• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.1
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• pp.160-169
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• 2000

Daily indoor and outdoor nitrogen dioxide ($NO_2$) concentration for 30 days were measured in 28 houses with questionnaire of housing characteristics in Brisbane, Australia. Using mass balance equation and regression analysis, penetration factors and source strength factors were calculated. The penetration factors of 27 houses except one house were between zero and 1, though penetration factor should be between zero and 1 by means of mass balance equation. Relationship between indoor and outdoor concentrations in each 27 house was calculated using regression analysis. According to the obtained linear regression equation, the slope means penetration factor and the intercept means source strength factor. Calculated mean and standard deviation of coefficients of determination ($R^2$) in electric and gas range houses were $0.70{\pm}0.13$ and $0.57{\pm}0.21$, respectively. The source strength factors were more than zero in 27 houses. Mean and standard deviation of slopes in electric and gas range houses were $0.65{\pm}0.18$ and $0.56{\pm}0.12$, respectively. Mean and standard deviation of intercepts in electric and gas range houses were $1.49{\pm}1.25$ and $5.77{\pm}3.55$, respectively. Air exchange rate and source strength were calculated from penetration factor and source strength factor, respectively. Geometric mean and standard deviation of calculated air exchange rates in 27 houses were $1.1/hr{\pm}1.5$. Presence of gas range was the most significant factor contributing to indoor $NO_2$ level in house characteristics (p=0.003). In gas range houses, source strengths ranged from 4.1 to $33.1cm^3/hr{\cdot}m^3$ with a mean $12.7cm^3/hr{\cdot}m^3$ and a standard deviation 9.8. The source strengths of gas range houses were significantly different from those of electric range houses by t-test (p<0.001)

• Nuclear Engineering and Technology
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• v.37 no.6
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• pp.595-604
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• 2005

A new instrument, an average BDFT (Birectional Flow Tube), was proposed to measure the flow rate in single and two phase flows. Its working principle is similar to that of the Pilot tube, wherein the dynamic pressure is measured. In an average BDFT, the pressure measured at the front of the flow tube is equal to the total pressure, while that measured at the rear tube is slightly less than the static pressure of the flow field due to the suction effect downstream. The proposed instrument was tested in air/water vertical and horizontal test sections with an inner diameter of 0.08m. The tests were performed primarily in single phase water and air flow conditions to obtain the amplification factor(k) of the flow tube in the vertical and horizontal test sections. Tests were also performed in air/water vertical two phase flow conditions in which the flow regimes were bubbly, slug, and churn turbulent flows. In order to calculate the phasic mass flow rates from the measured differential pressure, the Chexal drift-flux correlation and a momentum exchange factor between the two phases were introduced. The test results show that the proposed instrument with a combination of the measured void fraction, Chexal drift-flux correlation, and Bosio & Malnes' momentum exchange model could predict the phasic mass flow rates within a $15\%$ error. A new momentum exchange model was also proposed from the present data and its implementation provides a $5\%$ improvement to the measured mass flow rate when compared to that with the Bosio & Malnes' model.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.12
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• pp.1007-1017
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• 2003

An experimental study on the air-side pressure drop and heat transfer coefficient of slit fin-tube heat exchanger has been carried out. The data reduction methodology for air-side heat transfer coefficients in the literature is not based on a consistent approach. This paper focuses on new method of data reduction to obtain the air-side performance of fin-tube heat exchanger using R22 and recommends standard procedures for dry and wet surface heat transfer estimation in fin-tube heat exchanger having refrigerant on the tube-side. Results are presented as plots of friction f-factor and Colburn j -factor against Reynolds number based on the fin collar outside diameter and compared with previous studies. The data covers a range of refrigerant mass fluxes of 150∼250 kg/$m^2$s with air flows at velocity ranges from 0.3 m/s to 0.8 m/s.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.3
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• pp.220-229
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• 2003

An experimental study on the air-side pressure drop and heat transfer coefficient of slit fin-tube heat exchanger has been carried out. The data reduction methodology for air-side heat transfer coefficients in the literature is not based on a consistent approach. This paper focuses on new method of data reduction to obtain the air-side performance of fin-tube heat exchanger using R22 and recommends standard procedures for dry surface heat transfer estimation in fin-tube heat exchanger having refrigerant on the tube-side. Results are presented as plots of friction f-factor and Colburn j -factor against Reynolds number based on the fin collar outside diameter and compared with previous studies. The data covers a range of refrigerant mass fluxes of 150~250 kg/$m^2$s with air flows at velocity ranges from 0.6 m/s to 1.6 m/s.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.277-282
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• 2006

In order to predict the indoor air pollutant, the VOCs emission rate is used through small chamber in the design process. However, the small chamber method has limitations as the convective mass transfer coefficient, the most important factor when predicting VOCs contamination of indoor air, is different between the small chamber result and the measured data in the actual building. Furthermore, the existing studies which analyzed mass transfer coefficient in the small chamber were directed on the small chambers developed at the time and FLEC(Field and Laboratory Emission Cell), thus, are different from the current small chamber which has been changed with improvements. The purpose of this study is to determine the emission rate of pollutant in double-layered building materials through the CFD(Computational of Fluid Dynamics) and Numerical analysis based on the mass transfer coefficient on singled-layered building material by using the current small chamber widely used in Korea. Futhermore, this study used the new convective mass transfer coefficient($h_m'$) which indicates the existing convective mass transfer coefficient($h_m$) including VOC partition coefficient(k). Also, formaldehyde was selected as target pollutant.

• Journal of Environmental Science International
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• v.2 no.3
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• pp.161-177
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• 1993

The Yellow Sand Events observed over the Korean peninsula during 22-24 April, 1993 were examined using the synoptic data and GMS visible image to identify the transport path of the Yellow Sand and the main factor governing the duration of the Yellow Sand phenomenon. The 850 hPa convergence chart and the 700 hPa trajectory analyses of the air mass laden with Yellow Sand particles suggested that the Yellow Sand particles observed over Korea were probably transported from the Gobi Desert and the Loess Plateau. The duration of the Yellow Sand Events was about 35-40 hours rather shorter than normal as the high pressure system centered near the Mongolia region moved rapidly toward the Yellow Sea, which drove away the Yellow Sand particles over the Korean peninsula toward the Japan Islands, furthermore the low-level stratification of the air mass over the Korean penishula showed the unstable atmospheric condition leading to atmospheric diffusion of the particles. The trajectory analyses and the GMS visible image indicated that the long-range transport of the air mass laden with the Yellow Sand particles of this case was more dependent on the 700 hPa air flow than on the 850 hPa air flow.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.136-138
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• 2000

The vehicle emissions of primary air pollutants are described by the emission factor (EF), defined as the emitted mass (g) of a compound per distance (km) and vehicle. The EF can be determined by exhaust measurements from single vehicles in dynamometric tests. However, the EF of a large number of vehicles has to be measured to obtain the representative results for actual road traffic emissions. Road traffic emissions can also be determined by exhaust measurements of driving vehicles or in tunnel measurements. (omitted)

• Journal of Environmental Science International
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• v.15 no.10
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• pp.913-918
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• 2006

Despite the wide distribution of air pollutants, the concentrations of indoor air pollutants may be the dominant risk factor in personal exposure due to the fact that most people spend an average of 80% of their time in enclosed buildings. Researches for improvement of indoor air quality have been developed such as installation of air cleaning device, ventilation system, titanium dioxide$(TiO_2)$ coating and so on. However, it is difficult to evaluate the magnitude of improvement of indoor air quality in field study because indoor air quality can be affected by source generation, outdoor air level, ventilation, decay by reaction, temperature, humidity, mixing condition and so on. In this study, evaluation of reduction of formaldehyde and nitrogen dioxide emission rate in indoor environments by $TiO_2$ coating material was carried out using mass balance model in indoor environment. we proposed the evaluation method of magnitude of improvement in indoor air quality, considering outdoor level and ventilation. Since simple indoor concentration measurements could not properly evaluate the indoor air quality, outdoor level and ventilation should be considered when evaluate the indoor net quality.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.8
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• pp.730-738
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• 2001

This work discusses the pressure droop, heat and mass transfer of the finned-tube heat exchangers having 7 mm tubes and offset strips in dehumidifying applications. It focuses on the fin material saving and the reduction of pressure drop. The experiment was conducted using three times scaled-up models to simulate the performance of the prototype. Eight kinds of fins having different strips and S shape edges were tested. the area density of the strip was a major factor and its shape and the location were secondary factors on the pressure drop, the heat and mass transfer. The reduced-area fin can almost equal the non-reduced fin in the aspect of heat and mass transfer. The strip fins proposed in the present work can considerably reduce both the pressure drop and the fin material for similar thermal load.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.681-693
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• 1995

A new set of capillary tube selection charts for R-22 is proposed. The set of charts takes into account of the roughness effect on the mass flow rate. For this purpose, a set of numerical model is developed and a series of experiments is conducted to verify the numerical model. A numerical model is used to calculated the mass flow rate for several sets of tube diameter, length, inlet pressures and degree of subcooling. The outlet of the tube is controlled to be at critical condition. The experimental flow rate is compared with calculated values. The calculated values are consistently less than the experimental ones except for the flow rate range below 40kg/hr. The deviation is within 10---. Based on the nunmerical model and results of experiments, the set of capillary tube selection charts for R-22 is constructed. The set of charts consists of standard capillary tube chart(L=2030mm, d=1.63mm, ${\varepsilon}=2.5{\mu}m$), non -standard flow factor(${\phi}_1$) chart, and non-standard roughness factor(${\phi}_2$) chart. The mass flow rate, flow factor, and the roughness factor are defined respectively as; $\dot{m}={\phi}_1{\phi}_2\dot{m}_{standard}\\{\phi}_1=\frac{\dot{m}(L,\;d,\;\varepsilon_{standard})}{\dot{m}_{standard}(L_{standard},\;d_{standard},\;{\varepsilon}_{standard})}\\{\phi}_2=\frac{\dot{m}(L_{standard},\;d_{standard},\;{\varepsilon})}{\dot{m}_{standard}(L_{standard},\;d_{standard},\;{\varepsilon}_{standard})}$.