• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.5
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• pp.514-520
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• 2015

The effects of suspension stiffness on the reaction load of the gearbox suspension for a three-point suspension wind turbine drive train were investigated by finite element analysis. The reaction forces of the gearbox suspension appear to increase as the gearbox suspension stiffness increases; however, the main bearing stiffness has a reverse effect on the reaction forces. The influence of the gearbox suspension stiffness is greater than that of the main bearing. Since the suspensions must provide the gearbox with proper support, it is not practical to use soft gearbox suspension for small reaction forces. It is more feasible to use stiff main bearings. As a guideline for the main bearing stiffness in the present study, we propose a relative stiffness of 100-150% of the reference.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.65-68
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• 2003

This study is intended to look into the influence of environment and construction factor on bleeding of concrete. According to the results, as wind is light, relative humidity is high and temperature is low, the amount of bleeding increases greatly, and evaporation speed is influenced greatly by order of wind, temperature and humidity. As the properties of bleeding by construction factor, the amount of bleeding increases with an increase of placing thickness, but the bleeding ratio, the amount of bleeding per unit volume, increases with a decrease of the placing thickness. Bleeding speed is fastest at about 90 minute after placing concrete. Also, as wind is light, relative humidity is high, temperature is low and the placing thickness is thick, bleeding speed grow faster.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.127-133
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• 2013

The purpose of this study was to investigate maximum and minimum grain size which eroded by wind according to soil and wind conditions, such as top soil water content, roughness, land slope, wind velocity and proportion of grain size under 0.84mm. For performing this study, portable wind erosion tunnel was designed and utilized during field test, which facilitated measuring actual wind erosions under artificially controlled wind conditions. In the result, maximum, minimum grain size had strong negative correlation with roughness while weak positive correlation with wind velocity. Also, Slope which means the effect of gravity also influence grain size erodible by winds. Based on these results, regression equations were suggested for predicting maximum and minimum grain sizes by using multiple linear regression analysis from SPSS 20.0. The equation for maximum grain size erodible by winds showed a good agreement with the observed data with $R^2$=0.896. Other equation for minimum grain size had $R^2$=0.777.

• Journal of Korean Society for Atmospheric Environment
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• v.7 no.2
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• pp.105-113
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• 1991

An investigation is carried out for the role of topography in governign the mesoscale distribution of $SO_2$ concentration in Seoul. The three dimensional wind fields computed for a given synoptic meteorological condition by an atmospheric mesoscale model in the terrain following coordinate have been employed to compute the three dimensional mesoscale distributions of $SO_2$ concentration by the diffusion model in Seoul area. Terrain may affect the mesoscale distributions of $SO_2$ concentration through its influence on the mesoscale wind fields. This study discusses only the terrain effect on the concentration through its modification of the wind. This effect is to produce higher concentration in lower area according to the structure of divergence fields derived from and atmospheric mesoscale model.

• Journal of environmental and Sanitary engineering
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• v.24 no.3
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• pp.37-54
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• 2009

The study has analyzed impacts and intensity of weather that affect $PM_{10}$ concentration based on PM10 forecast conducted by the city of Seoul in order to identify ways to improve the accuracy of PM10 forecast. Variables that influence $PM_{10}$ concentration include not only velocity and direction of the wind and rainfalls, but also those including secondary particulate matter, which were identified to greatly influence the concentration in complicated manner as well. In addition, same variables were found to have different impacts depending on seasons and conditions of other variables. The study found out that improving accuracy of $PM_{10}$ concentration forecast face some limits as it is greatly influenced by the weather. As an estimation, this study assumed that basic research units and artificially estimated pollutant emissions, study on mechanisms of secondary particulate matter productions, observatory compliment, and enhanced forecaster's expertise are needed for better forecast.

• Wind and Structures
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• v.19 no.6
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• pp.649-663
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• 2014

The present paper discusses the characteristics of unsteady aerodynamic forces on long-span curved roofs. A forced vibration test is carried out in a wind tunnel to investigate the effects of wind speed, vibration amplitude, reduced frequency of vibration and rise/span ratio of the roof on the unsteady aerodynamic forces. Because the range of parameters tested in the wind tunnel experiment is limited, a CFD simulation is also made for evaluating the characteristics of unsteady aerodynamic forces on the vibrating roof over a wider range of parameters. Special attention is paid to the effect of reduced frequency of vibration. Based on the results of the wind tunnel experiment and CFD simulation, the influence of the unsteady aerodynamic forces on the dynamic response of a full-scale long-span curved roof is investigated on the basis of the spectral analysis.

• Wind and Structures
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• v.36 no.6
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• pp.367-377
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• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

• Wind and Structures
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• v.4 no.6
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• pp.481-494
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• 2001

Wind tunnel pressure tests were conducted on a 1:100 scale model of a large industrial building with solar panels mounted parallel to the flat roof. The model form was chosen to have the same aspect ratio as the Texas Tech University test building. Pressures were simultaneously measured on the roof, and on the topside and underside of the solar panel, the latter two combining to produce a nett panel pressure. For the configurations tested, varying both the lateral spacing between the panels and the height of the panels above the roof surface had little influence on the measured pressures, except at the leading edge. The orientation of the panels with respect to the wind flow and the proximity of the panels to the leading edge had a greater effect on the measured pressure distributions. The pressure coefficients are compared against the results for the roof with no panels attached. The model results with no panels attached agreed well with full-scale results from the Texas Tech test building.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.847-852
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• 2004

The wind turbine blade is the equipment converted wind into electric energy. The effect of the blade has influence of the output power and efficiency of wind turbine. The design of blade is considered of lift-to-drag ratio. structure. a condition of process of manufacture and stable maximum lift coefficient, etc. This study is used the simplified method for design of the aerodynamic blade and aerodynamic analysis used blade element method This Process is programed by delphi-language. The Program has any input values such as tip speed ratio blade length. hub length. a section of shape and max lift-to-drag ratio. The Program displays chord length and twist angle by input value and analyzes performance of the blade.