• 한국항만학회지
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• 제5권2호
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• pp.19-37
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• 1991

This work aims to : establish a model of the container physical distribution system of Pusan port comprising 4 sub-systems of a navigational system, on-dock cargo handling/transfer/storage system, off-dock CY system and an in-land transport system : examine the system regarding the cargo handling capability of the port and analyse the cost of the physical distribution system. The overall findings are as follows : Firstly in the navigational system, average tonnage of the ships visiting the Busan container terminal was 33,055 GRT in 1990. The distribution of the arrival intervals of the ships' arriving at BCTOC was exponential distribution of $Y=e^{-x/5.52}$ with 95% confidence, whereas that of the ships service time was Erlangian distribution(K=4) with 95% confidence, Ships' arrival and service pattern at the terminal, therefore, was Poisson Input Erlangian Service, and ships' average waiting times was 28.55 hours In this case 8berths were required for the arriving ships to wait less than one hour. Secondly an annual container through put that can be handled by the 9cranes at the terminal was found to be 683,000 TEU in case ships waiting time is one hour and 806,000 TEU in case ships waiting is 2 hours in-port transfer capability was 913,000 TEU when berth occupancy rate(9) was 0.5. This means that there was heavy congestion in the port when considering the fact that a total amount of 1,300,000 TEU was handled in the terminal in 1990. Thirdly when the cost of port congestion was not considered optimum cargo volume to be handled by a ship at a time was 235.7 VAN. When the ships' waiting time was set at 1 hour, optimum annual cargo handling capacity at the terminal was calculated to be 386,070 VAN(609,990 TEU), whereas when the ships' waiting time was set at 2 hours, it was calculated to be 467,738 VAN(739,027 TEU). Fourthly, when the cost of port congestion was considered optimum cargo volume to be handled by a ship at a time was 314.5 VAN. When the ships' waiting time was set at I hour optimum annual cargo handling capacity at the terminal was calculated to be 388.416(613.697 TEU), whereas when the ships' waiting time was set 2 hours, it was calculated to be 462,381 VAN(730,562 TEU).

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2018년도 공동국제학술발표회
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• pp.63-63
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• 2018

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2017년도 공동학술발표회
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• pp.57-58
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• 2017

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2017년도 추계학술발표회
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• pp.217-217
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• 2017

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2017년도 추계학술발표회
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• pp.218-218
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• 2017

• 한국해양공학회지
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• 제33권1호
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• pp.98-98
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• 2019

• 한국안전학회지
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• 제35권3호
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• pp.79-85
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• 2020

Ahn-heung Proving Ground(APG) of Agency for Defense Development(ADD) is the only weapon test site which has been performing firing tests for many kinds of missile, artillery and ammunition. APG has been performing the firing tests of so many times every year. The tests related to missiles, artillery and ammunitions cover 80% among the quantity of annual test events. The target area of many kinds of missile, artillery and ammunition is on the sea. Therefore, APG has its marine firing ranges which were approved by the ministry of Defense. Both weapons and ships can run into each other on the sea. APG has to monitor and detect the positions of the ships in the specific dangerous zone on the sea. The positions of the ships are detected by Scanter 2001 radar and GPS100 detection radar. Evading the time period when the ships appear very often on the sea may be a good solution to keep the maritime safety. And evading the place where the ships appear very often on the sea may be a good solution as well. This paper is to analyze the ships' distribution characteristics of marine firing range, which are to raise the efficiency of many kinds firing tests which have been performed in APG of ADD. Ship distribution data from February 2014 to December 2016 were used in this paper. Ship distribution was analyzed with monthly data, seasonal data and etc. The number of the ships in approved sea area is higher in the morning than in the afternoon, and in fall than other seasons, and from August to November, and below 0.5 m in the hight of wave. Using the these conditions, we can raise the test efficiency of many kinds firing tests and guarantee maritime safety. The number of the ships in approved sea area is entirely unrelated to visibility of the sea. The time period when the number of the ships are high on the sea is morning. The season when the number of the ships are comparatively high on the sea is fall. APG of ADD could raise the efficiency of the firing tests and improve the maritime safety, using the analysis results of the characteristics on the ship distribution.

• 한국산업보건학회지
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• 제21권3호
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• pp.123-127
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• 2011

Objectives: The purpose of this study was to investigate the status of asbestos-containing materials (ACMs) used on ships and to consider measures for preventing worker exposure to asbestos fibers. Methods: A total of 17 ships including 16 ships under repair and a ship under construction at shipyards in Korea were investigated. Bulk samples were collected from suspected ACMs on engine exhaust pipes, boiler steam pipes, generator exhaust pipes, and etc. in ships in order to identify the presence of ACMs. Types and contents of asbestos were determined using polarized light microscopy (PLM). Results: ACMs were found from 14 ships out of 17 ships investigated. Only chrysotile asbestos was found from all samples. ACMs were mainly found from samples collected at the exhaust pipes of the engine, generator and incinerator, and boiler steam pipes where exhaust gases or steam of high temperature pass through. In most cases, types of ACMs were asbestos-containing fabrics such as asbestos tape. Friable ACMs were also found in some cases. Use of ACMs on ships was relevant to built time and owner of the ships rather than type and tonnage of the ships. Conclusions: ACMs were found from most ships built prior to 2000s. Therefore, measures for preventing asbestos-related diseases such as preparation of asbestos map on the ship and installation of warning signs, hazard communication with workers (ship-repairing workers, engine room workers and etc.), and follow-up for worker's health management are needed.

• 디지털융복합연구
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• 제19권10호
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• pp.195-202
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• 2021

본 연구의 목적은 국적선을 용도별로 여객선, 화물선, 유조선, 예선, 부선, 기타선으로 구분하여 각각 변동률을 살펴보고 방향성을 상호 비교 분석하는데 있다. 본 연구는 통계청 KOSIS "교통물류 => 운항선박통계 => 국적선 보유현황"에서 2011년 1월부터 2021년 3월까지 총 123개 월간자료를 검색하였다. 이를 위해 각 선박별로 전월대비 증감률을 산출하여 상승률과 변동률을 분석하였다. 상관관계분석에서 총합은 예선, 부선, 유조선, 화물선, 여객선 순으로 높은 관계를 보여 주었다. 회귀분석에서 각 선박들은 모두 통계적으로 유의하게 도출되었으며 상호 독립적으로 변동하는 것으로 나타났다. 상승률은 지난 분석기간 동안 여객선, 유조선, 예선, 부선, 화물선 순으로 높게 증가하였다. Scatter Charts 분석에서 총합에 대해 보선과 예선은 일정 수준 이상의 동조화현상을 보여주었다. 각 선박별 동조화현상은 다소 낮게 산출되어 각 선박별 연관성은 낮은 것으로 나타났다. 그러나 유조선과 예선, 유조선과 보선, 예선과 보선은 상대적으로 동조화현상이 높아 상대적으로 연관성이 크게 나타나 있다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제9권4호
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• pp.446-459
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• 2017

Naval ships are assigned many and varied missions. Their performance is critical for mission success, and depends on the specifications of the components. This is why performance analyses of naval ships are required at the initial design stage. Since the design and construction of naval ships take a very long time and incurs a huge cost, Modeling and Simulation (M & S) is an effective method for performance analyses. Thus in this study, a simulation core is proposed to analyze the performance of naval ships considering their specifications. This simulation core can perform the engineering level of simulations, considering the mathematical models for naval ships, such as maneuvering equations and passive sonar equations. Also, the simulation models of the simulation core follow Discrete EVent system Specification (DEVS) and Discrete Time System Specification (DTSS) formalisms, so that simulations can progress over discrete events and discrete times. In addition, applying DEVS and DTSS formalisms makes the structure of simulation models flexible and reusable. To verify the applicability of this simulation core, such a simulation core was applied to simulations for the performance analyses of a submarine in an Anti-SUrface Warfare (ASUW) mission. These simulations were composed of two scenarios. The first scenario of submarine diving carried out maneuvering performance analysis by analyzing the pitch angle variation and depth variation of the submarine over time. The second scenario of submarine detection carried out detection performance analysis by analyzing how well the sonar of the submarine resolves adjacent targets. The results of these simulations ensure that the simulation core of this study could be applied to the performance analyses of naval ships considering their specifications.