• Magazine of the Korea Concrete Institute
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• 제6권2호
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• pp.59-67
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• 1994

• The Plant Pathology Journal
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• 제17권6호
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• pp.373.3-373
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• 2001

• Atmosphere
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• 제21권2호
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• pp.197-208
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• 2011

The objective of this study is to describe the short-range forecast system of the Korea Air Force (KAF) and to verificate its performace in 2009 summer. The KAF weather prediction model system, based on the Weather Research and Forecasting (WRF) model (i.e., the KAF-WRF), is configured with a parent domain overs East Asia and two nested domains with the finest horizontal grid size of 2 km. Each domain covers the Korean peninsula and South Korea, respectively. The model is integrated for 84 hour 4 times a day with the initial and boundary conditions from National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) data. A quantitative verification system is constructed for the East Asia and Korean peninsula domains. Verification variables for the East Asia domain are 500 hPa temperature, wind and geopotential height fields, and the skill score is calculated using the difference between the analysis data from the NCEP GFS model and the forecast data of the KAF-WRF model results. Accuracy of precipitation for the Korean penisula domain is examined using the contingency table that is made of the KAF-WRF model results and the KMA (Korea Meteorological Administraion) AWS (Automatic Weather Station) data. Using the verification system, the operational model and parallel model with updated version of the WRF model and improved physics process are quantitatively evaluated for the 2009 summer. Over the East Aisa region, the parallel experimental model shows the better performance than the operation model. Errors of the experimental model in 500 hPa geopotential height near the Tibetan plateau are smaller than errors in the operational model. Over the Korean peninsula, verification of precipitation prediction skills shows that the performance of the operational model is better than that of the experimental one in simulating light precipitation. However, performance of experimental one is generally better than that of operational one, in prediction.

• Atmosphere
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• 제25권4호
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• pp.611-622
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• 2015

Heavy rainfall ($>30mm\;hr^{-1}$) over the Korean Peninsula is examined in order to understand thermo-dynamic characteristics of the atmosphere, using radiosonde observational data from seven upper-air observation stations during the last 17 years (1997~2013). A total of 82 heavy rainfall cases during the summer season (June-August) were selected for this study. The average values of thermo-dynamic indices of heavy rainfall events are Total Precipitable Water (TPW) = 60 mm, Convective Available Potential Energy (CAPE) = $850J\;kg^{-1}$, Convective Inhibition (CIN) = $15J\;kg^{-1}$, Storm Relative Helicity (SRH) = $160m^2s^{-2}$, and 0~3 km bulk wind shear = $5s^{-1}$. About 34% of the cases were associated with a Changma front; this pattern is more significant than other synoptic pressure patterns such as troughs (22%), migratory cyclones (15%), edges of high-pressure (12%), typhoons (11%), and low-pressure originating from Changma fronts (6%). The spatial distribution of thermo-dynamic conditions (CAPE and SRH) is similar to the range of thunderstorms over the United States, but extreme conditions (supercell thunderstorms and tornadoes) did not appear in the Korean Peninsula. Synoptic conditions, vertical buoyancy (CAPE, CIN), and wind parameters (SRH, shear) are shown to discriminate among the environments of the three types. The first type occurred with high CAPE and low wind shear by the edge of the high pressure pattern, but Second type is related to Changma front and typhoon, exhibiting low CAPE and high wind shear. The last type exhibited characteristics intermediate between the first and second types, such as moderate CAPE and wind shear near the migratory cyclone and trough.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제19권6호
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• pp.235-249
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• 2020

The Ministry of Land, Infrastructure and Transport established safety standards for Level 3 autonomous vehicles for the first time in the world in December 2019, and specified the safety standards for conditional autonomous driving systems. Accordingly, it is necessary to analyze the influence of various driving environments on take-over. In this study, using a driving simulator, we investigated how traffic conditions and weather conditions affect take-over time and stabilization time. The experimental procedure was conducted in the order of preliminary training, practice driving, and test driving, and the test driving was conducted by dividing into a traffic density and geometry experiment and a weather environment experiment. As a result of the experiment, it was analyzed that the traffic volume and weather environment did not affect the take-over time and take-over stabilization time, and only the curve radius affects take-over stabilization time.

• Current Optics and Photonics
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• 제2권1호
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• pp.15-22
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• 2018

To measure atmospheric temperature, water vapor, and aerosol simultaneously, an efficient multi-function Raman lidar using an ultraviolet-wavelength laser has been developed. A high-performance spectroscopic box that utilizes multicavity interference filters, mounted sequentially at small angles of incidence, is used to separate the lidar return signals at different wavelengths, and to extract the signals with high efficiency. The external experiments are carried out for simultaneous detection of atmospheric temperature, water vapor, and aerosol extinction coefficient in Beijing, under clear and hazy weather conditions. The vertical profiles of temperature, water vapor, and aerosol extinction coefficient are analyzed. The results show that for an integration time of 5 min and laser energy of 200 mJ, the mean deviation between measurements obtained by lidar and radiosonde is small, and the overall trend is similar. The statistical temperature error for nighttime is below 1 K up to a height of 6.2 km under clear weather conditions, and up to a height of 2.5 km under slightly hazy weather conditions, with 5 min of observation time. An effective range for simultaneous detection of temperature and water vapor of up to 10 km is achieved. The temperature-inversion layer is found in the low troposphere. Continuous observations verify the reliability of Raman lidar to achieve real-time measurement of atmospheric parameters in the troposphere.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제33권3호
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• pp.1105-1113
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• 2013

Understanding the characteristics of truck-involved crashes is of keen interest because such crashes are highly associated with greater potential leading to severer injury. The purpose of this study is to identify factors affecting injury severity of truck-involved crashes on freeways. In addition, a binary logistic regression technique is applied to identify causal factors affecting truck crash severity under normal and adverse weather conditions. Major findings from the analyses are discussed with truck operations strategies including speed enforcement, variable speed limit, and truck lane restriction, from the safety enhancement point of view. The results of this study would be useful for developing traffic control and operations strategies to reduce truck-involved crashes and injury severity in practice.

• Journal of Korea Port Economic Association
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• 제33권2호
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• pp.83-96
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• 2017

As a way to address global warming, among the renewable energy sources, there have been heavy investments worldwide for the development of offshore wind farms. However, such development has a drawback: investment costs are higher than those for onshore wind farms due to required operations such as offshore transportation and installation. In particular, delays in installation due to adverse maritime weather conditions are factors that affect the economics of offshore wind farms' operation. Therefore, in this study, we analyze the optimal schedule of the construction of an offshore wind farm from a macro perspective by considering the weather conditions in Korea. For this purpose, we develop a mathematical model and apply it to a 2.5 GW offshore wind farm project on the southwestern coast of the country. We use data from the Korea Meteorological Agency for maritime weather conditions and attempt to reflect the actual input data based on precedent cases overseas. The results show that it takes 6 months to install 35 offshore wind turbines. More specifically, it is pointed out that it is possible to minimize costs by not working in winter.

• International Journal of Highway Engineering
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• 제20권2호
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제19권3호
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• pp.533-542
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• 1994

In a Doppler weather radar, high resolution windspeed profile measurements are needed to provide reliable detection of a hazardous weather condition. For this purpose, the pulse-pair method is generally considered to be the most efficient estimator. However, this estimator has some bias errors due to asymmetric spectra and may yield meaningless results in the case of a multimodal return spectrum in this paper, bias errors were analyzed and an improved method was suggested to reduece these errors. For the case of a multimodal or seriously skewed spectrum, the modes of spectrum may provide more reliable information than the statistical mean. Therefore, the idea of a relatively simple mode estimator is also developed.