Dong Hui Ko

Development of the Inter-tidal Exposure Duration Formulae Using Tidal Harmonic Constants

A new formulae for the estimation of the exposure duration in the inter-tidal zone are developed. The exposure duration is one of the most important factors influencing the habitat distribution of the benthic organisms. The formulae can estimate the exposure duration only using the four major tidal harmonic constants available in almost coastal areas. It is easier than the existing method using the frequency analysis of the hourly tidal elevation data. The estimation results by using the formulae suggested in this study are compared with the value by using the observed tidal elevation data analysis in the west coast, Korea. The mean RMS (root-mean squared) errors ranged form 0.8 to 1.4%. It can be used to simply estimate the accurate exposure duration in the region not having the longterm hourly tidal elevation data.

Error analysis on the Offshore Wind Speed Estimation using HeMOSU-1 Data

In this paper, error analyses on the calculation of offshore wind speed have been conducted using HeMOSU-1 data to develop offshore wind energy in Yeonggwang sea of Korea and onshore observed wind data in Buan, Gochang and Yeonggwang for 2011. Offshore wind speed data at 98.69 m height above M.S.L is estimated using relational expression induced by linear regression analysis between onshore and offshore wind data. In addition, estimated offshore wind speed data is set at 87.65 m above M.S.L using power law wind profile model with power law exponent(0.115) and its results are compared with the observed data. As a result, the spatial adjustment error are 1.6~2.2 m/s and the altitude adjustment error is approximately 0.1 m/s. This study shows that the altitude adjustment error is about 5% of the spatial adjustment error. Thus, long term observed data are needed when offshore wind speed was estimated by onshore wind speed data. because the conversion of onshore wind data lead to large error.

Analysis on the Estimation Error of the Lowest and Highest Astronomical Tides using the Wido Tidal Elevation Data

In designing of the wind power facilities, the highest and lowest astronomical tides (HAT and LAT) are needed in terms of an international design tidal water levels. The AHHW and ALLW, however, have been used as the design tidal levels in Korea. The HAT and LAT in the Wido coastal sea should be estimated to satisfy the standard because the pilot wind power facilities will be located in the adjacent Wido coastal sea. In this study, the HAT and LAT are estimated using the 31-years hourly tidal elevation data of the Wido tidal gauging station and the nodal variation patterns of the major lunar components, such as , , and , are analysed to check the expected long-term lunar cycle, i.e., 18.61-year`s nodal variation patterns. The temporal amplitude variations of the , , and clearly show the 18.61-years periodic patterns in case of the no-nodal correction condition. In addition, the suggested HAT and LAT elevations, estimated as the upper and lower confidence limits of the yearly HAT and LAT elevations, show 40 cm greater than AHHW and 35 cm lower than ALLW, respectively.

Numerical Simulation Test of Scour around Offshore Jacket Structure using FLOW-3D

As offshore structures such as offshore wind and offshore platforms have been installed frequently in ocean, scour effects are considered important. To test the scour effect, numerical simulation of scour has been carried out. However, the test was usually conducted under the uni-directional flow without bi-directional current flow in western sea of Korea. Thus, in this paper, numerical simulations of scour around offshore jacket substructure of HeMOSU-1 installed in western sea of Korea are conducted using FLOW-3D. The conditions are uni-directional and bi-directional flow considering tidal current. And these results are compared to measured data. The analysis results for 10,000 sec show that under uni-directional conditions, maximum scour depth was about 1.32 m and under bidirectional conditions, about 1.44 m maximum scour depth occurred around the structure. Meanwhile, about 1.5~2.0 m scour depths occurred in field observation and the result of field test is similar to result under bi-directional conditions.

Extreme Offshore Wind Estimation using Typhoon Simulation

Long-term measured wind data are absolutely necessary to estimate extreme offshore wind speed. However, it is almost impossible to collect offshore wind measured data. Therefore, typhoon simulation is widely used to analyze offshore wind conditions. In this paper, 74 typhoons which affected the western sea of Korea during 1978-2012(35 years) were simulated using Holland(1980) model. The results showed that 49.02 m/s maximum wind speed affected by BOLAVEN(1215) at 100 m heights of HeMOSU-1 (Herald of Meteorological and Oceanographic Special Unit 1) was the biggest wind speed for 35 years. Meanwhile, estimated wind speeds were compared with observed data for MUIFA, BOLAVEN, SANBA at HeMOSU-1. And to estimate extreme wind speed having return periods, extreme analysis was conducted by assuming 35 annual maximum wind speed at four site(HeMOSU-1, Gunsan, Mokpo and Jeju) in western sea of the Korean Peninsular to be Gumbel distribution. As a results, extreme wind speed having 50-year return period was 50 m/s, that of 100-year was 54.92 m/s at 100 m heights, respectively. The maximum wind speed by BOLAVEN could be considered as a extreme winds having 50-year return period.

Statistical Characteristics of Hourly Tidal Levels around the Korean Peninsula

한반도 연안 주요 조위관측소 조위자료를 선정하여 확률분포 측면에서 분석을 수행함으로써 조위 특성 및 통계적인 매개변수들을 분석하였다. 조석현상이 우세한 인천과 군산 자료의 조위확률 분포는 HWONT와 LWONT에서 2개의 대칭형 첨두형태를 보이고, 목포 자료의 경우 비대칭형 첨두형태를 보이고 있다. 반면에 제주, 여수, 부산 자료의 경우 편평한 첨두형태를 보이고, 포항, 속초 자료의 경우 1개의 첨두형태를 보이고 있다. 본 연구에서 노출과 침수 관계식으로 제안한 6개의 매개변수를 가진 가우스 혼합분포 모형은 정확하고, 관측결과와도 잘 일치하고 있다. σ₁, σ₂ 매개변수는 LWONT, HWONT와 σ₁, σ₂ 매개변수는 평균조차와 밀접하다. σ₁, σ₂는 제안한 확률분포의 최빈값에 해당한다.

Estimation on the Radius of Maximum Wind Speed using RSMC Best Track Data

Typhoon simulation method is widely used to estimate sea surface wind speeds during the typhoon periods. Holland (1980) model has been regarded to provide relatively better results for observed wind data. JTWC or RSMC best track data are available for typhoon modeling, but these data show slightly different because the data generation process are different. In this paper, a Newton-Raphson method is used to solve the two nonlinear equations based on the Holland model that is formed by the two typhoon parameters, i.e. the longest radius of 25 m/s and 15 m/s wind speeds, respectively. The solution is the radius of maximum wind speed which is of importance for typhoon modeling. This method is based on the typhoon wind profile of JMA and it shows that Holland model appears to fit better the characteristics of typhoons on the temporal and spatial changes than that of the other models. In case of using RSMC best track data, the method suggested in this study shows better and more reasonable results for the estimation of radius of maximum wind speed because the consistency of the input data is assured.

Estimation of Probability Distribution Functions for Water Temperature Data in Korean Coasts

As the temperature data show a distribution pattern with a number of peaks, assumption of normal distribution will result in a serious bias in the analysis. In this study, the Gaussian Mixture Distribution (GMD), a type of bimodal distribution, is presumed as a frequency distribution for the water temperature, in order to estimate the optimal parameter and to carry out the relation analysis between the optimal parameter and the basic statistical information such as mean and variance on the data. By the way, an estimation formulae to compute the frequency distribution of the data is developed by computing the parameters of GMD (i.e. , , , , , ) by means of the major characteristic values, such as mean, standard deviation and skewness of the data. The formulae shows an excellent coincidence with the result from the observation data, in the RMS limit accuracy of 5%.

Assessment of Offshore Wind Power Potential in the Western Seas of Korea

In this paper, annual wind data in 2014 at six locations(Seosudo, Gadaeam, Sibidongpa, Galmaeyeo, Haesuseo, Jigwido) are collected and analyzed in order to review optimal candidate site for offshore wind farm in the Western Seas of Korea. Observed wind data is fitted to Rayleigh and Weibull distribution and annual energy production is estimated according to wind frequency. GWE-3kH(3 kW-class) and GWE-10KU (10 kW-class) turbine are selected as wind turbine. Also, power curve are used to calculate wind energy potential. As a result, annual mean wind speed at six locations(Seosudo, Gadaeam, Sibidongpa, Galmaeyeo, Haesuseo, Jigwido) were calculated about 4.60, 4.5, 5.00, 5.13, 5.51, 5.90 m/s, respectively. In addition, annual energy production were estimated at 10,622.752, 11,313.05, 13,509.41, 14,899.55, 17,106.13, 19,660.85 kWh. Generally, annual mean energy density were between poor and marginal class and capacity factor at Jigwido was calculated at 22.44%. Its value is higher than the others.

Estimation on the Distribution Function for Coastal Air Temperature Data in Korean Coasts

Water temperature due to climate change can be estimated using the air temperature because the air and water temperatures are closely related and the water temperatures have been widely used as the indicators of the environmental and ecological changes. It is highly necessary to estimate the frequency distribution of the air and water temperatures, for the climate change derives the change of the coastal water temperatures. In this study, the distribution function of the air temperatures is estimated by using the long-term coastal air temperature data sets in Korea. The candidate distribution function is the bi-modal distribution function used in the previous studies, such as Cho et al.(2003) on tidal elevation data and Jeong et al.(2013) on the coastal water temperature data. The parameters of the function are optimally estimated based on the least square method. It shows that the optimal parameters are highly correlated to the basic statistical informations, such as mean, standard deviation, and skewness coefficient. The RMS error of the parameter estimation using statistical information ranges is about 5 %. In addition, the bimodal distribution fits good to the overall frequency pattern of the air temperature. However, it can be regarded as the limitations that the distribution shows some mismatch with the rapid decreasing pattern in the high-temperature region and the some small peaks.