• Title/Summary/Keyword: Marine environment prediction

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Time Dependent Chloride Transport Evaluation of Concrete Structures Exposed to Marine Environment (해안 환경 하에 있는 콘크리트 구조물의 시간의존적 염화물침투 평가)

  • Song, Ha-Won;Pack, Seung-Woo;Ann, Ki-Yong
    • Journal of the Korea Concrete Institute
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    • v.19 no.5
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    • pp.585-593
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    • 2007
  • This paper presents a model for durability evaluation of concrete structures exposed to marine environment, considering mainly a build-up of surface chloride $(C_s)$ as well as diffusion coefficient (D) and chloride threshold level $(C_{lim})$. In this study, time dependency of $C_s$ and D were extensively studied for more accurate evaluation of service life of concrete structures. An analytical solution to the Fick's second law was presented for prediction of chloride ingress for time varying $C_s$. For the time varying $C_s$, a refined model using a logarithm function for time dependent $C_s$ was proposed by the regression analysis, and averaging integrated values of the D with time over exposed duration were calculated and then used for prediction of the chloride ingress to consider time dependency of D. Durability design was also carried out for railway concrete structures exposed to marine environment to ensure 100 years of service life by using the proposed models along with the standard specification on durability in Korea. The proposed model was verified by the so-called performance-based durability design, which is widely used in Europe. Results show that the standard specification underestimates durability performances of concrete structures exposed to marine environment, so the cover depth design using current durability evaluation in the standard specifications is very much conservative. Therefore, it is found that utilizing proposed models considering time dependent characteristics of $C_s$ and D can evaluate service lift of concrete structures in marine environment more accurately.

Collision Cause-Providing Ratio Prediction Model Using Natural Language Processing Analytics (자연어 처리 기법을 활용한 충돌사고 원인 제공 비율 예측 모델 개발)

  • Ik-Hyun Youn;Hyeinn Park;Chang-Hee, Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.30 no.1
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    • pp.82-88
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    • 2024
  • As the modern maritime industry rapidly progresses through technological advancements, data processing technology is emphasized as a key driver of this development. Natural language processing is a technology that enables machines to understand and process human language. Through this methodology, we aim to develop a model that predicts the proportions of outcomes when entering new written judgments by analyzing the rulings of the Marine Safety Tribunal and learning the cause-providing ratios of previously adjudicated ship collisions. The model calculated the cause-providing ratios of the accident using the navigation applied at the time of the accident and the weight of key keywords that affect the cause-providing ratios. Through this, the accuracy of the developed model could be analyzed, the practical applicability of the model could be reviewed, and it could be used to prevent the recurrence of collisions and resolve disputes between parties involved in marine accidents.

A Study on Estimate Model for Peak Time Congestion

  • Kim, Deug-Bong;Yoo, Sang-Lok
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.20 no.3
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    • pp.285-291
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    • 2014
  • This study applied regression analysis to evaluate the impact of hourly average congestion calculated by bumper model in the congested area of each passage of each port on the peak time congestion, to suggest the model formula that can predict the peak time congestion. This study conducted regression analysis of hourly average congestion and peak time congestion based on the AIS survey study of 20 ports in Korea. As a result of analysis, it was found that the hourly average congestion has a significant impact on the peak time congestion and the prediction model formula was derived. This formula($C_p=4.457C_a+29.202$) can be used to calculate the peak time congestion based on the predicted hourly average congestion.

Evaluation of the Influence of a Convective Term Caused by Various Finite Difference Schemes in General Curvature Coordinate (일반곡선 좌표계 사용시 대류항의 차분스킴에 의한 영향 평가)

  • 이연원
    • Journal of Advanced Marine Engineering and Technology
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    • v.18 no.3
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    • pp.94-101
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    • 1994
  • To develope the new simulator for the analysis of fluid flow information, the influence of various convective difference schemes were evaluated. General curvilinear coordinate system with nonorthogonal grids was adopted for the successful analysis of various complex geometries. Computation results show that if we can not obtain full grid numbers within available computational environment, we need to use higher order finite difference schemes to keep the prediction accuracy.

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Preliminary Study for Establishing the Realtime Ocean Prediction System in Busan Harbor (부산항 실시간 해양예보시스템 구축을 위한 기초연구)

  • Jung, Yun-Chul;Lee, Ho-Jin
    • Journal of Navigation and Port Research
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    • v.32 no.3
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    • pp.245-250
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    • 2008
  • Recently the numerical prediction technique is applied to many fields, because numerical models are developed so much for last decades. The real-time ocean prediction system is one of them and is capable of providing the real-time marine information for users to promote the safety af maritime traffic and preservation of marine resources. The system is composed of observing system, data distribution system and modelling system. In this study authors develop the modelling system and show the results as preliminary study for establishing the real-time ocean prediction system in Busan port. The system test is performed only for M2 tidal modelling due to the lack qf observation data, thus a full-scale test is required in future if enough data are provided Also observing system and data distribution system will be constructed continuously in future, then service for real-time data for users will be initiated.

Field Research for the Durability Assessment Factor for deriving the Carbonation of Concrete Bridges in the Marine Environment (해양 환경하 콘크리트 교량의 탄산화 내구성능 평가 인자 도출을 위한 현장조사 연구)

  • Chai, Won-Kyu;Lee, Myeong-Gu;Son, Young-Hyun
    • Journal of the Korean Society of Safety
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    • v.30 no.6
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    • pp.102-109
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    • 2015
  • In this study, on the basis of the results of the field survey and the theoretical consideration for Korean Standard Specification for concrete durability and maintenance, the following conclusions are derived. From the survey, the prediction equation of carbonation depth for the southwest region in Korea is experimentally proposed, $y_p=5.865{\sqrt{t}}$, which predicts about 60mm of the carbonation depth for the concrete structures of 100 years, a 1st class of target endurance period, under a combined deterioration environment like a marine environment. Considering that the marginal value for a carbonation depth limitation under very severely marine environment is 25mm, in accordance with the Specification, it is found that the predicting carbonation depth for the concrete cover depths, 100mm and 60mm are 63mm and 29.4mm, respectively. In conclusion, according to the equation and the Specification, it is strongly required that the reinforced concrete structures with the cover depth under 100mm have to make a protection from combined deterioration factors by any methods like a surface coating, an increment of cover depth or an application of a special concrete.

Development of a Water Quality Indicator Prediction Model for the Korean Peninsula Seas using Artificial Intelligence (인공지능 기법을 활용한 한반도 해역의 수질평가지수 예측모델 개발)

  • Seong-Su Kim;Kyuhee Son;Doyoun Kim;Jang-Mu Heo;Seongeun Kim
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.1
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    • pp.24-35
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    • 2023
  • Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.