been proposed for predicting the characteristics of ship manoeuvring motions at relatively high advance speed [19]. Howeverf, this method can hardly be applied to motions of ships in starting, stopping, backing and slow steaming conditions, even though such extensive motions are of vital importance from a safety point of view particularly in harbour areas. The method presented here aims at predicting the characteristics of ship manoeuvring at low advance speed, which covers starting, stopping, backing and slow steaming conditions. The force mathematical models at large angles of incidence to the hull as well as under the wide range of propeller operations are formulated. Simulations of various manoeuvres at low advance speed are carried out for two types of merchant ship, I.e. a LNGC and a VLCC. Comparisons between simulations and corresponding full-scale measurements [10], [15] or free-running model tests [6],[10] provide a first verification of the proposed mathematical models.

• Journal of the Society of Naval Architects of Korea
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• v.29 no.3
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• pp.90-101
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• 1992

Some practical methods have already been proposed for predicting the characteristics of ship manoeuvring motions at relatively high advance speed. However, these methods can hardly be applied to motions of ships in starting, stoppint, backing and slow steaming conditions, even though such extensive motions are of vital importance from a safety point of view particularly in harbour areas. The method presented here aims at predicting the characteristics of ship manoeuvring at low advance speed, which covers starting, stopping, backing and slow steaming conditions. The force mathematical models at large angles of incidence to the hull as well as under the tilde range of propeller operations are formulated. Simulations of various manoeuvres at low advance speed are carried out for two types of merchant ship, i.e. a LNGC and a VLCC. Comparisons between simulations and corresponding full-scale measurements or free-running model tests provide a first verification of the proposed mathematical models.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.127-127
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• 2017

• Journal of the Society of Naval Architects of Korea
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• v.57 no.6
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• pp.312-321
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• 2020

In this study, machine learning techniques were applied to predict the residual resistance coefficient (Cr) of low-speed full ships. The used machine learning methods are Ridge regression, support vector regression, random forest, neural network and their ensemble model. 19 hull form variables were used as input variables for machine learning methods. The hull form variables and Cr data obtained from 139 hull forms of KRISO database were used in analysis. 80 % of the total data were used as training models and the rest as validation. Some non-linear models showed the overfitted results and the ensemble model showed better results than others.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.5
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• pp.447-456
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• 2019

In the early stage of ship design, the rapid prediction of resistance of hull forms is required. Although there are more accurate prediction methods such as model test and CFD analysis, statistical methods are still widely used because of their cost-effectiveness and quickness in producing the results. This study suggests the prediction formula for the residual resistance coefficient (Cr) of the low-speed full ships. The formula was derived from the statistical analysis of model test results in KRISO database. In order to improve prediction accuracy, the local variables of hull forms are defined and used for the regression process. The regression formula for these variables using only principal dimensions of hull forms are also provided.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.03a
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• pp.145-153
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• 2002

A coastwise chemical tanker sailing at full speed has capsized in calm water and whole turing. In the precious paper, we investigated reasons of the accident by demonstrating the proper correction for the free surface effect of the liquid cargo and the bow-sinkage effect. In this paper, we also carry out model experiments of a transverse pressure under the seawater and an outward heel moment according to the heel angle and rudder angle, on the basis of radius of turning circle, ship's speed and drift angle of model ship occurring in turning. It is also shown that the flooding of seawater onto the deck occurring in turning generated a significant outward heel moment and the vertical distance between the center of gravity of the ship and the renter of lateral water drag.