• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.207-211
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• 2004

The final goal of this research is to establish the relative dangerousness D/B for factors on seakeeping performance. This D/B is essential to develope the seakeeping performance evaluation system built-on-ship. The system is composed of the apparatus for measuring a vertical acceleration to be generated by the ship's motions, computer for calculating the synthetic seakeeping performance index and monitor for displaying the evaluating diagram of navigational safety of ship. In this paper, a methodology on the establishment of the relative dangerousness D/B for factors on seakeeping performance is presented by a numerical simulations, playing an important role on the algorithm of the program for calculating the synthetic seakeeping performance index. Finally, It is investigated whether the relative dangerousness D/B can be realized an accurate values according to the loading conditions, weather conditions, wave directions end present ship's speed of a model ship.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.395-405
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• 2018

Seakeeping safety module in Korean e-Navigation system is one of the ship remote monitoring services that is employed to ensure the safety of ships by monitoring the ship's real time performance and providing a warning in advance when the abnormal conditions are encountered in seakeeping performance. In general, seakeeping performance has been evaluated by simulating ship motion analysis under specific conditions for its design. However, due to restriction of computation time, it is not realistic to perform simulations to evaluate seakeeping performance under real-time operation conditions. This study aims to introduce a reasonable and faster method to predict a ship's roll motion which is one of the factors used to evaluate a ship's seakeeping performance by using a machine learning-based surrogate model. Through the application of various learning techniques and sampling conditions on training data, it was observed that the difference of roll motion between a given surrogate model and motion analysis was within 1%. Therefore, it can be concluded that this method can be useful to evaluate the seakeeping performance of a ship in real-time operation.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.323-330
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• 2018

The Korean e-Navigation system is a Korean approach to correspond with implementation of IMO e-Navigation. It provides five services, among them SV20 service, a ship remote monitoring system that collects and processes sensor information related to fire, navigation, and seakeeping performance safety. The system also detects abnormal conditions such as fires, capsizing, sinking, navigation equipment failure during navigation, and calculates the safety index and determines the emergency level. According to emergency level, it provides appropriate emergency response guidance for the onboard operator. The fire safety module is composed of three sub-modules; each module is the safety index sub-module, the emergency level determination sub-module and emergency response guidance sub-module. In this study, operational concept of the fire safety module in SV20 service is explained, and fire safety assessment factors are estimated, to calculate the fire safety index. Fire assessment factors included 'Fire detector position factor,' 'Smoke diffusion rate factor,' and 'Fire-fighting facilities factor.'

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.45-46
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• 2018

S2 module, which is one of the Korean type e-Navigation services, is a service concept that monitors the situation onboard and provides an emergency level determination and response guidance to the ship when an alarm occurs. S2 module is divided into fire/ seakeeping / navigation safety sub-module. In this paper, the concept of S2 service based on actual ship is explained through the response guidance case study of navigation safety module in case of abnormal condition in the passenger ship H.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.41-42
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• 2018

This study is about the prediction of ship's roll motion characteristic which has been used for evaluating ship's seakeeping performance. In order to obtain the ship's roll RAO during voyage, this paper utilized machine learning-based surrogate model. By comparing the prediction result data of surrogate model with test data, we suggest the best approximation technique and data sampling interval of the surrogate model appropriate for predicting the ships' roll motion characteristic.