• Journal of Advanced Marine Engineering and Technology
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• v.39 no.2
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• pp.195-200
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• 2015

It is envisaged that the effect of increasingly stricter air emissions legislation implemented through IMO Annex VI and other local air quality controls, together with favorable financial conditions for the use of natural gas instead of liquid fuel oil as a bunker fuel, will see an increasing number of DF engine and single gas fuel engine applications to LNG carriers and other vessel types. As part of provision for the current international movements in the shipping industry to reduce GHG emission in air, new design concepts using natural gas as an alternative fuel source for propulsion of large commercial vessels, have been developed by shipyards and research institutes. In this study, an explosion analysis for a gas supply machinery room of LNG-fuelled container ship is presented. The gas fuel concept is employed for the high pressure ME-GI where a leakage in the natural gas double supply pipe to the engines is the subject of the present analysis. The consequences of a leak are simulated with computational fluid dynamics (CFD) tools to predict typical leak scenarios, gas cloud sizes and possible explosion pressures. In addition, capacity of the structure which is subject to explosion loads has been assessed.

• Journal of Navigation and Port Research
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• v.39 no.2
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• pp.99-105
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• 2015

Until recently, thermal power plants have used high-rank coals to generate electricity. The switched to low-rank coals, primarily because of the rising coal price and the advancement of combustion technology. Therefore the thermal power plants need more fuels aspect of quantity and they are going to build extra infrastructure to deal with the increased fuel demand in their specialized ports. This paper introduces the process of the economic analysis as a case study for Hadong T/P(Thermal Power) Port. This study also evaluates investment for mew projects in ports. We analyze the costs and benefits of the port investment project using various information. And then we conduct the economic analysis using NPV(net present value), B/C ratio and IRR grounded in a financial theory. Out result of the economic feasibility shows that the new project of constructing a third berth in Hadong T/P Port has positive economic value. Additionally, this study conducts the sensitivity analysis of the major variables like cost, benefit and discount rate.

• Journal of Navigation and Port Research
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• v.44 no.2
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• pp.79-87
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• 2020

In the field of logistics, the maritime shipping industry plays a critical role as the backbone of global trade activities. Nevertheless, previous studies on the commercialization and benefits of blockchain technology are limited in the field of marine logistics. Thus, the purpose of this study was to predict the benefit for each group involved in marine logistics when blockchain technology is applied. As such, 21 factors of benefits were selected for seven major logistics groups (financial institutions, freight forwarders, inland transportation, ocean carriers, port operators, port-related government authorities, and shippers) to study the benefit expected for each through the commercialization of blockchain technology. Based on the results, a different benefit level is expected for each group when blockchain technology is used. In order, ocean carriers (0.155), inland transportation (0.150), financial institutions (0.153), port operators (0.145), freight forwarders (0.142), port-related government authorities (0.129), and shippers (0.126) were found to benefit most from the use of blockchain technology. This study has industrial implications in that it presents the benefits expected when blockchain technology is realized and used in marine logistics by groups involved in logistics transactions.

• Journal of Power System Engineering
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• v.17 no.2
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• pp.95-102
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• 2013

For vessels operating in the cold climate regions, the ballast water inside or hopper tanks above the waterline may be frozen, starting at the top of the tank and at the side walls. Therefore, countermeasures against freeze-up of the ballast tank such as air-bubbling system, hot steam injecting system, heating coil system and water circulating system are taken to prevent freeze-up phenomenon; however, there are no rigorous investigations of anti-freezing to examine the effectiveness and validity of systems against freeze-up of the ballast tank, in which the temperatures are about $-25^{\circ}C$ (ambient air temperature) and $0^{\circ}C$ (sea water), respectively. In this paper, to ensure reasonable specifications for cold regions if the measures from the above-mentioned systems against freeze-up are effective, the phenomenon of ballast tank freeze-up is simulated and discussed in low temperature conditions. With the results using the commercial CFD code, CFX 14, the most cost-effective solution is conducted to prevent being frozen along the outer surface.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.216-217
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• 2019

As the shipping market deteriorates, shipping companies seek to realize economies of scale by promoting the enlargement of container ships. Container terminal operators are increasingly adopting automated equipment and systems in order to quickly provide services and attract traffic. As such, the competition for each terminal to become a hub port is intensifying. Increased automation of advanced container terminals improves productivity and efficiency In the meantime, Korea remains semi-automated. Therefore, the relevant subject survey through SPSS 23.0 program for analysis of recognition difference, We will check the awareness among stakeholders for the smooth introduction.

• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.137-150
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• 2011

Nationally and internationally reported statistics on marine accidents show that 80% or more of all marine accidents are caused fully or in part by human error. According to the statistics of marine accident causes from Korean Maritime Safety Tribunal(KMST), operating errors are implicated in 78.7% of all marine accidents that occurred from 2002 to 2006. In the case of the collision accidents, about 95% of all collision accidents are caused by operating errors, and those human error related collision accidents are mostly caused by failure of maintaining proper lookout and breach of the regulations for preventing collision. One way of reducing the probability of occurrence of the human error related marine accidents effectively is by investigating and understanding the role of the human elements in accident causation. In this paper, causal factors/root causes classification systems for marine accident investigation were reviewed and some typical human error analysis methods used in shipping industry were described in detail. This paper also proposed a human error analysis method that contains a cognitive process model, a human error analysis technique(Maritime HFACS) and a marine accident causal chains, and then its application to the actual marine accident was provided as a case study in order to demonstrate the framework of the method.

• Journal of Navigation and Port Research
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• v.38 no.1
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• pp.59-64
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• 2014

As global warming continues, the rate of ice melting in polar regions is increasing rapidly. The interest related to north polar route is increasing among not only countries near Arctic ocean but also the other countries, In the past, the classification society rule related to a design and operation of ship operating in polar area has been primarily amended by Russia, Norway and Finland located near Artic area. However recently International Maritime Organization decided to legislate the Polar Code to ensure safety of a ship operating in Arctic and Antarctic Ocean, and it is scheduled to be completed until 2014. The present paper focuses on the survey of the current enactment trends of Polar Code and suggests the confrontational strategy in related organization.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.5
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• pp.400-409
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• 2016

In recent, shipping companies have made an enormous effort to improve the operation of vessel in various approaches, due to recession of shipping market and increasing competition among shipping companies. One of important parameters for improving the efficiency of vessel is the resistance performance that consist of friction and residual resistance. Especially, it is recognized that the friction resistance tends to be affected by conditions of vessel’s surface and occupies approximately 70~90% of the total resistance for slow speed ships. In general, the surface of vessel is covered with various type of paint to reduce fouling and corrosion. As time goes by, however, it is so hull roughness would be increased by fouling over the wetted surface that anti-fouling paints, such as CDP(Controlled Depletion Paint), Tin-Free SPC(Self Polishing Co-polymer) or Foul Release, are applied evenly on the hull surface. Nevertheless, these anti-fouling paints could not prevent fouling absolutely. A fundamental study on evaluating ship resistance performance variation due to hull roughness has been performed using a commercial software, Star-CCM+, which solves the continuity and Navier-Stokes equations for incompressible and viscous flow. The results of present simulation for plate are compared with some experimental data available and the effect of surface roughness to ship resistance performance is discussed.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.497-508
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• 2019

Purpose: The purpose of this study is to overcome limitations of conventional studies that to predict Baltic Dry Index (BDI). The study proposed applications of Artificial Neural Network (ANN) named Long Short-Term Memory (LSTM) to predict BDI. Methods: The BDI time-series prediction was carried out through eight variables related to the dry bulk market. The prediction was conducted in two steps. First, identifying the goodness of fitness for the BDI time-series of specific ANN models and determining the network structures to be used in the next step. While using ANN's generalization capability, the structures determined in the previous steps were used in the empirical prediction step, and the sliding-window method was applied to make a daily (one-day ahead) prediction. Results: At the empirical prediction step, it was possible to predict variable y(BDI time series) at point of time t by 8 variables (related to the dry bulk market) of x at point of time (t-1). LSTM, known to be good at learning over a long period of time, showed the best performance with higher predictive accuracy compared to Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN). Conclusion: Applying this study to real business would require long-term predictions by applying more detailed forecasting techniques. I hope that the research can provide a point of reference in the dry bulk market, and furthermore in the decision-making and investment in the future of the shipping business as a whole.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.701-716
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• 2022

Purpose: This study aims to predict the dry cargo transportation market economy. The subject of this study is the BDI (Baltic Dry Index) time-series, an index representing the dry cargo transport market. Methods: In order to increase the accuracy of the BDI time-series, we have pre-processed the original time-series via time-series decomposition and data augmentation techniques and have used them for ANN learning. The ANN algorithms used are Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) to compare and analyze the case of learning and predicting by applying time-series decomposition and data augmentation techniques. The forecast period aims to make short-term predictions at the time of t+1. The period to be studied is from '22. 01. 07 to '22. 08. 26. Results: Only for the case of the MAPE (Mean Absolute Percentage Error) indicator, all ANN models used in the research has resulted in higher accuracy (1.422% on average) in multivariate prediction. Although it is not a remarkable improvement in prediction accuracy compared to uni-variate prediction results, it can be said that the improvement in ANN prediction performance has been achieved by utilizing time-series decomposition and data augmentation techniques that were significant and targeted throughout this study. Conclusion: Nevertheless, due to the nature of ANN, additional performance improvements can be expected according to the adjustment of the hyper-parameter. Therefore, it is necessary to try various applications of multiple learning algorithms and ANN optimization techniques. Such an approach would help solve problems with a small number of available data, such as the rapidly changing business environment or the current shipping market.