• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.845-857
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• 2020

The precise estimation of accelerated soil wind erosion that can cause severe economic and environmental impacts still has not been achieved to date. The objectives of this investigation were to verify the applicability of a Wind Erosion Prediction System (WEPS) that expressed the soil loss as mass per area for specific areas of interest on a daily basis for a single event in arable lands. To this end, we selected and evaluated the results published by Hagen in 2004 and the soil depth converted from the mass of soil losses obtained by using the WEPS. Hagen's results obtained from the WEPS model followed the 1 : 1 line between predicted and measured value for soil losses with only less than 2 kg·m-2 whereas the values between the measured and predicted loss did not show any correlation for the given field conditions due to the initial field surface condition although the model provided reasonable estimates of soil loss. Calculated soil depths of the soil loss by wind for both the observed and predicted ones ranged from 0.004 to 3.113 cm·10 a-1 and from 0 to 2.013 cm·10 a-1, respectively. Comparison of the soil depths between the observed and predicted ones did not show any good relationship, and there was no soil loss in the predicted one while slight soil loss was measured in the observed one. Therefore, varying the essential model inputs and factors related to wind speed and soil properties are needed to accurately estimate soil loss for a given field in arable land.

• Journal of Environmental Science International
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• v.18 no.8
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• pp.927-932
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• 2009

Wind turbine noise become main environmental problem as wind energy have been installed all around. Noise from large wind turbine give annoyance to listener, moreover it increase loading to whole system by restricting blade tip speed. However accurate noise mechanism of wind turbine is not yet examined. This paper reviewed noise source and analysis theory. Broadband noise if main component of wind turbine noise and airfoil self noise is main noise source. These make acoustic analogy hard to apply for analysis. For this reason, experimental equation is method for wind turbine noise prediction up to now. Spectrum analysis shows that vortex shedding noise exists around $1k{\sim}2k$ Hz. This region is most sensitive frequency range to human. Thus it is necessary to reduce this noise source.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.151-164
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• 2002

Predictions of the pedestrian level wind speeds for the downtown area of Auckland that have been obtained by wind tunnel and computational fluid dynamic (CFD) modelling are presented. The wind tunnel method involves the observation of erosion patterns as the wind speed is progressively increased. The computational solutions are mean flow calculations, which were obtained by using the finite volume code PHOENICS and the $k-{\varepsilon}$ turbulence model. The results for a variety of wind directions are compared, and it is observed that while the patterns are similar there are noticeable differences. A possible explanation for these differences arises because the tunnel prediction technique is sensitivity to gust wind speeds while the CFD method predicts mean wind speeds. It is shown that in many cases the computational model indicates high mean wind speeds near the corner of a building while the erosion patterns are consistent with eddies being shed from the edge of the building and swept downstream.

• New & Renewable Energy
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• v.10 no.2
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.327-333
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• 2019

Wind speed data constitute important weather information for aircrafts flying at low altitudes, such as drones. Currently, the accuracy of low altitude wind predictions is much lower than that of high-altitude wind predictions. Deep neural networks are proposed in this study as a method to improve wind speed forecast information. Deep neural networks mimic the learning process of the interactions among neurons in the brain, and it is used in various fields, such as recognition of image, sound, and texts, image and natural language processing, and pattern recognition in time-series. In this study, the deep neural network model is constructed using the wind prediction values generated by the numerical model as an input to improve the wind speed forecasts. Using the ground wind speed forecast data collected at the Boseong Meteorological Observation Tower, wind speed forecast values obtained by the numerical model are compared with those obtained by the model proposed in this study for the verification of the validity and compatibility of the proposed model.

• New & Renewable Energy
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• v.8 no.4
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• pp.3-12
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• 2012

Large offshore wind farms have actively been developed in order to meet the needs for wind energy since the land-based wind farms have almost been fully developed especially in Europe. The key problem for the construction of offshore wind farms may be on the high cost of energy compared to land-based ones. NREL (National Renewable Energy Laboratory) has developed a spreadsheet-based tool to estimate the cost of wind-generated electricity from both land-based and offshore wind turbines. Component formulas for various kinds and scales of wind turbines were made using available field data. In this paper, this NREL estimation model is introduced and applied to the offshore wind turbines now under designing or in production in Korea, and the result is discussed.

• Journal of Ocean Engineering and Technology
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• v.3 no.2
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• pp.517-517
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• 1989

• Journal of Environmental Science International
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• v.19 no.9
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• pp.1169-1175
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• 2010

A case study for the design of a wind farm in complex terrain was carried out using the wind farm site analysis software OpenWind, which has an open-source platform and is free to use. The Youngdeok Wind Farm, constructed on mountainous terrain in Korea, was chosen as a model site; the design process reproduced using OpenWind. A comparison of the positions of the wind turbine derived from the OpenWind optimization process and the current positions were in good agreement. The annual energy production predicted by OpenWind compared with the prediction by the micrositing software, WindSim, were also validated to within 1%. Therefore, it was confirmed that OpenWind can be used for a practical wind farm design project. It is also anticipating that this paper will provide a prototype process for the design of a wind farm site and offer a database for the post-evaluation of a constructed wind farm in Korea.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.3
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• pp.249-261
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• 2003

A three-dimensional mesoscale atmospheric dispersion modeling system consisting of the Lagrangian particle dispersion model (LPDM) and the meteorological mesoscale model (MM5) was employed to simulate the transport and dispersion of non-reactive pollutant during the nuclear spill event occurred from Sep. 31 to Oct. 3, 1999 in Tokaimura city, Japan. For the comparative analysis of numerical experiment, two more sets of foreign mesoscale modeling system; NCEP (National Centers for Environmental Prediction) and DWD (Deutscher Wetter Dienst) were also applied to address the applicability of air pollution dispersion predictions. We noticed that the simulated results of horizontal wind direction and wind velocity from three meteorological modeling showed remarkably different spatial variations, mainly due to the different horizontal resolutions. How-ever, the dispersion process by LPDM was well characterized by meteorological wind fields, and the time-dependent dilution factors ($\chi$/Q) were found to be qualitatively simulated in accordance with each mesocale meteorogical wind field, suggesting that LPDM has the potential for the use of the real time control at optimization of the urban air pollution provided detailed meteorological wind fields. This paper mainly pertains to the mesoscale modeling approaches, but the results imply that the resolution of meteorological model and the implementation of the relevant scale of air quality model lead to better prediction capabilities in local or urban scale air pollution modeling.

• Wind and Structures
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• v.18 no.6
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• pp.669-691
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• 2014

Since low-rise residential buildings are the most common and vulnerable structures in coastal areas, a reliable prediction of their performance under hurricanes is necessary. The present study focuses on developing a refined finite element model that is able to more rigorously represent the load distributions or redistributions when the building behaves as a unit or any portion is overloaded. A typical 5:12 sloped low-rise residential building is chosen as the prototype and analyzed under wind pressures measured in the wind tunnel. The structural connections, including the frame-to-frame connections and sheathing-to-frame connections, are modeled extensively to represent the critical structural details that secure the load paths for the entire building system as well as the boundary conditions provided to the building envelope. The nail withdrawal, the excessive displacement of sheathing, the nail head pull-through, the sheathing in-plane shear, and the nail load-slip are found to be responsible for the building envelope damage. The uses of the nail type with a high withdrawal capacity, a thicker sheathing panel, and an optimized nail edge distance are observed to efficiently enhance the building envelope performance based on the present numerical damage predictions.