• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.483-489
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• 2014

This study aimed at a scientific examination of the relationship between NVOCs concentration and the physical environment of red pine forest in spring season. Atmospheric NVOC samples in red pine forest was collected through five trials conducted from March to May 2013, using Tanax-Ta-charged disposable tubes and mini-pumps. At each trial, measurements were taken at three different points in daytime (sunrise, southing and sunset). For maximum accuracy, two tubes were used for each measurement at the same location, and the mean value was used for analysis. Compound analysis on the NVOC samples was done using the HS-SPME method and GC-MS. Analysis of the relationship between NVOC and the physical forest environment found higher concentrations of most substances, including ${\alpha}$-pinene and ${\beta}$-pinene, with higher temperature, dew point, and lower concentrations with higher wind velocity. The findings of this study offer scientific evidence which can inform the creation of 'healing forests' and 'recreational forests' as well as forest environment in general, helping to promote public health and recreational activities.

• Journal of Energy Engineering
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• v.5 no.2
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• pp.160-169
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• 1996

Parametric studies are conducted for optimizing the integration design between gas turbine compressor and air separation unit (ASU) of integrated gasification combined cycle power plant. The present study adopts the ASU of double-distillation column process, from which integration conditions with compressor such as the heat exchanger condition between air and nitrogen, the amount and the pressure of extracted air are defined and mathematically formulated. The performance variations of the compressor integrated with ASU are analyzed by combining streamline curvature method and pressure loss models, and the predicted results are compared with the performance test results of actual compressors to verify the prediction accuracy. Using the present performance prediction method, the effects of pinch-point temperature difference (PTD) in the heat exchanger, the amount and the pressure of extracted air on compressor performances are quantitatively examined. As the extraction air amount or the PTD is increased, the pressure ratio and the power consumption of compressor are increased. The compressor efficiency deteriorates as the increase of the flow rate of air extracted at higher pressure level while improving at lower pressure air extraction. Furthermore, through the characteristic curve between generalized inlet condition and efficiency of compressor, optimal integration condition is presented to maximize the compressor efficiency.

• Journal of Environmental Impact Assessment
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• v.23 no.6
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• pp.432-444
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• 2014

When the water quality modelling is done with a manual calibration, it is possible that the researcher's opinion may affect the objectivity of the research. Hence, the role of the automatic calibration is highly important. This research applies a technique to automatically calibrate the water quality parameters by implementing an optimization method. This involves estimating the optimum water quality parameters targeting influential parameters towards the lake's BOD, DO, Phosphorus, Nitrogen and Phytoplankton. To accurately calculate the water temperature and hydraulic characteristics of a deep, stratifying lake, EFDC, a 3-dimensional hydraulic model which can be linked to the WASP7 was applied. With EFDC, the segment of the lake is formed and utilized as an input data of the WASP7. For the calibration of the water quality parameters of the WASP7, an influence coefficient algorithm and a genetic algorithm was applied. Of the five water quality variables for calibration, the normalized residuals of the observed and calculated values of DO, TN, CBOD were relatively small and the three water quality variables were calibrated properly. Yet the accuracy of the calibration of TP and Chl-a was relatively low.

• Korean Journal of Poultry Science
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• v.28 no.3
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• pp.215-224
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• 2001

Since nitrogen(N) is a volatile compound affected by many environmental factors, determining the N content of manure tends to be difficult. Upon arrival in the laboratory, the manure should be moist and refrigerated. Manure samples will have variable N contents due to drying temperature, and the presence of soil in the sample will affect N content. Acidification of the sample prevents ammonia volatilization and should be done before drying. It is recommended that manure samples be pretreated with a strong oxidizing agent, KMnO$_4$, followed by digestion under reduced conditions (reduced Fe-$H_{2}$ $SO_{4}$ ), which achieves a complete recovery of both $NO_{3}$ -N and $NO_{2}$ -N without a low recovery of $NH_{4}$ -N, resulting in a more accurate determination of N content. Accuracy of results for N content determined by recently developed rapid analysis techniques in the field should be tested by comparison with results obtained at laboratories using approved standard methods. Most commonly, the Kjeldahl system is used to determine manure N content. More research is needed on the effects of species, breed, age and individuals on the nutrient contents of manure. The procedures for manure sampling on the farm, shipping and handling of the sample until it reaches the laboratory, and the methods of sampling of the manure at the laboratory must be studied. Development of animal agricultural laboratories where feed, manure, soil, and water are all analyzed by appropriate specialists is needed.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1075-1086
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• 2019

Recently, as the incidence of climate warming and abnormal climate increases, the forecasting of hydrological factors such as precipitation and river flow is getting more complicated, and the risk of water shortage is also increasing. Therefore, this study aims to develop a model for predicting the amount of water intake in mid-term. To this end, the correlation between water intake and meteorological factors, including temperature and precipitation, was used to select input factors. In addition, the amount of water intake increased with time series and seasonal characteristics were clearly shown. Thus, the preprocessing process was performed using the time series decomposition method, and the support vector machine (SVM) was applied to the residual to develop the river intake prediction model. This model has an error of 4.1% on average, which is higher accuracy than the SVM model without preprocessing. In particular, this model has an advantage in mid-term prediction for one to two months. It is expected that the water intake forecasting model developed in this study is useful to be applied for water allocation computation in the permission of river water use, water quality management, and drought measurement for sustainable and efficient management of water resources.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.1-15
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• 2007

The objective of this paper is the establishment of finite element analysis frame work for pavement research. Finite element analysis results simulating various loading experiments are verified with sensor measurements obtained from the KHC Test Road. The accuracy of the finite element analysis can be supported by these efforts so that it helps spread out the finite element analysis to pavement research and design processes. The finite element model used in this research is the full 3D nonlinear model including concrete slab, lean concrete base, subbase, shoulder, dowel, and tie-bar. In order to accomplish the accurate verification, the loading condition and the pavement temperature distribution are exactly simulated with field measured data. The curling behavior and the strain distribution are compared with measured responses from the loading tests with a truck and the FWD. Strain and curling predictions from the concrete slab are matched well with measured responses but the strain prediction from the lean concrete base is not matched with measured response. In addition, the magnitude of permanent curling is evaluated with the finite element analysis.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.599-605
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• 2019

Rice yield (kg 10a^-1) in South Korea was estimated by meteorological variables that are influential factors in crop growth. This study investigated the possibility of anticipating the rice yield variability using a simple but an efficient statistical method, a multiple linear regression analysis, on the basis of the annual variation of meteorological variables. Due to heterogeneous environmental conditions by region, the yearly rice yield was assessed and validated for each province in South Korea. The monthly mean meteorological data for the period 1986-2018 (33 years) from 61 weather stations provided by Korean Meteorological Administration was used as the independent variable in the regression analysis. An 11-fold (leave-three-out) cross-validation was performed to check the accuracy of this method estimating rice yield at each province. This result demonstrated that temporal variation of rice yield by province in South Korea can be properly estimated using such concise procedure in terms of correlation coefficient (0.7, not significant). Furthermore, the estimated rice yield well captured spatial features of observation with mean bias of 0.7 kg 10a^-1 (0.15%). This method may offer useful information on rice yield by province in advance as long as accurate agro-meteorological forecasts are timely obtained from climate models.

• Atmosphere
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• v.27 no.3
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• pp.359-370
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• 2017

In this study, the oceanic Total Precipitable Water (TPW) retrieval algorithm at 16 km altitude of High Altitude Long Endurance Unmanned Aerial Vehicle (HALE UAV) is described. Empirical equation based on Wentz method (1995) that uses the 18.7 and 22.235 GHz channels is developed using the simulated brightness temperature and SeeBor training dataset. To do radiative simulation, Satellite Data Simulator Unit (SDSU) Radiative Transfer Model (RTM) is used. The data of 60% (523) and 40% (349) in the SeeBor training dataset are used to develop and validate the TPW retrieval algorithm, respectively. The range of coefficients for the TPW retrieval at the altitude of 3~18 km with 3 km interval were 153.69~199.87 (${\alpha}$), 54.330~58.468 (${\beta}$), and 84.519~93.484 (${\gamma}$). The bias and RMSE at each altitude were found to be about $-0.81kg\;m^{-2}$ and $2.17kg\;m^{-2}$, respectively. Correlation coefficients were more than 0.9. Radiosonde observation has been generally operated over land. To validate the accuracy of the oceanic TPW retrieval algorithm, observation data from the Korea Meteorological Administration (KMA) Gisang 1 research vessel about six clear sky cases representing spring, autumn, and summer season is used. Difference between retrieved and observed TPW at 16 km altitude were in the range of $0.53{\sim}1.87kg\;m^{-2}$, which is reasonable for most applications. Difference in TPW between retrieval and observation at each altitude (3~15 km) is also presented. Differences of TPW at altitudes more than 6 km were $0.3{\sim}1.9kg\;m^{-2}$. Retrieved TPW at 3 km altitude was smaller than upper level with a difference of $-0.25{\sim}0.75kg\;m^{-2}$ compared to the observed TPW.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.53-59
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• 2014

In this study, we suggest a system to build the monitoring model for compressed natural gas (CNG) stations, operated in only non-stationary modes, and perform the real-time monitoring and the abnormality diagnosis using principal component analysis (PCA) that is suitable for processing large amounts of multi-dimensional data among multivariate statistical analysis methods. We build the model by the calculation of the new characteristic variables, called as the major components, finding the factors representing the trend of process operation, or a combination of variables among 7 pressure sensor data and 5 temperature sensor data collected from a CNG station at every second. The real-time monitoring is performed reflecting the data of process operation measured in real-time against the built model. As a result of conducting the test of monitoring in order to improve the accuracy of the system and verification, all data in the normal operation were distinguished as normal. The cause of abnormality could be refined, when abnormality was detected successfully, by tracking the variables out of the score plot.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.8
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• pp.640-647
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• 2014

Infrared signature of aircraft exhaust plume is the critical factor for aircraft survivability. To improve the military aircraft survivability, the accurate prediction of infrared signature for the propulsion system is needed. The numerical analysis of thermal fluid field for nozzle inflow, free stream flow, and plume region is conducted by using the in-house code. Weighted Sum of Gray Gases Model based on Narrow Band with regrouping is adopted to calculate the spectral infrared signature emitted from aircraft exhaust plume. The accuracy and reliability of the developed code are validated in the one-dimensional band model. It is found that the infrared radiant intensity is relatively more strong in the plume through the analysis, the results show the different characteristic of the spectral infrared signature along the temperature, the partial pressure, and the species distribution. The continuous spectral radiant intensity is shown near the nozzle exit due to the emission from the nozzle wall.