• Atmosphere
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• v.23 no.1
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• pp.93-102
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• 2013

Atmospheric transport pathway of an air mass is an important constraint controlling the chemical properties of the air mass observed at a designated location. Such information could be utilized for understanding observed temporal variabilities in atmospheric concentrations of long-lived chemical compounds, of which sinks and/or sources are related particularly with natural and/or anthropogenic processes in the surface, and as well as for performing inversions to constrain the fluxes of such compounds. The Lagrangian particle dispersion model FLEXPART provides a useful tool for estimating detailed particle dispersion during atmospheric transport, a significant improvement over traditional "single-line" trajectory models that have been widely used. However, those without a modeling background seeking to create simple back-trajectory maps may find it challenging to optimize FLEXPART for their needs. In this study, we explain how to set up, operate, and optimize FLEXPART for back-trajectory analysis, and also provide automatization programs based on the open-source R language. Discussions include setting up an "AVAILABLE" file (directory of input meteorological fields stored on the computer), creating C-shell scripts for initiating FLEXPART runs and storing the output in directories designated by date, as wells as processing the FLEXPART output to create figures for a back-trajectory "footprint" (potential emission sensitivity within the boundary layer). Step by step instructions are explained for an example case of calculating back trajectories derived for Anmyeon-do, Korea for January 2011. One application is also demonstrated in interpreting observed variabilities in atmospheric $CO_2$ concentration at Anmyeon-do during this period. Back-trajectory modeling information introduced in this study should facilitate the creation and automation of most common back-trajectory calculation needs in atmospheric research.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.3
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• pp.297-306
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• 2013

This study used long-term air and weather data from 2000 to 2009 as raw data sets to develop regression models in order to estimate precipitation scavenging contributions of ambient $PM_{10}$ and $NO_2$ in Korea. The data were initially analyzed to calculate scavenging ratio (SR), defined as the removal efficiency for $PM_{10}$ and $NO_2$ by actual precipitation. Next, the effective scavenging contributions (ESC) with considering precipitation probability density were calculated for each sector of precipitation range. Finally, the empirical regression equations for the two air pollutants were separately developed, and then the equations were applied to test the model validity with the raw data sets of 2010 and 2011, which were not involved in the modeling process. The results showed that the predicted $PM_{10}$ ESC by the model was 23.8% and the observed $PM_{10}$ ESCs were 23.6% in 2010 and 24.0% in 2011, respectively. As for $NO_2$, the predicted ESC by the model was 16.3% and the observed ESCs were 16.4% in 2010 and 16.6% in 2011, respectively. Thus the developed regression models fitted quite well the actual scavenging contribution for both ambient $PM_{10}$ and $NO_2$. The models can then be used as a good tool to quantitatively apportion the natural and anthropogenic sink contribution in Korea. However, to apply the models for far future, the precipitation probability density function (PPDF) as a weather variable in the model equations must be renewed periodically to increase prediction accuracy and reliability. Further, in order to apply the models in a specific local area, it is recommended that the long-term oriented local PPDF should be inserted in the models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.740-746
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• 2017

Infrared signatures emitted from hot exhaust gases generated by the internal combustion engine and generator of naval ships and from the metal surfaces of the funnel have become the targets of infrared homing missiles, which is the main cause of a reduced survivability of naval ships. The infrared signatures from the exhaust gas and the metal surface of a funnel can be reduced by installing an infrared signature suppression (IRSS) system on a ship. The IRSS system consists of three parts: an eductor that generates turbulent flow of the exhaust gas, a mixing tube that mixes the exhaust gas with ambient air, and a diffuser that forms an air film using the pressure difference between the inside and outside air. As a basic study to develop an IRSS system using domestic technology, this study analyzed the model test conditions of an IRSS system developed by an overseas engineering company and installed on a domestic naval ship, and a numerical heat-flow analysis was conducted based on the results of the aforementioned analysis. Numerical heat-flow analysis was performed using a commercial numerical-analysis application, and various turbulence models were considered. As a result, the temperature and velocity of the exhaust gas at the educator inlet and diffuser outlet and that of the metal surface of the diffuser were measured, and found to agree well with the measurement results of the model test.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.4
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• pp.393-399
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• 2017

In a reciprocating compressor, the piston and connecting rod are important parts. Excess mechanical stress on these parts may cause damage, and broken parts are expensive and difficult to replace. Therefore, it is necessary to analyze the mechanical stress affecting durability and longevity. The main purpose of this study was to identify locations of maximum stress on pistons and connecting rods. Based on dynamic calculation of the working process of a specific air compressor, an analysis of piston and connecting rod performance has been completed. A three-dimensional model for the air compressor's pistons and connecting rods was built separately, and FEM analysis of these components was carried out using a numerical method. The pistons were loaded by pressure which was changed according to crankshaft angle without thermal boundary conditions. The simulation results were used to predict and estimate stress concentration as well as the value of this stress on pistons and connecting rods. The maximum equivalent stress calculated are over 190 MPa on pistons and 123 MPa on connecting rods at crank angle $135^{\circ}$ and $225^{\circ}$ but these are under tensile yield strength. Besides, the calculated safety factors of connecting rods and pistons is higher than 1. Moreover, the results obtained can be used to provide manufacturers with references to optimize the design of pistons and connecting rods for reciprocating compressors.

• Journal of Distribution Science
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• v.12 no.2
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• pp.59-71
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• 2014

Purpose - In recent years, many firms have attempted various approaches to cope with the continual increase of aviation transportation. The previous research into freight charge forecasting models has focused on regression analyses using a few influence factors to calculate the future price. However, these approaches have limitations that make them difficult to apply into practice: They cannot respond promptly to small price changes and their predictive power is relatively low. Therefore, the current study proposes a freight charge-forecasting model using time series data instead a regression approach. The main purposes of this study can thus be summarized as follows. First, a proper model for freight charge using the autoregressive integrated moving average (ARIMA) model, which is mainly used for time series forecast, is presented. Second, a modified ARIMA model for freight charge prediction and the standard process of determining freight charge based on the model is presented. Third, a straightforward freight charge prediction model for practitioners to apply and utilize is presented. Research design, data, and methodology - To develop a new freight charge model, this study proposes the ARIMAC(p,q) model, which applies time difference constantly to address the correlation coefficient (autocorrelation function and partial autocorrelation function) problem as it appears in the ARIMA(p,q) model and materialize an error-adjusted ARIMAC(p,q). Cargo Account Settlement Systems (CASS) data from the International Air Transport Association (IATA) are used to predict the air freight charge. In the modeling, freight charge data for 72 months (from January 2006 to December 2011) are used for the training set, and a prediction interval of 23 months (from January 2012 to November 2013) is used for the validation set. The freight charge from November 2012 to November 2013 is predicted for three routes - Los Angeles, Miami, and Vienna - and the accuracy of the prediction interval is analyzed using mean absolute percentage error (MAPE). Results - The result of the proposed model shows better accuracy of prediction because the MAPE of the error-adjusted ARIMAC model is 10% and the MAPE of ARIMAC is 11.2% for the L.A. route. For the Miami route, the proposed model also shows slightly better accuracy in that the MAPE of the error-adjusted ARIMAC model is 3.5%, while that of ARIMAC is 3.7%. However, for the Vienna route, the accuracy of ARIMAC is better because the MAPE of ARIMAC is 14.5% and the MAPE of the error-adjusted ARIMAC model is 15.7%. Conclusions - The accuracy of the error-adjusted ARIMAC model appears better when a route's freight charge variance is large, and the accuracy of ARIMA is better when the freight charge variance is small or has a trend of ascent or descent. From the results, it can be concluded that the ARIMAC model, which uses moving averages, has less predictive power for small price changes, while the error-adjusted ARIMAC model, which uses error correction, has the advantage of being able to respond to price changes quickly.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.213-223
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• 2017

Recently, the air quality of South Korea has deteriorated and public interest has been increasing. Various observation means are used for the monitoring of the atmospheric environment, but it relies on the experience and judgment of the observer in the absence of spatial information on the emission facilities. The purpose of this study was to determine the availability of using drones for monitoring air pollutant emission facilities. A texture transformation method was applied to the drone ortho image to detect the small gas emission facility and the slope data calculated by the digital surface model (DSM) was used to reduce the false alarm ratio. As a result, it shows the possibility of using drones in the detection of small gas emission facilities by showing about 80% of positive detection ratio and 40% of false alarm ratio. In the future, various researches are required to the improve positive detection ratio and the reduction of the false alarm ratio. Based on these results, it is necessary to construct a database including 3D spatial information of air pollutant emission facilities.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.123-133
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• 2007

Thermal spatial representativities of meteorological stations over Korea have been investigated using land surface temperature (LST) based on MODerate resolution Imaging Spectroradiometer (MODIS) satellite observation. The linear regression method was used to estimate air temperatures from MODIS LST product. To compare MODIS LST with observed air temperatures at six meteorological stations, the mean values of MODIS LST with nine given window sizes were calculated. In this case, the position of centered pixel in each given window size is correspond to that of each meteorological station. We also applied $4^{\circ}C$ threshold for RMSE comparison, which is based on a analogous study on daily maximum air temperature model using satellite data. In this study, the results showed that each station has a different representativity; Deajeon $15km{\times}15km$, Chuncheon $11km{\times}11km$, Seoul $7km{\times}7km$, Deagu $5km{\times}5km$, Kwangju $3km{\times}3km$, and Busan $3km{\times}3km$.

• Journal of Environmental Health Sciences
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• v.46 no.2
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• pp.136-149
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• 2020

Objectives: The purpose of this study was to perform an aggregate human risk assessment for benzene in an industrial complex using the CalTOX model and to improve the reliability and predictability of the model by analyzing the uncertainty and sensitivity of the predicted assessment results. Methods: The CalTOX^TM 4.0 beta model was used to evaluate a selected region, and @Risk 7.6 software was used to analyze uncertainty and sensitivity. Results: As a result of performing the aggregate risk assessment on the assumption that 6.45E+04 g/d of benzene would be emitted into the atmosphere over two decades, 3% of the daily source term to air remained in the selected region, and 97% (6.26E+04 g/d) moved out of the region. As for exposure by breathing, the predicted LADD_inhalation was 2.14E-04 mg/kg-d, and that was assessed as making a 99.99% contribution to the LADD_total. Regarding human Risk_cancer assessment, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was identified as the most influential variable, followed by 'exposure time, active indoors (h/day)', and 'exposure duration (years)'. Conclusions: As for the results of the human cancer risk assessment for the selected region, the predicted human cancer risk was 5.19E-06 (95% CI; 4.07E-06-6.81E-06) (in the 95th percentile, corresponding to the highest exposure level, a confidence interval of 90%). As a result of analyzing sensitivity, 'source term to air' was found to be most influential.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.2
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• pp.161-168
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• 2011

The heating, ventilating, air conditioning (HVAC) system is a very important part of an automotive vehicle: it controls the microclimate inside the passenger's compartment and removes the frost or mist that is produced in cold/rainy weather. In this study, the numerical analysis of the defrost duct in an HVAC system and the de-icing pattern is carried out using commercial CFX-code. The mass flow distribution and flow structure at the outlet of the defrost duct satisfied the duct design specification. For analyzing the de-icing pattern, additional grid generation of solid domain of ice and glass is pre-defined for conductive heat transfer. The flow structure near the windshield, streakline, and temperature fields clearly indicate that the de-icing capacity of the given defrost duct configuration is excellent and that it can be operated in a stable manner. In this paper, the unsteady changes in temperature, water volume fraction, and static enthalpy at four monitoring points are discussed.

• Solar Energy
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• v.12 no.3
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• pp.70-83
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• 1992

The interaction between the surface radiation and the mixed convection transport from an isolated thermal source, with a uniform surface heat flux input and located in a rectangular enclosure, is stuied numerically. The enclosure simulates a practical system such an air cooled electric device, where an air-stream flows through the openings on the two vertical walls. The heat source represents an electric component located in such an enclosure. The size of this cavity is $0.1[m]{\times}0.1[m]$. The inlet velocity is assumed as 0.07[m/s] and the inlet temperature is maintained as $27^{\circ}C$. The inflow is kept at a fixed position. Laminar, two dimensional flow is assumed, and the problem lies in the mixed convection regime, governed by buoyancy force and surface readiation. The significant variables include the location of the out-flow opening, of the heat source and the wall emissivity. The basic nature of the resulting interaction betwwn the externally induced air stream and the buoyancy-driven flow generated by the source is investigated. As a result, the best location of the heat source to make the active heat transfer is 0.075[m] from the left wall on the floor. The trends observed are also discussed in terms of heat removal from practical systems such as electric circuitry.