• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.130-139
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• 2017

The crop damage caused by strong wind was predicted using the wind speed data available from Korean Meteorological Administration (KMA). Wind speed data measured at 19 automatic weather stations in 2012 were compared with wind data available from the KMA's digital forecast. Linear regression equations were derived using the maximum value of wind speed measurements for the three-hour period prior to a given hour and the digital forecasts at the three-hour interval. Estimates of daily maximum wind speed were obtained from the regression equation finding the greatest value among the maximum wind speed at the three-hour interval. The estimation error for the daily maximum wind speed was expressed using normal distribution and Weibull distribution probability density function. The daily maximum wind speed was compared with the critical wind speed that could cause crop damage to determine the level of stages for wind damage, e.g., "watch" or "warning." Spatial interpolation of the regression coefficient for the maximum wind speed, the standard deviation of the estimation error at the automated weather stations, the parameters of Weibull distribution was performed. These interpolated values at the four synoptic weather stations including Suncheon, Namwon, Imsil, and Jangsu were used to estimate the daily maximum wind speed in 2012. The wind damage risk was determined using the critical wind speed of 10m/s under the assumption that the fruit of a pear variety Mansamgil would begin to drop at 10 m/s. The results indicated that the Weibull distribution was more effective than the normal distribution for the estimation error probability distribution for assessing wind damage risk.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.213-225
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• 2018

In order to access the accuracy of the gridded daily Advanced Scatterometer (hereafter DASCAT) ocean surface wind data in the surrounding of Korea, the DASCAT was compared with the wind data from buoys. In addition, the reanalysis data for wind at 10 m provided by European Centre for Medium-Range Weather Forecasts (ECMWF, hereafter ECMWF), National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR, hereafter NCEP), Modern Era Retrospective-analysis for Research and Applications-2 (MERRA-2, hereafter MERRA) were compared and analyzed. As a result, the RMSE of DASCAT for the actual wind speed is about 3 m/s. The zonal components of wind of buoys and the DASCAT have strong correlation more than 0.8 and the meridional components of wind them have lower correlation than that of zonal wind and are the lowest in the Yellow Sea (r=0.7). When the actual wind speed is below 10 m/s, the EMCWF has the highest accuracy, followed by DASCAT, MERRA, and NCEP. However, under the wind speed more than 10 m/s, DASCAT shows the highest accuracy. In the nature of error according to the wind direction, when the zonal wind is strong, all dataset has the error of more than $70^{\circ}$ on the average. On the other hand, the RMSE of wind direction was recorded $50^{\circ}$ under the strong meridional winds. ECMWF shows the highest accuracy in these results. The RMSE of the wind speed according to the wind direction varied depending on the actual wind direction. Especially, MERRA has the highest RMSE under the westerly and southerly wind condition, while the NCEP has the highest RMSE under the easterly and northerly wind condition.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.2
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• pp.596-603
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• 1991

Fatigue life prediction of pressure vessel is studied analytically using cumulative damage models and linear elastic fracture mechanics method. The stresses are analyzed by finite element method. During operation, the maximum stress occurs at the outside of neck region while fatigue analysis indicates that the bottom of nozzle part has the shortest fatigue life. Previously proposed fatigue life prediction equation and cumulative damage model are modified successfully by introducing reference fatigue modulus. It is found that the modified life prediction equation and damage model are useful for lower stress level application.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.547-554
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• 2018

Wind energy is widely recognized as one of the cheapest forms of clean and renewable energy. In fact, in several countries, wind energy has achieved cost parity with fossil fuel-based sources of electricity generation for new electricity generation plants. Offshore wind energy development promises to be a significant domestic renewable energy source for the target of korea government 3020 plan. A pivotal activity during the development phase of a wind project is wind resource assessment. Several approaches can be categorized as three basic scales or stages of wind resource assessment: preliminary area identification, area wind resource evaluation, and micrositing. This study is to estimate the wind power capacity of chonnam province offshore area using three basic stages based on the six meteorological mast data. WindPRO was used, one of a well-known wind energy prediction programs and based on more than 25 years of experiences in development of software tools for wind energy project development. The design results of offshore wind power generation capacity is calculated as total 2.52GW with six wind farms in chonnam offshore area.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.597-604
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• 2019

Artificial neural networks are algorithms that simulate learning through interaction and experience in neurons in the brain and that are a method that can be used to produce accurate results through learning that reflects the characteristics of data. In this study, a model using deep neural network was presented to improve the predicted wind speed values in the meteorological dynamic model. The wind speed prediction improvement model using the deep neural network presented in the study constructed a model to recalibrate the predicted values of the meteorological dynamics model and carried out the verification and testing process and Separate data confirm that the accuracy of the predictions can be increased. In order to improve the prediction of wind speed, an in-depth neural network was established using the predicted values of general weather data such as time, temperature, air pressure, humidity, atmospheric conditions, and wind speed. Some of the data in the entire data were divided into data for checking the adequacy of the model, and the separate accuracy was checked rather than being used for model building and learning to confirm the suitability of the methods presented in the study.

• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.561-568
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• 2006

CFD simulation for one of tilt-rotor UAV configurations, TR-E2S1, was performed to investigate its aerodynamic characteristics. Control surfaces such as elevator and rudder were deflected and wing incidence angle was changed. Also aerodynamic stabilities were analyzed with the variation of pitch and yaw angles. The comparison of CFD with wind tunnel test results reveals the same trends in the aerodynamic characteristics and stabilities. However 12% scale wind tunnel test model is too small for accurate data collection and should build a high fidelity model for quantitative data comparison.

• Aerospace Engineering and Technology
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• v.7 no.2
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• pp.27-30
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• 2008

Wall correction method for wind tunnel test is reviewed and applied to the numerical experimental results obtained at the wind tunnel condition. The corrected lift coefficient agrees well with the reference data generated from the grid having very far boundary However the corrected drag coefficient presents some deviation from the reference data.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.135-139
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• 1999

Wind velocity is one of the primary variables for describing atmospheric state from GMS-5. And its accurate depiction is essential for operational weather forecasting and for initialization of NWP(Numerical Weather Prediction) models. The aim of this research is to incorporate imagery from other available spectral channels and examine the error characteristics of winds derived from these images. Multi spectral imagery from GMS-5 was used for this purpose and applied to Korean region with together BoM(Bureau of Meteorology). The derivation of wind velocity estimates from low and high resolution visible, split window infrared, and water vapor images, resulted in improvements in the amount and quality of wind data available for forecasting.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.1
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• pp.13-23
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• 2003

A local wind model and a three dimensional local environmental model including advection, diffusion, deposition. and photochemical reactions were performed at Gwangyang Bay, Korea, to predict air flow and air pollutants concentrations. A large grid was used, and nesting method was employed for small grid calculation. From the meterological module simulation, we were able to reproduce local wind characteristics such as sea/land winds and mountain/valley winds simulation at Gwangyang Bay. In addition, the concentration module showed high concentration regions at Yosu industrial complex, Gwangyang steel company. and Container anchor. It was also seen that air pollutants were dispersed by sea/land winds. A comparison between the measurement and the prediction of sulfur dioxide and nitric oxide, which are relatively low-reacted pollutants, was performed. However, the measured nitrogen dioxide and ozone concentrations were higher than the simulated ones. Particularly, ozone concentration between 8 a..m. and 8 p.m. agreed well, but the measured ozone during the rest of time were generally higher.

• Wind and Structures
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• v.19 no.6
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• pp.603-621
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• 2014

Past high speed wind events have exposed the vulnerability of the roof systems of existing light-framed wood structures to uplift loading, contributing greatly to economic and human loss. This paper further investigates the behaviour of light-framed wood structures under the uplift loading of a realistic pressure distribution. A three-dimensional finite-element model is first developed to capture the behaviour of a recently completed full-scale experiment. After describing the components used to develop the numerical model, a comparison between the numerical prediction and experimental results in terms of the deflected shape at the roof-to-wall connections is presented to gain confidence in the numerical model. The model is then used to analyze the behaviour of the truss system under realistic and equivalent uniform pressure distributions and to perform an assessment of the use of the tributary area method to calculate the withdrawal force acting on the roof-to-wall connections.