• Korean Journal of Computational Design and Engineering
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• v.4 no.4
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• pp.381-390
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• 1999

In this study, a pseudo ship structure data model for the :.hip cargo hold structure based on STEP is proposed. The proposed data model is based on Application Reference Model of AP218 Ship Structure which is the model that specifies conceptual structures and constraints used to describe the information requirements of an application. And the proposeddata model refers the Ship Common Model framework for the model architecture which is the basis for ongoing ship AP development within the ISO ship-building group and the ship product definition information model of CSDP research project for analyzing the relationship between ship structure model entities. The proposed data model includes Space, Compartment. Ship Structural System, Structural Part and Structural Feature of cargo hold. To generate this data model schema in EXPRESS format, ‘GX-Converter’was used which enables user to edit a model in EXPRESS format and convert schema file in EXPRESS format. Using this model schema, STEP physical file containing design data for ship cargo hold data structure was generated through SDAI programming. The another STEP physical file was also generated containing geometry data of ship cargo hold which was extracted and calculated by SDAI and external surface/surface intersection program. The geometry information of ship cargo hold can be then transferred to commercial CAD system, for example, Pro/Engineer. Examples of the modification of the design information are also Presented.

• Journal of Navigation and Port Research
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• v.48 no.2
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• pp.116-124
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• 2024

Automatic docking of small planing ship is a critical aspect of maritime operations, requiring accurate prediction of motion states to ensure safe and efficient maneuvers. This study investigates the use of Artificial Neural Network (ANN) to predict motion state of a small planing ship to enhance navigation automation in port environments. To achieve this, simulation tests were conducted to control a small planing ship while docking at various heading angles in calm water and in waves. Comprehensive analysis of the ANN-based predictive model was conducted by training and validation using data from various docking situations to improve its ability to accurately capture motion characteristics of a small planing ship. The trained ANN model was used to predict the motion state of the small planning ship based on any initial motion state. Results showed that the small planing ship could dock smoothly in both calm water and waves conditions, confirming the accuracy and reliability of the proposed method for prediction. Moreover, the ANN-based prediction model can adjust the dynamic model of the small planing ship to adapt in real-time and enhance the robustness of an automatic positioning system. This study contributes to the ongoing development of automated navigation systems and facilitates safer and more efficient maritime transport operations.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.3
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• pp.215-221
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• 2011

To improve the naval ship acquisition process, systems engineering, modeling and simulation, etc. have been introduced, and there has been ongoing research on acquisition systems for effective support of it. However, due to characteristics of the naval ship acquisition process, development process mainly carried out at a shipyard such as basic design, detailed design, construction and test is difficult to integrate with the acquisition systems of IPT(Integrated Project Team). In addition, research aimed to improve this is rather lacking. In this paper, the naval ship product structure concept proposed in previous research was applied to the basic design system at shipyard, and basic research for expanding the coverage of naval ship acquisition systems to the basic design phase is performed. A data structure of modeling system appropriate to the basic design phase was proposed through research findings and the prototype system based on it was implemented.

• Journal of Navigation and Port Research
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• v.40 no.4
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• pp.165-171
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• 2016

SEEMP (Ship Energy Efficiency Management Plan) has entered into force since 2013 for the reduction of GHG emission of operating ships. SEEMP guidelines include the hardware modification or installation of energy-saving device on ship. It also includes software based energy-saving technology such as optimum routing, speed optimization, etc. Hardware based technologies are not easy to apply to ongoing vessel due to the operational restriction. Therefore, IT based energy-saving technology was applied and its energy efficiency was evaluated using before and after energy-saving system applied voyage data. SEEMP advises a voluntary participation of EEOI (Ship Energy Efficiency Operation Indicator) use as an indicator of ship energy efficiency operation, and those results were also shown to evaluate the improvement efficiency of energy-saving system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.230-231
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• 2019

This study is a development on condition based maintenance(CBM) technology which is a core item of future autonomous ships. It is developing to design & installation of condition monitoring system and acquisition & processing of data from ongoing ships for fault prediction & prognosis of engine in operation. The ultimate goal of this study is to develop a predicts and decision support software for marine engine faults. To do this, the FMEA and fault tree analysis of the main engine should be accompanied by the analysis of classification of system, identification of the components, the type of faults, and the cause and phenomenon of the failure. Finally, the CBM system solution software could predict and diagnose the failure of main engine through integrated analysis for bid-data of ongoing ships and engineering knowledge. Through this study, it is possible to pro-actively cope with abnormal signals of engine and to manage efficiently, and as a result, expected that marine accident and ship operation loss during navigation will be prevented in advance.

• Electronics and Telecommunications Trends
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• v.35 no.3
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• pp.85-97
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• 2020

In the maritime industry, the convergence of information and communication technology (ICT) occurs in two areas. The first one is the convergence of e-navigation technology to apply ICT to the maritime domain. This was led by EU's initiative and is also being promoted in our country. The other one is the convergence of autonomous ship technology to apply various ICT technologies for commercial purposes. This initiative is being led by maritime industries. In this paper, we describe trends of e-navigation and maritime autonomous surface ship technology convergence. Subsequently, we explain the standardization status of performance and technical standard bodies, international standardization organizations, and related standard-developing organizations to provide the interoperability of these technologies. Finally, we examine ongoing projects in Korea and suggest future directions for their R&D and standardization.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.243-244
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• 2009

From large to small vessels of the surface is not smooth. and The surface ship has a surface roughness. Because surface roughness increases the surface resistance and heat transfer, be considered when designing a ship that is an important design factor. Due to surface roughness study on flow around and due to changes in flow and turbulence intensity for the ongoing research is conducted. Roughness of the surface ships from the ship by air as well as machines can be widely applied. In this study, the surface roughness of the leisure marine interval, any change will affect the surface flow, area due to surface roughness for boundary-experimental study was performed.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.69-82
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• 2018

The number of ships serviced at the container terminals in Busan is increasing by 2.9% per year. In spite of the increase in calling ships, there are no official records of waiting rate by the port authority. This study attempts to compare the theoretical ship waiting ratio and actual ship waiting ratio. The actual ship waiting ratio of container terminals is acquired from the 2014 to 2016 data of PORT-MIS and Terminal Operating System (TOS). Furthermore, methods and procedures to measure the actual ship's waiting rate of container terminal are proposed for ongoing measurement. In drawing the theoretical ship waiting ratio, the queuing theory is applied after deploying the ship arrival probability distribution and ship service probability distribution by the Chi Square method. As a result, the total number of ships waiting in a terminal for three years was 587, the average monthly service time and the average waiting time was 13.8 hours and 17.1 hours, respectively, and the monthly number of waiting ships was 16.3. Meanwhile, according to the queuing theory with multi servers, the ship waiting ratio is 31.1% on a 70% berth occupancy ratio. The reason behind the huge gap is the congested sailing in the peak days of the week, such as Sunday, Tuesday, and Wednesday. In addition, the number of waiting ships recorded on Sundays was twice as much as the average number of waiting ships.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.311-316
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• 2018

IMO introduced the concept of e-Navigation and proposed MSPs(Maritime Service Portfolios) concept to reduce marine accidents, to improve efficiency of ship operation, port operation, and ship operation technology. Korean e-Navigation defines S1 ~ S5 services, as the service concept focused on domestic e-Navigation service corresponding to IMO MSPs, and is constructing a system as an ongoing project. S2 service (onboard system remote monitoring service) among the concepts of Korean e-Navigation services, is a service concept that judges the emergency level according to risk if an abnormal condition occurs during navigation, and provides corresponding guidance to accident ships based on emergency level. The purpose of this paper is to provide a basic architecture proposal of Korean e-Navigation S2 service navigation safety module, based on the S2 service operation concept. To do this, we conducted a questionnaire survey to ask experts with experience with sailors, to respond to the subjective risk experienced by sailors considering effects of anomalies, including equipment failure relative to sailing and navigational safety. Risk level for each abnormal condition was classified. The basic algorithm design of the navigation safety module is composed of safety index (SI) calculation module based on results of questionnaire and expert opinions, safety level (SL) determination module according to safety index, and corresponding guidance generation module according to safety level. To conduct basic validation of basic architecture of the navigation safety module, simulation of the ship anomaly monitoring was performed, and results have been revealed.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.311-318
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• 2021

Research has been ongoing to detect ships from offshore photographs for a variety of reasons, including maritime security, identifying international trends, and social scientific research. Due to the development of artificial intelligence, R-CNN models for object detection in photographs and images have emerged, and the performance of object detection has risen dramatically. Ship detection in offshore photographs using the R-CNN model has also begun to apply to satellite photography. However, satellite images project large areas, so various objects such as vehicles, landforms, and buildings are sometimes recognized as ships. In this paper, we propose a novel methodology to improve the performance of ship detection in satellite photographs using R-CNN series models. We separate land and sea via marker-based watershed algorithm and perform morphology operations to specify RoI one more time, then detect vessels using R-CNN family models on specific RoI to reduce typology. Using this method, we could reduce the misdetection rate by 80% compared to using only the Fast R-CNN.