• Journal of the Korean Solar Energy Society
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• v.31 no.5
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• pp.47-59
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• 2011

The purpose of this paper is to simulate the high ozone concentration in Shiwha Banwol indusrial complex. High pollution episodes (ozone alert) of this area are the results of geographical location and its air pollutants emission. This research has used meteorological model (RAMS) and photochemical air pollution Model (CIT model). As first step of the evaluate of this combined model system simulations are done in terms of meteorological characteristics like wind fields, PBL-height, etc.. Numerical simulations are carried out with real meteorological synoptic data on June. 24-25, 2010. In comparison with real measurement and another research the model reflects well local meteorological phenomena and shows the possibility to be utilized to analyse the pollutant dispersion over irregular terrain region. The high ozone concentration is deeply correlated to the ambient air temperature, wind speed and solar radiation. Local meteorological phenomena like sea-land breeze impact on horizontal dispersion of ozone. This analysis of meteorological characteristics can, in turn, help to predict their influences on air quality and to manage the high ozone episodes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.759-765
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• 2011

This paper proposes an effective assistant model for considering the stator slot-opening effect on air gap flux density distribution in conventional interior-type permanent magnet (IPM) motor. Different from the conventional slot-opening effect analysis in surface-type PM (SPM) motor, a composite effect of slot-opening uniquely existing in IPM motor, which additionally causes enhancement of air gap flux density due to magnet flux path distortion in iron core between the buried PM and rotor surface. This phenomenon is represented by a proposed assistant model, which simply deals with this additional effect by modifying magnetic pole-arc using an effective method. The validity of this proposed analytical model is applied to predict the air gap flux density distribution in an IPM motor model and confirmed by finite element method (FEM).

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.9-19
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• 2015

Internal air temperature of greenhouse is an important variable that can be influenced by the complex interaction between outside weather and greenhouse inside climate. This paper focuses on a data-based model approach to predict internal air temperature of the greenhouse. External air temperature, solar radiation, wind speed and wind direction were measured next to an experimental greenhouse supported by the Electronics and Telecommunications Research Institute and used as input variables for the model. Internal air temperature was measured at the center of three sections of the greenhouse and used as an output variable. The proposed model consisted of a transfer function including the four input variables and tested the prediction accuracy according to the sampling interval of the input variables, the orders of model polynomials and the time delay variable. As a result, a second-order model was suitable to predict the internal air temperature having the predictable time of 20-30 minutes and average errors of less than ${\pm}1K$. Afterwards mechanistic interpretation was conducted based on the energy balance equation, and it was found that the resulting model was considered physically acceptable and satisfied the physical reality of the heat transfer phenomena in a greenhouse. The proposed data-based model approach is applicable to any input variables and is expected to be useful for predicting complex greenhouse microclimate involving environmental control systems.

• Journal of dental hygiene science
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• v.24 no.1
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• pp.22-28
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• 2024

Background: Particulate matter (PM) has been extensively observed due to its negative association with human health. Previous research revealed the possible negative effect of air pollutant exposure on oral health. However, the predictive model between air pollutant exposure and the prevalence of periodontitis has not been observed yet. Therefore, this study aims to propose a predictive model for the number of patients with periodontitis exposed to PM and atmospheric factors in South Korea using deep learning. Methods: This study is a retrospective cohort study utilizing secondary data from the Korean Statistical Information Service and the Health Insurance Review and Assessment database for air pollution and the number of patients with periodontitis, respectively. Data from 2015 to 2022 were collected and consolidated every month, organized by region. Following data matching and management, the deep neural networks (DNN) model was applied, and the mean absolute percentage error (MAPE) value was calculated to ensure the accuracy of the model. Results: As we evaluated the DNN model with MAPE, the multivariate model of air pollution including exposure to PM_2.5, PM₁₀, and other atmospheric factors predict approximately 85% of the number of patients with periodontitis. The MAPE value ranged from 12.85 to 17.10 (mean±standard deviation=14.12±1.30), indicating a commendable level of accuracy. Conclusion: In this study, the predictive model for the number of patients with periodontitis is developed based on air pollution, including exposure to PM_2.5, PM₁₀, and other atmospheric factors. Additionally, various relevant factors are incorporated into the developed predictive model to elucidate specific causal relationships. It is anticipated that future research will lead to the development of a more accurate model for predicting the number of patients with periodontitis.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.11
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• pp.1079-1088
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• 2001

A dynamic simulation model was developed to analyse the transient characteristics of a multi-inverter heat pump. The programs included a basic air conditioning system such as a evaporator, condenser, compressor, linear electronic expansion valve (LEV) and by-pass circuit. The theoretical model was derived from mass conservation and energy conservation equations to predict the performance of the multi-inverter heat pump at various operating conditions. Calculated results were compared with the values obtained from the experiments at different operation frequencies of compressor, area of the LEV and configuration of indoor units operation. The results of the simulation model showed a good agreement with the experimental ones, so that the model could be used as an efficient tool for thermodynamic design and control factor design of air-conditioners.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.4
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• pp.97-103
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• 2012

This study investigates thermal insulation properties of multi layer materials depending on thickness of air layers. Numerical analysis on the heat flow of different insulating materials was conducted to identify whether their temperature distributions demonstrate the reduced rate of heat transfer conclusively or not. Analytical model is divided into two categories. One is to distinguish temperature distribution of the air-layer materials from the non-air layer ones. The other is to compare the efficacy between eight-layered insulating materials with no air-layer contained and three-layered insulating materials which include an air-layer definitely. In the latter case, the identical thickness is assigned to each material. The effect of thermal insulation by including an air-layer is verified in the first analytical model. The result of the second model shows that the insulation of the eight-layered materials is coterminous at the three-layered ones with an air-layer and the thermal insulation of the two materials is imperceptible. The benefits of cost and energy saving are anticipated if air-layers are efficiently incorporated in multi layer insulating materials in a greenhouse.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.1
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• pp.66-75
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• 2012

The purpose of this study is to analyze the effect of intervention variables which may affect the air travel demand for Jeju domestic flights and to anticipate the air travel demand for Jeju domestic flights. The air travel demand forecasts for Jeju domestic flights are conducted through ARIMA-Intervention Model selecting five intervention variables such as 2002 World Cup games, SARS, novel swine-origin influenza A, Yeonpyeongdo bombardment and Japan big earthquake. The result revealed that the risk factor such as the threat of war that is a negative intervention incident and occurred in Korea has the negative impact on the air travel demand due to the response of risk aversion by users. However, when local natural disasters (earthquakes, etc) occurring in neighboring courtiers and global outbreak of an epidemic gave the negligible impact to Korea, negative intervention incident would have a positive impact on air travel demand as a response to find alternative due to rational expectation of air travel customers. Also we realize that a mega-event such as the 2002 Korea-Japan World Cup games reduced the air travel demand in a short-term period unlike the perception in which it will increase the air travel demand and travel demands in the corresponding area.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.4
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• pp.512-518
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• 2000

A wall fuel-film flow model is developed to predict the effect of a wall-fuel-film on air-fuel ratio in an SI engine in transient conditions. Fuel redistribution in the intake port resulting from charge backflow and a simple liquid fuel behavior in the cylinder are included in this model. Liquid fuel film flow is calculated of every crank angle degree using the instantaneous air flow rate. The model is validated by comparing the calculated results and corresponding engine experiment results of a commercial 4 cylinder DOHC engine. The predicted results match well with the experimental results. To maintain the constant air-fuel ratio during transient operation. the fuel injection rate control can be obtained from the simulation result.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.2
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• pp.109-118
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• 2013

The absence of a simple and general analytical model has been a problem in the design and analysis of desiccant-assisted air-conditioning systems. In this study, such an analytical model has been developed based on the approximate integral solution of the coupled transient ordinary differential equations for the heat and mass transfer processes in a desiccant wheel. It turned out that the initial conditions should be determined by the solution of four linear algebraic equations including the heat and mass transfer equations for the air flow as well as the energy and mass conservation equations for the desiccant bed. It is also shown that time-averaged exit air temperature and humidity relations could be given in terms of the heat and mass transfer effectiveness.

• Corrosion Science and Technology
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• v.23 no.3
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• pp.228-234
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• 2024

Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.