• Title/Summary/Keyword: 감천항

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Development of Response Scenario for a Simulated HNS Spill Incident (위험유해물질 유출사고 대응을 위한 가상시나리오 개발)

  • Lee, Moonjin;Oh, Sangwoo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.20 no.6
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    • pp.677-684
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    • 2014
  • In response to possible HNS (Hazardous and Noxious Substance) spill accident, HNS spill accident scenario and response scenario were developed. The accident area listed in scenarios is the coastal area of Busan, and scenario for possible accident in the designated area and strategies to respond the accident were developed, respectively. The scenario for accident was developed by designating HNS spill according to risk evaluation of HNS and analysis of HNS spill probability along the coastal area of Busan, and then estimating possible and potential impact from the accident. The scenario for response has been suggested as a systematical responding operations in order to effectively reduce the estimated impact from the accident. The possible HNS spill accident on the seas around Busan, has been designated by the spillage of 1,000ton of xylene due to collision accident in Gamcheon Port, and the possible impacts occurred by the accident has been simulated with the help of the atmospheric and oceanic dispersion model of xylene. In the responding scenario for the accident, a phased strategies regarding emergency rescue of peoples, protection and recovery of xylene, protective measures for the responders, and post management of the accident have been suggested.

Development of machine learning framework to inverse-track a contaminant source of hazardous chemicals in rivers (하천에 유입된 유해화학물질의 역추적을 위한 기계학습 프레임워크 개발)

  • Kwon, Siyoon;Seo, Il Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.112-112
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    • 2020
  • 하천에서 유해화학물질 유입 사고 발생 시 수환경 피해를 최소화하기 위해 신속한 초기 대응이 필요하다. 따라서, 본 연구에서는 수환경 화학사고 대응 시스템 구축을 위해 하천 실시간 모니터링 지점에서 관측된 유해화학물질의 농도 자료를 이용하여 발생원의 유입 지점과 유입량을 역추적하는 프레임워크를 개발하였다. 본 연구에서 제시하는 프레임워크는 첫 번째로 하천 저장대 모형(Transient Storage Zone Model; TSM)과 HEC-RAS 모형을 이용하여 다양한 유량의 수리 조건에서 화학사고 시나리오를 생성하는 단계, 두번째로 생성된 시나리오의 유입 지점과 유입량에 대한 시간-농도 곡선 (BreakThrough Curve; BTC)을 21개의 곡선특징 (BTC feature)으로 추출하는 단계, 최종적으로 재귀적 특징 선택법(Recursive Feature Elimination; RFE)을 이용하여 의사결정나무 모형, 랜덤포레스트 모형, Xgboost 모형, 선형 서포트 벡터 머신, 커널 서포트 벡터 머신 그리고 Ridge 모형에 대한 모형별 주요 특징을 학습하고 성능을 비교하여 각각 유입 위치와 유입 질량 예측에 대한 최적 모형 및 특징 조합을 제시하는 단계로 구축하였다. 또한, 현장 적용성 제고를 위해 시간-농도 곡선을 2가지 경우 (Whole BTC와 Fractured BTC)로 가정하여 기계학습 모형을 학습시켜 모의결과를 비교하였다. 제시된 프레임워크의 검증을 위해서 낙동강 지류인 감천에 적용하여 모형을 구축하고 시나리오 자료 기반 검증과 Rhodamine WT를 이용한 추적자 실험자료를 이용한 검증을 수행하였다. 기계학습 모형들의 비교 검증 결과, 각 모형은 가중항 기반과 불순도 감소량 기반 특징 중요도 산출 방식에 따라 주요 특징이 상이하게 산출되었으며, 전체 시간-농도 곡선 (WBTC)과 부분 시간-농도 곡선 (FBTC)별 최적 모형도 다르게 산출되었다. 유입 위치 정확도 및 유입 질량 예측에 대한 R2는 대부분의 모형이 90% 이상의 우수한 결과를 나타냈다.

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A Brief Clustering Measurement for the Korean Container Terminals Using Neural Network based Self Organizing Maps (자기조직화지도 신경망을 이용한 국내 컨테이너터미널의 클러스터링 측정소고)

  • Park, Ro-Kyung
    • Journal of Korea Port Economic Association
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    • v.26 no.1
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    • pp.43-60
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    • 2010
  • The purpose of this paper is to show the clustering measurement way for Korean container terminals by using neural network based SOM(Self Organizing Map). Inputs[Number of Employee, Quay Length, Container Terminal Area, Number of Gantry Crane], and output[TEU] are used for 3 years(2002,2003, and 2004) for 8 Korean container terminals by applying both DEA and SOM models. Empirical main results are as follows: First, the result of DEA analysis shows the possibility for clustering among the terminals and reference terminals except Gamcheon and Gwangyang terminals because of the locational closeness. Second, the result of neural network based SOM clustering analysis shows the positive clustering in clustering positions 1, 2, 3, 4, and 5. Third, the results between SOM clustering and DEA clustering show the matching ratio about 67%. The main policy implication based on the findings of this study is that the port policy planner of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the clustering measurement way for the Korean container terminals using neural network based SOM with DEA models for clustering Korean ports and terminals.

Ship's Hull Fouling Management and In-Water Cleaning Techniques (선체부착생물관리와 수중제거기술)

  • Hyun, Bonggil;Jang, Pung-Guk;Shin, Kyoungsoon;Kang, Jung-Hoon;Jang, Min-Chul
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.24 no.6
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    • pp.785-795
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    • 2018
  • The International Maritime Organization (IMO) has recognized the risk of hull fouling and announced '2011 Guidelines for the control and management of ship's biofouling to minimize the transfer of invasive aquatic species'and is planning international regulations to enforce them in the future. In this study, to effectively respond to future international regulation, we introduce the case of leading countries related to management of hull fouling and also investigate environmental risk assessment techniques for in-water cleaning. Australia and New Zealand, the leading countries in hull fouling management, have established hull fouling regulations through biological and chemical risk assessment based on in-water cleaning scenarios. Most European countries without their government regulation have been found to perform in-water cleaning in accordance with the IMO's hull fouling regulations. In the Republic of Korea, there is no domestic law for hull fouling organisms, and only approximately 17 species of marine ecological disturbance organisms, are designated and managed under the Marine Ecosystem Law. Since in-water cleaning is accompanied by diffusion of alien species and release of chemical substances into aquatic environments, results from biological as well as chemical risk assessment are performed separately, and then evaluation of in-water cleaning permission is judged by combining these two results. Biological risk assessment created 40 codes of in-water cleaning scenarios, and calculated Risk Priority Number (RPN) scores based on key factors that affect intrusion of alien species during in-water cleaning. Chemical risk assessment was performed using the MAMPEC (Marine Antifoulant Model to Predict Environmental Concentrations), to determine PEC and PNEC values based on copper concentration released during in-water cleaning. Finally, if the PEC/PNEC ratio is >1, it means that chemical risk is high. Based on the assumption that the R/V EARDO ship performs in-water cleaning at Busan's Gamcheon Port, biological risk was estimated to be low due to the RPN value was <10,000, but the PEC/PNEC ratio was higher than 1, it was evaluated as impossible for in-water cleaning. Therefore, it will be necessary for the Republic of Korea to develop the in-water cleaning technology by referring to the case of leading countries and to establish domestic law of ship's hull fouling management, suitable for domestic harbors.