• Journal of Astronomy and Space Sciences
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• v.34 no.2
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• pp.105-110
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• 2017

Solar wind density depletions are phenomena that solar wind density is rapidly decreased and keep the state. They are generally believed to be caused by the interplanetary (IP) shocks. However, there are other cases that are hardly associated with IP shocks. We set up a hypothesis for this phenomenon and analyze this study. We have collected the solar wind parameters such as density, speed and interplanetary magnetic field (IMF) data related to the solar wind density depletion events during the period from 1996 to 2013 that are obtained with the advanced composition explorer (ACE) and the Wind satellite. We also calculate two pressures (magnetic, dynamic) and analyze the relation with density depletion. As a result, we found total 53 events and the most these phenomena's sources caused by IP shock are interplanetary coronal mass ejection (ICME). We also found that solar wind density depletions are scarcely related with IP shock's parameters. The solar wind density is correlated with solar wind dynamic pressure within density depletion. However, the solar wind density has an little anti-correlation with IMF strength during all events of solar wind density depletion, regardless of the presence of IP shocks. Additionally, In 47 events of IP shocks, we find 6 events that show a feature of blast wave. The quantities of IP shocks are weaker than blast wave from the Sun, they are declined in a short time after increasing rapidly. We thus argue that IMF strength or dynamic pressure are an important factor in understanding the nature of solar wind density depletion. Since IMF strength and solar wind speed varies with solar cycle, we will also investigate the characteristics of solar wind density depletion events in different phases of solar cycle as an additional clue to their physical nature.

• 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.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1338-1341
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• 2002

The Weibull probability density function and the Rayleigh function are compared by analyzing the relations of the capacity factors which are compared the actual wind speed frequency curve with which are modelled using the probability density functions with different mean wind speeds. For this analysis, the wind speed means of arithmetic, root mean square, cubic mean cuberoot, and standard deviations are computed from the measured wind speed data of a specific site and the coefficients of probability density functions are calculated. The capacity factors for Vestas 850[kW] wind turbine are calculated and analyzed. The results shows that the wind speed frequency curve by Rayleigh function is more close to the actual curve than by Weibull function. The more the wind speed frequency curve is close to the actual one, the more the capacity factors become large values.

• Wind and Structures
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• v.16 no.6
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• pp.603-616
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• 2013

This study is aimed at formulating an empirical equation for the across-wind fluctuating moment and spectral density coefficient, which are needed to estimate the across-wind dynamic responses of tall buildings, as a function of the side ratios of buildings. In order to estimate an empirical formula, wind tunnel tests were conducted on aero-elastic models of the rectangular prisms with various aspect and side ratios in turbulent boundary layer flows. In this paper, criteria for the across-wind fluctuating moment and spectral density are briefly discussed and the results are analyzed mainly as a function of the side ratios of the buildings. Finally, empirical formulas for the across-wind fluctuating moment coefficient and spectral density coefficient according to variation of the aspect ratio are proposed.

• KIEAE Journal
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• v.12 no.1
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• pp.127-132
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• 2012

The energy consumption in the world is growing rapidly. And the environmental issues of climate become a important task. The interest in renewable energy like wind and solar is increasing now. Especially, by reducing power transmission loss, a small wind power is getting attention at the residential areas and campus of university. In this study, we attempted to estimate and compare the wind energy density using wind data of AWS (Automatic Weather Station) of H University. In this case of a campus, the weibull distribution parameter C is 2.27, and K is 0.88. According to the data, the energy density of the small wind power is 12.7 W/m2. We did CFD(Computational Fluid Dynamics) simulations at H University campus by 7 wind directions(ENE, ESE, SE, NW, WNW, W, WSW). In the results, we suggest 4 small wind powers. The small wind power generating system can produce 4,514kWh annually.

• Wind and Structures
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• v.2 no.2
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• pp.105-117
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• 1999

The various spectral density functions of wind are applied in the wind process simulation by the spectral representation method. In view of the spectral density functions, the characteristics of the simulated processes are compared. The ensemble spectral density functions constructed from the simulated sample processes are revealed to have the similarity not only in global shape but also in the maximum values with the target spectral density functions with a high accuracy. For the correlation structure to be satisfied in the circumferential direction on the cooling tower shell, a new formula is suggested based on the mathematical expression representing the circumferential distribution of the wind pressure on the cooling tower shell. The simulated wind processes are applied in the dynamic analysis of cooling tower shell in the time domain and the fluctuating stochastic behavior of the cooling tower shell is investigated.

• Journal of the Korean earth science society
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• v.31 no.3
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• pp.225-233
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• 2010

Wind power density distribution over the North Korea territory was investigated by using 30-year wind observations at 27 meteorological stations. The mean annual wind power density over North Korea turned out to be 58.6W/$m^2$, which corresponds to the wind power class of 1. The wind power density shows a seasonal variation, having the highest density in spring and the lowest in summer. In particular, the wind power density in summer is about a half of that in spring. The diurnal variation of the wind power density shows that the highest and lowest densities occur in the afternoon and between 3 and 6 am in local time, respectively. The most potential wind energy generation regions are the Gaema Plateau in the central region, the northeast part of Hamgyeongbuk-do, the south coast of Pyongan-do and the west coast of Hwanghae-do. The mean annual wind power density in Changjin is 151.2W/$m^2$, which is equivalent to the class of 3. In Ryongyon, the annual mean wind power density is 102.4W/$m^2$, which belongs to the class of 2.

• Wind and Structures
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• v.10 no.1
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• pp.45-60
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• 2007

Transmission tower is a vital component in electrical system. In order to accurately compute the dynamic response and reliability of transmission tower under the excitation of wind loading, a new method termed as probability density evolution method (PDEM) is introduced in the paper. The PDEM had been proved to be of high accuracy and efficiency in most kinds of stochastic structural analysis. Consequently, it is very hopeful for the above needs to apply the PDEM in dynamic response of wind-excited transmission towers. Meanwhile, this paper explores the wind stochastic field from stochastic Fourier spectrum. Based on this new viewpoint, the basic random parameters of the wind stochastic field, the roughness length $z_0$ and the mean wind velocity at 10 m heigh $U_{10}$, as well as their probability density functions, are investigated. A latticed steel transmission tower subject to wind loading is studied in detail. It is shown that not only the statistic quantities of the dynamic response, but also the instantaneous PDF of the response and the time varying reliability can be worked out by the proposed method. The results demonstrate that the PDEM is feasible and efficient in the dynamic response and reliability analysis of wind-excited transmission towers.

• Journal of Environmental Science International
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• v.18 no.8
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• pp.885-897
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• 2009

In order to make sure the impact of spatial resolution of wind energy map on the estimation of wind power density in the Korean Peninsula, the comparison studies on the characteristics of wind energy map with three different spatial resolutions were carried out. Numerical model used in the establishment of wind map is MM5 (5th generation Mesoscale Model) with RBAPS (Regional Data Assimilation and Prediction System) as initial and boundary data. Analyzed Period are four months (March, August, October, and December), which are representative of four seasons. Since high spatial resolution of wind map make the undulation of topography be clear, wind pattern in high resolution wind map is correspond well with topography pattern and maximum value of wind speed is also increase. Indication of island and mountains in wind energy map depends on the its spatial resolution, so wind patterns in Heuksan island and Jiri mountains are clearly different in high and low resolutions. And area averaged power density can be changed by estimation method of wind speed for unit area in the numerical model and by treatment of air density. Therefore the studiable resolution for the topography should be evaluated and set before the estimation of wind resources in the Korean Peninsula.

• Journal of Environmental Science International
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• v.11 no.1
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• pp.41-56
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• 2002

In order to estimate the quantitative roles of the tide induced residual currents, density currents and wind driven currents on the residual currents in Kwangynag Bay Korea, numerical experiments with a diagnostic multi-level model were carried out. Density currents were calculated from the temperature and salinity data observed in January, May, August and November 1998. Anti-clockwise circulations are formed at the western inner part of the bay, the location from the east of Myodo Is. to the south of POSCO Co. and the place between Yeosu peninsula and Namhae Is. from the calculation results of the tide induced residual currents. Velocities of the density currents are less than 3cm/s at the western inner part of the bay and about 5cm/s at the southern entrance of the bay. Density currents get strong in summer and weak in autumn. Wind driven currents at the surface layer flow in the directions of the given winds which are the daily mean winds when the temperature and salinity observations are carried out. In the middle and lower layers, however the wind driven currents flow in the opposite direction to the surface currents as supplementary currents. The surface wind driven currents are greater than the tide induced residual currents or the density currents. The calculated residual currents including the tide induced residual currents, density currents and wind driven currents agree with the results of the current observations approximately. In the Bay, the wind driven currents affect on the residual currents greatestly and tide induced residual currents and density currents do in the second place and the third place.