• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.203-210
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• 2019

Recently, a number of researchers have produced research and reports in order to forecast more exactly air quality such as particulate matter and odor. However, such research mainly focuses on the atmospheric diffusion models that have been used for the air quality prediction in environmental engineering area. Even though it has various merits, it has some limitation in that it uses very limited spatial attributes such as geographical attributes. Thus, we propose the new approach to forecast an air quality using a deep learning based ensemble model combining temporal and spatial predictor. The temporal predictor employs the RNN LSTM and the spatial predictor is based on the geographically weighted regression model. The ensemble model also uses the RNN LSTM that combines two models with stacking structure. The ensemble model is capable of inferring the air quality of the areas without air quality monitoring station, and even forecasting future air quality. We installed the IoT sensors measuring PM2.5, PM10, H2S, NH3, VOC at the 8 stations in Jeonju in order to gather air quality data. The numerical results showed that our new model has very exact prediction capability with comparison to the real measured data. It implies that the spatial attributes should be considered to more exact air quality prediction.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.221-226
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• 2008

A microchannel condenser as a part of a R410A residential air-conditioning system was examined experimentally and numerically in this study. The system was operated in separate environmental chambers and its performance was measured in ARI A, B, and C conditions. A numerical model for the microchannel condenser was developed and its results were compared with the experimental results. The model simulated the condenser with the assumption of the uniform air and refrigerant distribution, and with the consideration of the non-uniform air distribution at the face of the condenser and refrigerant distribution in the headers. In order to consider the non-uniform air distribution, air velocity contours were generated from the measured local air velocities at the face of the condenser. The simulation results showed that the effect of the air and refrigerant distribution was not a significant parameter in predicting the capacity of the microchannel condenser which was experimentally examined in this study. The comparison of the calculated and experimental results showed that the condenser capacity could be predicted well for every test condition. However, the prediction of refrigerant pressure drop deviated significantly from the measured values.

• Journal of the Korean Society of Visualization
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• v.20 no.2
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• pp.21-27
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• 2022

Air purifiers can be placed where the air cleaning is required, making it easy to manage indoor air quality. The position of the air purifier affects the indoor airflow pattern, resulting in different air cleaning efficiency. Many efforts and strategies have been examined through numerical simulations and experiments to find the proper location of the air purifier, but problems still remain due to the various geometrical indoor spaces and arrangements. Herein, we develop an artificial intelligence model to predict the performance of an air purifier depending on the installation location. To obtain the training data, numerical simulations were performed on the different locations of the air purifiers and airflow patterns. The trained artificial intelligence model predicted the air exchange performance depending on the installation location of the air purifier with a prediction accuracy of 92%.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.105-113
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• 2017

This study considers an optimal investment planning for improving survivability from an air threat in the layered air defense system. To establish an optimization model, we first represent the layered air defense system as a network model, and then, present two optimization models minimizing the failure probability of counteracting an air threat subject to budget limitation, in which one deals with whether to invest and the other enables continuous investment on the subset of nodes. Nonlinear objective functions are linearized using log function, and we suggest dynamic programming algorithm and linear programing for solving the proposed models. After designing a layered air defense system based on a virtual scenario, we solve the two optimization problems and analyze the corresponding optimal solutions. This provides necessity and an approach for an effective investment planning of the layered air defense system.

• Journal of Information Technology and Architecture
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• v.11 no.2
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• pp.157-173
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• 2014

As Air Base Defence, Anti-Aircraft Defence and Nuclear-Biological-Chemical Protection model considered as ground operation models in Republic of Korea Air Force are designed as the voice-centered system between participant nodes, there is a problem communicating accurately. In recent years, the military is developing a command and control capability using data communication technology to solve the problem. Therefore, this paper proposes new model to maximize efficiency of performance improvement through the Data Communication-based Future Air Base Defence Model. We refer to a research paper that is related existing and developed new model. and then we really experimented under WiBro Network that is constructed to Air Base for maintenance control. Based on the analysis and the test result of new Air Base Defence Model, we have concluded that the performance improvement effect is reached.

• Preventive Nutrition and Food Science
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• v.13 no.3
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• pp.225-230
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• 2008

Onion slices were dehydrated in a single layer at drying air temperatures ranging from $50{\sim}70^{\circ}C$ in a laboratory scale convective hot-air dryer at an air velocity of 0.66 m/s. The effect of drying air temperature on the drying kinetic characteristics were determined. It was found that onion slices would dry within $210{\sim}460\;min$ under these drying conditions. Moisture transfer during dehydration was described by applying the Fick's diffusion model and the effective diffusivity changed between $1.345{\times}10^{-8}$ and $2.658{\times}10^{-8}\;m^2/s$. A non-linear regression procedure was used to fit 9 thin layer drying models available in the literature to the experimental drying curves. The Logarithmic model provided a better fit to the experimental drying data as compared to other models. Temperature dependency of the effective diffusivity during the hot-air drying process obeyed the Arrhenius relationship with estimated activation energy being 31.36 kJ/mol. The effect of the drying air temperature on the drying model constants and coefficients were also determined.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.10
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• pp.467-473
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• 2014

Since the operating conditions of HVAC systems are different from those for which they are designed, on-going commissioning is required to optimize the energy consumed and the environment in the building. This study presents a methodology to analyze operational data and its applications. A predicted operation model is to be produced through a statistical data analysis using multiple regressions in SPSS. In this model, the dependent variable is the pre-cooling time, and the independent variables include the power output of the supply air inverter during pre-cooling, the supply air set temperature during pre-cooling, the indoor temperature-indoor set temperature just before pre-cooling, supply heat capacity, and the lowest outdoor air temperature during non-cooling/non-heating hours. The correlation coefficient R2 of the multiple regression model between the pre-cooling hour and the internal/external factors is of 0.612, and this could be used to provide information related to energy conservation and operating guidance.

• Asian Journal of Atmospheric Environment
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• v.8 no.4
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• pp.184-191
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• 2014

Air quality in a subway tunnel has been crucial in most of the subway environments where IAQ could be affected by many factors such as the number of passengers, the amount and types of ventilation, train operation factors and other facilities. A modeling approach has been introduced to manage the general IAQ in a subway station. Field surveys and $CO_2$ measurements were initially conducted to analyze and understand the relationship between indoor and outdoor air quality while considering internal pollution sources, such as passengers and subway trains, etc. The measurement data were then employed for the model development with other statistical information. For the model development, the algorithm of simple continuity was set up and applied to model the subway IAQ concerned, while considering the major air transport through staircases and tunnels. Monitored $CO_2$ concentration on the concourse and platform were correlated with modeling results where the correlation values for the concourse and platform were $R^2=0.96$ and $R^2=0.75$, respectively. It implies that the box modeling approach introduced in this study would be beneficial to predict and control the indoor air quality in subway environments.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.10
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• pp.947-955
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• 2005

For the purpose of evaluating the thermal performance for air-barrier air conditioning system in perimeter zone, two air-conditioning systems, conventional perimeter air-conditioning system and air-barrier system, are evaluated and compared by scale model experiment and simulation during cooling season. As a result, measurement shows that supply air velocity of 1 m/s in the upstream direction at perimeter is more effective. Air-barrier system could reduce the cooling energy by $10\sim20\%$ compared with conventional system. Numerical simulation was carried out considering solar effect for reliable result. This method has improved the accuracy of numerical simulation for the space affected by the solar radiation. Both measurement and simulation results show that supply air velocity of 1 m/s at perimeter is the most effective.

• Environmental Analysis Health and Toxicology
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• v.26
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• pp.4.1-4.6
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• 2011

Objectives: This study was carried out to determine whether or not pine needles can be used as passive samplers of atmospheric polycyclic aromatic hydrocarbons (PAHs) using the correlation between accumulated PAH concentrations in air (Ca, ng/$m^3$) and those deposited on pine needles (Cp, ng/g dry). Methods: PAHs in ambient air was collected using low volume PUF sampler and pine needles was gathered at same place for 7 months. Results: A good correlation ($R^2$=0.8582, p<0.05) was found between Ca and Cp for PAHs with a higher gaseous state in air (AcPy, Acp, Flu, Phen, Ant, Flt, Pyr, BaA and Chry), but there was a poorer correlation ($R^2$=0.1491, p=0.5123) for the PAHs with a lower gaseous state (BbF, BkF, BaP, DahA, BghiP and Ind123). A positive correlation ($R^2$=0.8542) was revealed between the logarithm of the octanol-air partitioning coefficient ($logK_{oa}$) and Cp/Ca for the PAHs with a higher gaseous state in air, but there was a negative correlation ($R^2$=0.8131) for the PAHs with a lower gaseous state. The Ca-Cp model could not be used to estimate PAHs concentrations in air using deposited PAHs concentrations on pine needles, but the logKoa-Cp/Ca model could be used. Conclusions: It was found that pine needles can be used as passive samplers of atmospheric PAHs.