• Journal of Korean Society of Steel Construction
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• v.17 no.3 s.76
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• pp.263-270
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• 2005

This paper presents a program for protecting vehicles against side winds on highways. The present study consists of three processes. The first one involves giving a guideline for evaluating driving safety in high winds. The second one involves making a guideline for determining the necessity of wind protection system for a certain road area. A reasonable procedure is suggested based on the probability model of wind data on weather stations and the correction of local topographical conditions. The third one involves design of wind barriers. Both CFD analyses and wind tunnel tests were performed to find the proper type of wind barrier considering vehicle controllability, structural safety, economical efficiency as well as driver's visibility. Performance of the designed wind fences was verified from field tests. The performance of the four different types of wind barrier installed at the elevated bridge were tested and some of the results were provided.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.9-14
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• 2010

The main cause of global warming is carbon dioxide generated from the use of fossil fuels, and active research on the reduction of carbon is in progress to slow down the increasing global warming. Wind turbines generate electricity from kinetic energy of wind and are considered as representative for an energy source that helps to reduce carbon emission. Since the kinetic energy of wind is proportional to the cube of the wind speed, the intensity of wind affects wind farm construction validity the most. Therefore, to organize a wind farm, validity analysis should be conducted first through measurement of the wind resources. To facilitate the approval and permission and reduce installation cost, measuring sensors should be installed at locations below the actual wind turbine hub. Wind conditions change in shape with air density, and air density is most affected by the variable sterrain and surface type. So the magnitude of wind speed depends on the ground altitude. If wind conditions are measured at a location below the wind turbine hub, the wind speed has to be extrapolated to the hub height. This correction of wind speed according to height is done with the Deacon equation used in the statistical analysis of previously observed data. In this study, the optimal Deacon equation parameter was obtained through the analysis of the correction of the wind speed error with the Deacon equation based on the characteristics of terrain.

• Atmosphere
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• v.31 no.1
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• pp.101-112
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• 2021

The long-term trend of surface wind speed in Korea is examined for 31 KMA weather stations from 1985 to 2019. Most stations, except Daegwallyeong, have several times of anemometer height changes from tens of centimeters to several meters. To minimize such height change effect on long-term wind trend, the present study adjusts anemometer height in each station to the standard height of 10 m using the power-law wind profile. This adjustment results in non-negligible trend change. For instance, the increasing surface wind speed at Suwon station, which has six times of anemometer height changes in a range of 0.8 m to 20 m, is weakened up to 67% and becomes statistically insignificant. Likewise, the decreasing trend at Andong station, with three times of anemometer height changes in a range of 10 m to 15.5 m, is weakened up to 66%. A similar weakening in long-term trend is observed in most stations regardless of positive and negative trends. However, due to the cancellation between weakened negative trends and weakened positive trends, the station-averaged wind speed trend in Korea does not change much. This result suggests that anemometer height adjustment is crucial for evaluating local wind speed trend but its impact on nation-wide wind speed trend is rather minor.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.65-71
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• 2013

Wind shear means the variation of wind speed according to the height. Wind shear is the important factor affecting the energy production of wind turbines. Power Law is used to extrapolate wind speed data. Normally, a Power Law exponent of 0.143 is used and this is referred to as the 1/7th Power Law. The Power Law exponent is affected by atmospheric stability and surface roughness of the site. Thus, it is necessary to calculate the Power Law exponent of the site exactly for an accurate estimation of wind energy. In this study, wind resources were measured at the three Met-masts which were located in the coastal area of northeastern Jeju Island. The Power Law exponents of the sites were calculated and proposed using measured data. They were 0.141 at Handong, 0.138 at Pyeongdae, and 0.1254 at Udo. We compared annual energy productions which are calculated using a Power Law exponent of 0.143, the proposed value of the Power Law exponents for each site, and the measured data. As a result, the cases of calculating using the proposed values were more similar to the cases using the measured data than the cases using the 0.143 value. Finally, we found that the propsed values of the Power Law exponent are available to more accurately estimate wind resources.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.4
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• pp.201-212
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• 2016

A Wind resource assessment and optimal micrositing of wind turbines were implemented for the development of an onshore wind farm of 30 MW capacity on Gadeok Island in Busan, Republic of Korea. The wind data measured by the automatic weather system (AWS) that was installed and operated in the candidate area were used, and a reliability investigation was conducted through a data quality check. The AWS data were measured for one year, and were corrected for the long term of 30 years by using the modern era retrospective analysis for research and application (MERRA) reanalysis data and a measure- correlate-predict (MCP) technique; the corrected data were used for the optimal micrositing of the wind turbines. The micrositing of the 3 MW wind turbines was conducted under 25 conditions, then the best-optimized layout was analyzed with a various wake model. When the optimization was complete, the estimated park efficiency and capacity factor were from 97.6 to 98.7 and from 37.9 to 38.3, respectively. Furthermore, the annual energy production (AEP), including wake losses, was estimated to be from 99,598.4 MWh to 100,732.9 MWh, and the area was confirmed as a highly economical location for development of a wind farm.

• Journal of Bio-Environment Control
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• v.10 no.1
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• pp.42-49
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• 2001

This study was carried out to develop a fuzzy control technique of ventilation window for controlling a temperature in a greenhouse. To reduce the fuzzy variables, the inside air temperature shop was taken as one of fuzzy variables, because the inside air temperature variation of a greenhouse by ventilation at the same window aperture is affected by difference between inside and outside air temperature, outside wind speed and the wind direction. Therefore, the antecedent variables for fuzzy algorithm were used the control error and its slop, which was same value as the inside air temperature slop during the control period, and the conclusion variable was used the window aperture opening rate. Through the basic and applicative control experiment with the control period of 3 minutes the optimum ranges of fuzzy variables were decided. The control error and its slop were taken as 3 and 1.5 times compared with target error in steady state, and the window opening rate were taken as 30% of full size of the window aperture. To evaluate the developed fuzzy algorithm in which the optimized 19 rules of fuzzy production were used, the performances of fuzzy control and PID control were compared. The temperature control errors by the fuzzy control and PID control were lower than 1.3$^{\circ}C$ and 2.2$^{\circ}C$ respectively. The accumulated operating size of the window, the number of operating and the number of inverse operating for the fuzzy control were 0.4 times, 0.5 times and 0.3 times of those compared with the PID control. Therefore, the fuzzy control can operating the window more smooth and reduce the operating energy by 1/2 times of PID control.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.4
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• pp.785-796
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• 2000

In this study, the possibility of application of TUNVEN model was investigated through the validation and calibration processes. In order to validate and calibrate the TUNVEN model developed in USA to obtain prediction of the quasi-steady state longitudinal air velocities and the pollutants concentrations by solving the coupled one-dimensional steady state tunnel aerodynamic and advection equations. The major input parameters such as the concentration data for CO and $NO_x$, meteorological data and traffic volume in Hawngryung tunnel were measured. Prior to preparing the input parameters, the sensitivity analysis was conducted to identify the input parameters which need to be most accurately estimated in TUNVEN program. In order to establish the relationships between the model values and the measured values, the linear regression analysis was applied. In linear regression analysis, the model values were taken as independent parameter(X) and the measured values were taken as dependent parameter(Y) for four cases of data sef. From the results of linear regression analysis, the correlation coefficient(r) for four cases were calculated more than 0.91 and the values of slope and interception were analyzed as 0.5~2.2 and 0.01~2.3 respectively. From the above results, we concluded that the suitability of TUNVEN model was identified in prediction the longitudinal pollutant concentrations in tunnel.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Ecology and Resilient Infrastructure
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• v.7 no.1
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• pp.43-52
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• 2020

For investigating restriction in the use of computer modeling results without adjusting them with measured data, this study analyzed and compared microclimatic aspects and human thermal sensation between in situ measurement and computer modeling using ENVI-met in and around a small urban park of downtown Changwon in May, 2012. In the results, ENVI-met underestimated air temperatures and wind speeds than the measured ones and overestimated relative humidities. In the radiation analysis, ENVI-met overestimated solar radiation from the sky hemisphere and terrestrial radiation from the ground hemisphere and underestimated terrestrial radiation from the sky hemisphere. Also, the differences of mean radiant temperatures with the measured ones reached up to 19.6℃ which could create an 1.2 PMV difference. ENVI-met overestimated up to 2.3 PMV and 4℃ UTCI at 12:00. The difference was shown clearly in PMV than in UTCI. Therefore, when computer modeling is used in urban microclimate and human thermal sensation (comfort) studies the modeling results should be compared with measured data and adjusted adequately to adopt the results to urban and landscape planning and design.