• Wind and Structures
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• v.28 no.6
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• pp.381-388
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• 2019

This paper described the application of Geospatial Analysis in determining mean wind speed, $V_h$ for wind load calculation imposed to electrical transmission tower structural design. The basic wind speed data on available station obtained from Malaysian Meteorology Department is adjusted by considering terrain and ground roughness factor. The correlation between basic wind speed, terrain factor and ground roughness stated in EN-50341-1 is used to obtain the $V_h$ for overhead transmission line elements 50 m above ground. Terrain factor, $k_r$ and ground roughness, $z_0$ in this study are presented by land use types of study area. Wind load is then calculated by using equation stated in design code EN-50341-1 by using the adjusted mean wind speed. Scatter plots of $V_h$ for different $k_r$and $z_0$ are presented in this paper to see the effect of these parameters to the value of $V_h$. Geospatial analysis is used to represent the model of $V_h$. This model can be used to determine possible area that will subject to wind load which severe to the stability of transmission tower and transmission line.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.29-40
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• 2018

Strength design wind loads for the wind resistance design of structures shall be evaluated by the product of wind loads calculated based on the basic wind speed with 100 years return period and the wind load factor 1.3 specified in the provisions of load combinations in Korean Building Code (KBC) 2016. It may be sure that the wind load factor 1.3 in KBC(2016) had not been determined by probabilistic method or empirical method using meteorological wind speed data in Korea. In this paper, wind load factors were evaluated by probabilistic method and empirical method. The annual maximum 10 minutes mean wind speed data at 69 meteorological stations during past 40 years from 1973 to 2012 were selected for this evaluation. From the comparison of the results of those two method, it can be found that the mean values of wind load factors calculated both probability based method and empirical based method were similar at all meteorological stations. When target level of reliability index is set up 2.5, the mean value of wind load factors for all regions should be presented about 1.35. When target level of reliability index is set up 3.0, wind load factor should be presented about 1.46. By using the relationship between importance factor(conversion factor for return period) and wind load factor, the return periods for strength design were estimated and expected wind speeds of all regions accounting for strength design were proposed. It can be found that return period to estimate wind loads for strength design should be 500 years and 800 years in according to target level of reliability index 2.5 and 3.0, respectively. The 500 years basic wind speed map for strength design was suggested and it can be used with a wind load factor 1.0.

• Journal of the Korean Solar Energy Society
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• v.30 no.2
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• pp.54-64
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• 2010

Interest in new and renewable energies like solar energy and wind energy is increasing throughout the world due to the rapidly expanding energy consumption and environmental reasons. An essential requirement for wind force power generation is estimating the size of wind energy accurately. Wind energy is estimated usually using meteorological data or field measurement. This study attempted to estimate wind energy density using meteorological data on daily mean wind speed and the Weibull parameters in Seoul, a representative inland city where over 60% of 15 story or higher apartments in Korea are situated, and Busan, Incheon, Ulsan and Jeju that are major coastal cities in Korea. According to the results of analysis, the monthly mean probability density distribution based on the daily mean wind speed agreed well with the monthly mean probability density distribution based on the Weibull parameters. This finding suggests that the Weibull parameters, which is highly applicable and convenient, can be utilized to estimate the wind energy density distribution of each area. Another finding was that wind energy density was higher in coastal cities Busan and Incheon than in inland city Seoul.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.29-34
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• 2010

Wind speed and wind direction are usually taken using two parameters: wind speed and wind direction. This paper studies the average wind speed and direction calculation methods. The paper first introduces to basic wind's knowledge, and then presents several methods in calculating average wind speed and direction. Lastly some graphs are plotted base on these computational methods and the implementation of these methods in an actual buoy system.

• Structural Engineering and Mechanics
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• v.6 no.5
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• pp.555-569
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• 1998

The reliability of antenna tower designed for a n-year design wind speed is determined by considering the variability of the strength of the component members and of the mean wind speed. For obtaining the n-year design wind speed, maximum annual wind speed is assumed to follow Gumbel Type-1 distribution. Following this distribution of the wind speed, the mean and standard deviation of stresses in each component member are worked out. The variability of the strength of members is defined by means of the nominal strength and a coefficient of variation. The probability of failure of the critical members of tower is determined by the first order second moment method (FOSM) of reliability analysis. Using the above method, the reliability against allowable stress failure of the critical members as well as the system reliabilities for a 75 m tall antenna tower, designed for n-year design wind speed, are presented.

• Wind and Structures
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• v.15 no.1
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• pp.43-64
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• 2012

Many potential small wind turbine locations are near obstacles such as buildings and shelterbelts, which can have a significant, detrimental effect on the local wind climate. A neural network-based model has been developed which predicts mean wind speed and turbulence intensity at points in an obstacle's region of influence, relative to unsheltered conditions. The neural network was trained using measurements collected in the wakes of 18 scale building models exposed to a simulated rural atmospheric boundary layer in a wind tunnel. The model obstacles covered a range of heights, widths, depths, and roof pitches typical of rural buildings. A field experiment was conducted using three unique full scale obstacles to validate model predictions and wind tunnel measurements. The accuracy of the neural network model varies with the quantity predicted and position in the obstacle wake. In general, predictions of mean velocity deficit in the far wake region are most accurate. The overall estimated mean uncertainties associated with model predictions of normalized mean wind speed and turbulence intensity are 4.9% and 12.8%, respectively.

• Wind and Structures
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• v.31 no.3
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• pp.217-227
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• 2020

Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

• Atmosphere
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• v.25 no.4
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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).

• Journal of Environmental Science International
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• v.10 no.2
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• pp.135-142
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• 2001

In order to investigate horizontal wind field in the boundary layer around Pusan area, wind speed and wind direction measured at 14 AWS(Automatic Weather Station), 1997, was used. The wind direction at PRM(Pusan Regional Meterological Office) was showed that southwest and northeast wind dominated for spring and summer, northeast wind for fall and northwest for winter. Anticline flow was showed at \`Gaekumm\` which is located between Mt. Backyang(641m) and Mt. Yumkwang(503m) and affected on wind field at \`Pusanjin\`. The low wind speed and various wind direction was represented at the basin topography, \`Buckgu\`, \`Jeasong\`, \`Ilkwang\` and \`Kijang\`. The annual mean wind speed at 14 sites, 2.5ms(sup)-1, was lower than that measured at PRMO, 3.9ms(sup)-1. The wind direction analysis showed that the case of same direction in compare with that measured at PRMO is about 54% and case of opposite direction is about 12%. Annual and seasonal mean windrose showed wind direction is affected by not only synoptic weather state but also topography.

• Journal of Environmental Science International
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• v.9 no.6
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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 $C_r and C_v, C_v is higher than C_r$.