• 대기
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• 제18권3호
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• pp.171-182
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• 2008

In this study, we analyzed the spatial and temporal distribution of wind resources over Korea based on hourly observational data recorded over a period of 5 years from 457 stations belonging to Korea Meteorological Administration (KMA). The surface and 850 hPa wind data obtained from the Korea Local Analysis and Prediction System (KLAPS) and the Regional Data Assimilation and Prediction System (RDAPS) over a period of 1 year are used as supplementary data sources. Wind speed is generally high over seashores, mountains, and islands. In 62 (13.5%) stations, mean wind speeds for 5 years are greater than $3ms^{-1}$. The effects of seasonal wind, land-sea breeze, and mountain-valley winds on wind resources over Korea are evaluated as follows: First, wind is weak during summer, particularly over the Sobaek Mountains. However, over the coastal region of the Gyeongnam-province, strong southwesterly winds are observed during summer owing to monsoon currents. Second, the wind speed decreases during night-time, particularly over the west coast, where the direction of the land breeze is opposite to that of the large-scale westerlies. Third, winds are not always strong over seashores and highly elevated areas. The wind speed is weaker over the seashore of the Gyeonggi-province than over the other seashores. High wind speed has been observed only at 5 stations out of the 22 high-altitude stations. Detailed information on the wind resources conditions at the 21 stations (15 inland stations and 6 island stations) with high wind speed in Korea, such as the mean wind speed, frequency of wind speed available (WSA) for electricity generation, shape and scale parameters of Weibull distribution, constancy of wind direction, and wind power density (WPD), have also been provided. Among total stations in Korea, the best possible wind resources for electricity generation are available at Gosan in Jeju Island (mean wind speed: $7.77ms^{-1}$, WSA: 92.6%, WPD: $683.9Wm^{-2}$) and at Mt. Gudeok in Busan (mean wind speed: $5.66ms^{-1}$, WSA: 91.0%, WPD: $215.7Wm^{-2}$).

• 한국환경과학회지
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• 제9권6호
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• pp.475-482
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• 2000

The purpose of this study is to find out the temporal and spatial characteristics of the diurnal wind variation between coastal and inland areas using the hourly wind data of 58 AWS-stations in the South Korea which are collected during the 10 years from 1980. Diurnal variation is investigated by using the Fast Fourier Transform(FFT), and the wind direction in investigated by comparing C(sub)r with C(sub)v represented the constancy of wind. For the scalar wind speed, the maximum wind speed occurs in the daytime 14h to 16h. The maximum diurnal amplitude at coastal areas occurs from 12h to 16h, and is about 2 hours faster than that at inland areas. Vector mean wind speed is strong at coastal areas and Chupungnyong, Kumi, Taegu of inland areas. The diurnal variation ellipses make a right angle with coastline show that the land and sea breezes are prevailing. The constancy of wind is strong at all observations in January. In the relationship between $C_r and C_v, C_v is higher than C_r$.

• Wind and Structures
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• 제15권1호
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• pp.1-15
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• 2012

High-resolution wind data were acquired from a 100-m high offshore tower during the passage of Typhoon Hagupit in September, 2008. The meteorological tower was equipped with an ultrasonic anemometer and a number of cup anemometers at heights between 10 and 100 m. Wind characteristics of the strong typhoon, such as mean wind speed and wind direction, turbulence intensity, turbulence integral length scale, gust factor and power spectra of wind velocity, vertical profiles of mean wind speed were investigated in detail based on the wind data recorded during the strong typhoon. The measured results revealed that the wind characteristics in different stages during the typhoon varied remarkably. Through comparison with non-typhoon wind measurements, the phenomena of enhanced levels of turbulence intensity, gust factors, turbulence integral length scale and spectral magnitudes in typhoon boundary layer were observed. The monitored data and analysis results are expected to be useful for the wind-resistant design of offshore structures and buildings on seashores in typhoon-prone regions.

• 한국방재학회 논문집
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• 제9권4호
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• pp.21-28
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• 2009

국내 조선소는 빈번하게 태풍에 의해 영향을 받는 해안에 위치하며, 풍하중에 취약한 많은 경량 구조의 시설물들로 이루어져 있다. 본 연구에서는 주변 지형과 조선소내부 건물의 영향까지 고려하여 시설물의 강풍에 대한 위험 분석을 수행하였다. 몬테카를로 시뮬레이션에 의해 대상 지역의 극한 풍속을 추정하여 전산유체역학 해석을 위한 입사풍속으로 설정하였으며, 난류 유동을 고려한 전산 유체 해석을 이용하여 시설물 표면에 발생하는 풍압과 조선소 사업장 내의 풍속 분포를 추정하였다. 결과로서 일부 시설물에는 설계 하중보다 높은 풍하중이 작용하여 보강이 요구되는 것으로 판단되며, 향후 설계 풍하중을 고려하는 경우 주변의 국부적 지형 변화와 건물 배치를 고려해야 할 것으로 나타났다.

• 대기
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• 제25권4호
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• pp.659-667
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• 2015

In this study, sensitivity of inflow wind speed and turbulent Schmidt number to pollutant dispersion in an urban street canyon is investigated, by comparing CFD-simulated results to wind-tunnel results. For this, we changed systematically inflow wind speed at the street-canyon height ($1.5{\sim}10.0m\;s^{-1}$ with the increment of $0.5m\;s^{-1}$) and turbulent Schmidt number (0.2~1.3 with interval of 0.1). Also, we performed numerical experiments under the conditions that turbulent Schmidt numbers selected with the magnitude of mean kinetic energy at each grid point were assigned in the street canyon. With the increase of the inflow wind speed, the model underestimated (overestimated) pollutant concentration in the upwind (downwind) side of the street canyon because of the increase of pollutant advection. This implies that, for more realistic reproduction of pollutant dispersion in urban street canyons, large (small) turbulent Schmidt number should be assigned for week (strong) inflow condition. In the cases of selectively assigned turbulent Schmidt number, mean bias remarkably decreased (maximum 60%) compared to the cases of constant turbulent Schmidt number assigned. At week (strong) inflow wind speed, root mean square error decreases as the area where turbulent Schmidt number is selectively assigned becomes large (small).

• 한국철도학회논문집
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• 제8권1호
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• pp.6-14
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• 2005

The mechanism of ballast-flying phenomena by strong wind induced by high-speed trains has extensively been investigated by conducting wind tunnel test and field-measuring of wind velocity in the vicinity of the track. The ballast gathered from the Seoul-Busan high-speed railway track has been classified by mass and shape to find relationship between those properties and the characteristic of movement in high wind and 16-channel Kiel-probe array has been used to examine the detailed flow structure above the surface of the track. The probability of ballast-flying during the passage of the high-speed train has been assessed comparing the results from wind tunnel test and that from field-measuring. The results shows that when the G7 train runs well as the KTX train runs at 300km/h, about 25m/s wind gust is induced just above the tie and the probability far small ballast under 50g to fly is about 50％ when it is on the tie. If the G7 train runs at 350km/h, the wind gust just above the tie increases to 30m/s, therefore radical countermeasure seems to be needed.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2003년도 추계학술발표회
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• pp.163-166
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• 2003

The seasonal mean wind direction and wind speed in a greater coasting area are investigated using the ECMWF(European Centre for Medium-Range Weather Forecasts) data for 11 years from 1985 to 1995. In winter, the main wind direction in Korea and vicinity, Taiwan and vicinity, and the North Pacific Ocean of middle latitudes is a northwesterly wind, northeasterly wind, and westerly wind respectively. The wind speed is strongest in the East China Sea, the South China Sea, and the North Pacific Ocean of low latitudes(Beaufort wind scale 5-6). A distribution pattern of wind direction in spring and fall is similar to that in winter. Seasonal mean wind speed is strongest in winter and the next is fall. The wind speed in summer is generally weak. However, that in the Indochina and vicinity is strong by the influence of Asian monsoon.

• 대기
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• 제26권4호
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• pp.617-633
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• 2016

Jangbogo station is located in Terra Nova Bay over the East Antarctica, which is often affected by individual storms moving along nearby storm tracks and a katabatic flow from the continental interior towards the coast. A numerical simulation for two strong wind events of maximum instantaneous wind speed ($41.17m\;s^{-1}$) and daily mean wind speed ($23.92m\;s^{-1}$) at Jangbogo station are conducted using the polar-optimized version of Weather Research and Forecasting model (Polar WRF). Verifying model results from 3 km grid resolution simulation against AWS observation at Jangbogo station, the case of maximum instantaneous wind speed is relatively simulated well with high skill in wind with a bias of $-3.3m\;s^{-1}$ and standard deviation of $5.4m\;s^{-1}$. The case of maximum daily mean wind speed showed comparatively lower accuracy for the simulation of wind speed with a bias of -7.0 m/s and standard deviation of $8.6m\;s^{-1}$. From the analysis, it is revealed that the each case has different origins for strong wind. The highest maximum instantaneous wind case is caused by the approach of the strong synoptic low pressure system moving toward Terra Nova Bay from North and the other daily wind maximum speed case is mainly caused by the katabatic flow from the interiors of Terra Nova Bay towards the coast. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation and investigation of high wind events at Jangbogo station. However, additional efforts in utilizing the high resolution terrain is required to reduce the simulation error of high wind mainly caused by katabatic flow, which is received a lot of influence of the surrounding terrain.

• 신재생에너지
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• 제4권4호
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• pp.30-36
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• 2008

The possibility of whether the induced wind from a vehicle traveling on highway can be used in wind power generation has been verified through computational flow analysis. The bus which is presumed to accompany relatively strong and wide range of induced wind compared to passenger vehicles because of its wide frontal area has been set as the subject of research. In order to ensure the reliability of research, the flow analysis surrounding the bus on a flat road where median strip is not installed has been compared with a preceding research while the validity of grid system and interpretation method used in this research have been assured by a qualitative method. In case of the median strip type wind power generator system, because it has been verified that a strong streamwise wind speed (5 m/s) is derived from the contraction effect of flow passage between the bus and the median strip while maintaining a relatively consistent upwind wind speed (1.4 m/s) in vertical direction in the wake area after the bus passes by although the change of wind speed is intense, it was decided as having some possibility of wind power generation. In case of the traffic sign panel type wind power generator system installed at the upper top of highway, because the wind speed of 2 m/s level has been derived for a limited time only at a section equal to the length of the bus and a faint induced wind speed less than 0.5 m/s was shown at other regions, it was decided as having almost no possibility of wind power generation.

• 한국환경과학회지
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• 제19권10호
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• pp.1229-1235
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• 2010

Three meteor-statistical forecasting models - the transfer function model, the time-series autoregressive model and the neural networks model - were tested to develop a daily forecasting model for Jejudo, where the need and demand for wind power forecasting has increased. All the meteorological observation sites in Jejudo have been classified into 6 groups using a cluster analysis. Four pairs of observation sites among them, all having strong wind speed correlation within the same meteorological group, were chosen for a model test. In the development of the wind speed forecasting model for Jejudo, it was confirmed that not only the use a wind dataset at the objective site itself, but the introduction of another wind dataset at the nearest site having a strong wind speed correlation within the same group, would enhance the goodness to fit of the forecasting. A transfer function model and a neural network model were also confirmed to offer reliable predictions, with the similar goodness to fit level.