• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.176-178
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• 2019

부산항은 초미세먼지 기준으로 세계 10대 오염항만으로 보고되어, 우리나라 항만도시의 대기오염도가 심각한 수준임을 알 수 있다. 이처럼 선박, 하역장비, 대형화물차 등 항만오염배출원에서 발생하는 미세먼지는 항만지역 내외를 가리지 않고 배후도시 지역민의 삶의 질에 큰 영향을 미친다. 이외 하역장비, 대형화물차 등 항만운영으로 인해 발생하는 소음 또한 지역민 주거생활환경에 영향을 미치는 주요 요인이다. 이 연구는 부산항 신항의 배후도시인 창원시 항만배후지역(웅동생활권)의 주민이 겪고 있는 환경피해실태를 파악하고자 항만배후지역의 생활환경 중 체감오염도가 높은 미세먼지($PM_{10}$)와 소음에 대한 기초 영향조사 수행하였다. 연구결과 신항(창원) 배후지역의 미세먼지($PM_{10}$) 농도는 인근 지역인 창원시 경화동, 부산시 녹산동보다 높게 조사되었고, 경남지역 대기측정소(21개)의 평균보다 최대 $25{\mu}g/m^3$ 이상 높게 측정 되었다. 또한, 신항(창원) 배후지역의 소음도는 환경관리기준을 초과하는 것으로 조사되었다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.58-60
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• 2013

부산항 입항 및 출항 대기, 통과 선박의 중간 기항지로 이용되는 부산 남외항 대기 정박지는 N-1~N-5으로 구성되며 현재, 최대 90척이 동시에 정박 가능한 집단 정박지 지정방식으로 지정되어 있다. 부산 남외항 대기 정박지는 입 출항 선박 및 통과 선박, 급유선 등의 교통에 따른 충돌, 접촉 등의 해양 사고와 갑작스러운 돌풍 등 기상악화에 따른 충돌, 접촉 및 좌초 등의 해양 사고가 발생하고 있다. 부산 남외항 대기 정박지의 자연 환경, 이용현황, 기상, 입 출항 선박 및 통과 선박의 교통 흐름을 종합적으로 살펴보고 부산 남외항 대기 정박지에서 발생하는 해양사고를 분석하였다. 따라서 부산 남외항 대기 정박지의 운영상의 문제점을 찾고, 해상교통조사 설문조사 이론적 근거를 기초로 안전도 평가 시스템을 사용하여, 향후 개선방향을 제시하였다.

• 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 the Korean Society of Marine Environment & Safety
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• v.25 no.5
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• pp.519-526
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• 2019

This study proposes a methodology for estimating the appropriate capacity of anchorage for ports requiring the establishment of waiting anchorage and then applying the methodology to the ports in Jinhae Bay to compare it with the anchorage capacity of major ports in Korea. To estimate the appropriate anchorage capacity, the "Anchorage Capacity Index" was used, which was calculated from the "Total Gross Tonnage" and "Simultaneous Anchoring Capacity". The calculations were made according to the anchorage capacity index of 0.89 of the target harbors. The adequate anchorage capacity index for the new waiting anchorage was analyzed at a level of 6.0. If the concept of anchorage capacity index suggested in this study is reflected as a new design criteria of waiting anchorage, it will be helpful for the safety of berth, safety of anchorage and effective operation of harbor.

• Proceedings of KOSOMES biannual meeting
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• 2018.06a
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• pp.128-128
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• 2018

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.371-372
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• 2002

인천항은 한국의 주요항만의 하나로 원자재 수입 화물을 취급하는 항만이다. 수입 원자재 가운데 대두박 같은 사료 부 원료의 취급 시 강한 바람, 차량의 이동 저장시설에서의 상하차 등에 의해서 다량의 비산 먼지가 발생하며 이것이 주된 비산 먼지로 인천항만 주위의 주요 오염원이 되고 있는 실정이다. (Jeon et al.,2000) (중략)

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.141-143
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• 2019

Vessel Traffic Service (VTS) increases the efficiency of maritime traffic in terms of reducing marine accidents and the efficient use of port facilities. This means that ports and waterways have their own capacities and can be safely adapted to their capacity through proper traffic management of the VTS. Proper traffic management can reduce the number of vessels and unnecessary waiting in ports, which can lead to economic benefits of ups and port terminals. On the other hand, Korean ports and waterways have restrictions on the maximum speed for safety, but there is no restriction on the minimum speed. However, ships that operate at low speeds in ports and waterways may be able to occupy long periods of operational routes, which may impede efficient port operation. Therefore, the purpose of this study is to propose the minimum speed of ship for efficient port and waterway use. To this end, we reviewed the current laws and systems and proposed the appropriate minimum speed in the waterway using the theory of queue.

• Journal of Navigation and Port Research
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• v.40 no.6
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• pp.421-430
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• 2016

In this study, a gate simulation model was developed to reduce the truck waiting time for trucking companies servicing container terminals. To verify the developed model, 4 weeks of truck gate-in/gate-out data was collected in December 2014 at the Port of Busan New Port. Also, the existing gate system was compared to the proposed gate system using the developed simulation model. The result showed that based on East gate-in, a maximum number of 50 waiting trucks with a maximum waiting time of 120 minutes. With the proposed system the maximum number of waiting trucks was 10 with a maximum waiting time of 5.3 minutes. Based on West gate-in, the maximum number of waiting trucks was 17 and the maximum waiting time was 34 minutes in the existing gate system. With the proposed system the maximum number of waiting trucks was 10 with a maximum waiting time of 5.3 minutes. Based on West gate-out, the maximum number of waiting trucks was 11 with a maximum waiting time of 5.5 minutes. With the proposed system the maximum number of waiting trucks was 9 with a maximum waiting time of 4.4 minutes. This developed model shows how many waiting trucks there are, depending on the gate-in/gate-out time of each truck. This system can be used to find optimal gate system operating standards by assuming and adjusting the gate-in/gate-out time of each truck in different situations.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.344-350
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• 2022

Due to the increase in container cargo volume, the congestion of container terminals is increasing and the waiting time of gate in-out trucks has significantly lengthened at container yards and gates, resulting in severe inefficiency in gate in-out truck operations as well as port operations. To resolve this problem, the Busan Port Authority and terminal operator provide services such VBS, terminal congestion information, and expected operation processing time information. However, the visible effect remains insufficient, as it may differ from actual waiting time.. Thus, as basic data to resolve this problem, this study presents deep learning based average gate in-out truck waiting time prediction models, using container gate in-out information at Busan New Port. As a result of verifying the predictive rate through comparison with the actual average waiting time, it was confirmed that the proposed predictive models showed high predictive rate.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2007.10a
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• pp.111-112
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• 2007