• Title/Summary/Keyword: long-term wave data

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The Characteristics of Wave Statistical Data and Quality Assurance (파랑 통계자료의 특성과 신뢰성 검토)

  • Park, J.H.
    • Journal of Power System Engineering
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    • v.13 no.2
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    • pp.63-70
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    • 2009
  • This paper discusses the influence on long-tenn predictions of the ship response in ocean by using the Global Wave Statistics data, GWS, and wave information from the remote sensing satellites. GWS's standard scatter diagrams of significant wave height and zero-crossing wave period are suggested to be corrected to a round number of 0.01/1000 fitted with a statistical analytic model of the conditional lognormal distribution for zero-crossing wave period. The GEOSAT satellite data are utilized which presented by I. R. Young and G. J. Holland (1996, named as GEOSAT data). At first, qualities of this data are investigated, and statistical characteristic trends are studied by means of applying known probability distribution functions. The wave height data of GEOSAT are compared to the data observed onboard merchant ships, the data observed by measure instrument installed on the ocean-going container ship and so on. To execute a long-tenn prediction of ship response, joint probability functions between wave height and wave period are introduced, therefore long-term statistical predictions are executed by using the functions.

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Estimation of Design Wave Height for the Waters around the Korean Peninsula

  • Lee, Dong-Young;Jun, Ki-Cheon
    • Ocean Science Journal
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    • v.41 no.4
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    • pp.245-254
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    • 2006
  • Long term wave climate of both extreme wave and operational wave height is essential for planning and designing coastal structures. Since the field wave data for the waters around Korean peninsula is not enough to provide reliable wave statistics, the wave climate information has been generated by means of long-term wave hindcasting using available meteorological data. Basic data base of hindcasted wave parameters such as significant wave height, peak period and direction has been established continuously for the period of 25 years starting from 1979 and for major 106 typhoons for the past 53 years since 1951 for each grid point of the North East Asia Regional Seas with grid size of 18 km. Wind field reanalyzed by European Center for Midrange Weather Forecasts (ECMWF) was used for the simulation of waves for the extra-tropical storms, while wind field calculated by typhoon wind model with typhoon parameters carefully analyzed using most of the available data was used for the simulation of typhoon waves. Design wave heights for the return period of 10, 20, 30, 50 and 100 years for 16 directions at each grid point have been estimated by means of extreme wave analysis using the wave simulation data. As in conventional methodsi of design criteria estimation, it is assumed that the climate is stationary and the statistics and extreme analysis using the long-term hindcasting data are used in the statistical prediction for the future. The method of extreme statistical analysis in handling the extreme vents like typhoon Maemi in 2003 was evaluated for more stable results of design wave height estimation for the return periods of 30-50 years for the cost effective construction of coastal structures.

Trends of the Storm Wave Appearance on the East Coast Analyzed by using Long-term Wave Observation Data (장기실측 파랑자료 분석을 통한 동해안 폭풍파 출현 추세)

  • Jeong, Weon Mu;Ryu, Kyong-Ho;Oh, Sang-Ho;Baek, Won-dae
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.28 no.2
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    • pp.109-115
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    • 2016
  • The trend in appearance of storm waves on the east coast of Korea was investigated based on long-term wave data observed at six different stations. At the four wave stations of KIOST (Sokcho, Mukho, Hupo, and Jinha), no notable trend was found during the observation period with respect to the annual average and maximum values of the significant wave height. In addition, the annual number of the appearance of storm waves showed decreasing trend at the three stations except Jinha, where slightly increasing trend of the quantity was recognized. In contrast, at Donghea ocean data buoy of KMA, abruptly increasing trend was found for the annual average and maximum of the significant wave height and for the annual number of the appearance of storm waves as well, demonstrating lack of consistency in the observation data from Donghea buoy of KMA.

A Study on Continuous long-term Wave Observation using Remote Monitoring System (원격모니터링을 이용한 연속파랑관측에 관한 연구)

  • Shin, Bumshick
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.1
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    • pp.654-659
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    • 2018
  • In this study, continuous long-term observation is implemented with an ocean radar. Ocean radar conducts remote observation (combined) with ground-based radars, which enable a series of simultaneous observations of an extensive range of the coast with high frequency. An ocean radar for continuous long-term observation is operated at Samcheok on the east coast of Korea. Samcheok experienced tsunami damage in recent years and is the location of a nuclear power plant. In order to examine the reliability of the ocean radar, a pressure-type wave gauge, ultrasonic wave gauge, and ocean buoy are installed for the purpose of data comparison and verification. The ocean radar used in this study is an array-type HF-RADAR named WERA (WavE RAdar). The analysis of the data obtained from continuous long-term observations showed that the radar observations were in agreement with more than 90% of the wave data collected within a 25 km range from the center of two sites. Less than 1% of the entire observation data was unmeasured by the time series analysis. As a result of comparing the radar data with the direct observations made by the wave gauge, it was inferred that the RMS deviation is less than 20cm and the correlation coefficient was in the range of 0.84 ~ 0.87. Moreover, supported by such observations, a comprehensive monitoring system is being developed to provide the public with real-time reports on waves and currents via the internet.

Development of a Deep Learning-based Long-term PredictionGenerative Model of Wind and Sea Conditions for Offshore Wind Farm Maintenance Optimization (해상풍력단지 유지보수 최적화 활용을 위한 풍황 및 해황 장기예측 딥러닝 생성모델 개발)

  • Sang-Hoon Lee;Dae-Ho Kim;Hyuk-Jin Choi;Young-Jin Oh;Seong-Bin Mun
    • Journal of Wind Energy
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    • v.13 no.2
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    • pp.42-52
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    • 2022
  • In this paper, we propose a time-series generation methodology using a generative adversarial network (GAN) for long-term prediction of wind and sea conditions, which are information necessary for operations and maintenance (O&M) planning and optimal plans for offshore wind farms. It is a "Conditional TimeGAN" that is able to control time-series data with monthly conditions while maintaining a time dependency between time-series. For the generated time-series data, the similarity of the statistical distribution by direction was confirmed through wave and wind rose diagram visualization. It was also found that the statistical distribution and feature correlation between the real data and the generated time-series data was similar through PCA, t-SNE, and heat map visualization algorithms. The proposed time-series generation methodology can be applied to monthly or annual marine weather prediction including probabilistic correlations between various features (wind speed, wind direction, wave height, wave direction, wave period and their time-series characteristics). It is expected that it will be able to provide an optimal plan for the maintenance and optimization of offshore wind farms based on more accurate long-term predictions of sea and wind conditions by using the proposed model.

Characteristics of Spread Parameter of the Extreme Wave Height Distribution around Korean Marginal Seas (한국 연안 극치 파고 분포의 확산모수 특성)

  • Jeong, Shin-Taek;Kim, Jeong-Dae;Ko, Dong-Hui;Kim, Tae-Heon
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.21 no.6
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    • pp.480-494
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    • 2009
  • Long term extreme wave data are essential for planning and designing coastal structures. Since the availability of the field data for the waters around Korean peninsula is limited to provide a reliable wave statistics, the wave climate information has been generated by means of long-term wave hindcasting using available meteorological data. KORDI(2005) has proposed extreme wave data at 106 stations off the Korean coast from 1979 to 2003. In this paper, extreme data sets of wave(KORDI, 2005) have been analyzed for best-fitting distribution functions, for which the spread parameter proposed by Goda(2004) is evaluated. The calculated values of the spread parameter are in good agreement with the values based on method of moment for parameter estimation. However, the spread parameter of extreme wave data has a representative value ranging from about 1.0 to 2.8 which is larger than some foreign coastal waters, it is necessary to review deep water design wave.

Prediction of Significant Wave Height in Korea Strait Using Machine Learning

  • Park, Sung Boo;Shin, Seong Yun;Jung, Kwang Hyo;Lee, Byung Gook
    • Journal of Ocean Engineering and Technology
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    • v.35 no.5
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    • pp.336-346
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    • 2021
  • The prediction of wave conditions is crucial in the field of marine and ocean engineering. Hence, this study aims to predict the significant wave height through machine learning (ML), a soft computing method. The adopted metocean data, collected from 2012 to 2020, were obtained from the Korea Institute of Ocean Science and Technology. We adopted the feedforward neural network (FNN) and long-short term memory (LSTM) models to predict significant wave height. Input parameters for the input layer were selected by Pearson correlation coefficients. To obtain the optimized hyperparameter, we conducted a sensitivity study on the window size, node, layer, and activation function. Finally, the significant wave height was predicted using the FNN and LSTM models, by varying the three input parameters and three window sizes. Accordingly, FNN (W48) (i.e., FNN with window size 48) and LSTM (W48) (i.e., LSTM with window size 48) were superior outcomes. The most suitable model for predicting the significant wave height was FNN(W48) owing to its accuracy and calculation time. If the metocean data were further accumulated, the accuracy of the ML model would have improved, and it will be beneficial to predict added resistance by waves when conducting a sea trial test.

Long-Term Shoreline Change and Evaluation of Total Longshore Sediment Transport Rate on Hupo Beach (후포해빈에서 해안선의 장기변화 및 전연안표사량의 추정)

  • Park, Il-Heum;Lee, Young-Kweon
    • Journal of Ocean Engineering and Technology
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    • v.21 no.4
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    • pp.15-20
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    • 2007
  • The harbor siltation by longshore sediment transports has become a serious problem on the East Coast of Korea. A reasonable prediction of the longshore sediment rate is important to approach the siltation problem effectively. In the recently developed 1-line model, the empirical constants of the sediment transport formula, which include the absolute quantity of sediment transport rate and the spatial distribution of breaking wave height by wave deformation, are treated as calibration parameters. Since these constants should be determined by the very long-term shoreline data, the longshore sediment rates are much more reasonable values. The method was applied to Hupo Beach, which has experienced heavy siltation. The authors also discuss long-term shoreline change using aerial photos and the observed wave-induced current patterns. According to the result, the SW-direction sediment transport rate was $146,892m^3/year$, and the NE direction was $2,694,450m^3/year$ at Hupo Beach for the last 11 years. The siltation in Hupo Harbor might be affected by the NE-direction sediment transport from Hupo Beach.

Analysis Research on Preparation of 4th Wave (AI) of the Visegrad Group

  • Kim, Dong Hwa;Seo, Dae-Sung
    • The Journal of Asian Finance, Economics and Business
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    • v.5 no.4
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    • pp.201-211
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    • 2018
  • The paper suggests making a policy and strategies for a way of exporting Korean ICT product effectively in the EU and Eastern area, and an effective preparation of 4th industrial revolution through analysis of preparation status of 4th industrial revolution of the Visegrad group. Analyze policy, status, what they want for 4th preparation in the Visegrad group from comparing characteristics analysis of each country's official data, publication data, portal, paper, and etc. They have been preparing for 4th industrial revolution long time ago as basic research and business before 4th wave word. With these basic results, they are trying to apply such as, AI, S/W, security, ICT, etc. of 4th wave core technology. For the development of new export market in EU, the Korean team should research with university and research center or venture company. Through these cooperation, they should understand their personal characteristic, lifestyle, and what consumers want to purchase in EU. And this results can be used in South Asia and India that give a big effect to all over the world ICT market. The external impact of the 4th wave must have a long-term shift in manpower, and production policy is related to the EU's strategic role, or the preparation of the 4th wave to the V4 country in the short term.

Analysis of Extreme Wave Conditions for Long-Term Wave Observation Data Considering Directionality (방향성을 고려한 장기 파랑관측자료의 극치파랑조건 분석)

  • Kim, Gunwoo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.5
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    • pp.700-711
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    • 2022
  • In this study, deepwater design waves were estimated for 16 wave directions and various return periods based on statistical analysis of extreme waves observed for more than 20 years at three stations (Chilbal-do, Geomun-do, Donghae). These values were compared with design waves estimated based on the omni-directional wave data. The Weibull distribution was used as the probability distribution function whose parameters were determined by the least square method. The Kolmogorov-Smirnov test was applied for the goodness of fit test. Notably, the directional design waves were smaller than the omni-directional design wave for every wave direction. The maximum 50-year wave heights for directional sectors were 7.46 m (NNE), 12.05 m (S), and 9,59 m (SSW) at Chilbal-do, Geomun-do and Donghae whereas those for uni-directional wave data were 7.91 m, 13.82 m and 10.38 m, respectively. This implied possible under-estimation of the deepwater design waves for 16 wave directions being currently used in the design of offshore and coastal structures.