Korean Journal of Air-Conditioning and Refrigeration Engineering
/
v.18
no.11
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pp.906-914
/
2006
The present paper dealt with an experimental study of boiling heat transfer characteristics of R-290. Pressure gradient and heat transfer coefficient of the refrigerant flow inside horizontal smooth minichannel were obtained with inner tube diameter of 3.0 mm and length of 2,000 mm. The direct electric heating method was applied for supplying a heat to the refrigerant uniformly. The experiments were conducted with R-290 purity of 99.99%, at saturation temperature of 0 to $10^{\circ}C$, a mass flux range of $50{\sim}250kg/m^2s$, and a heat flux range of $5{\sim}20kW/m^2$. The heat transfer coefficients of R-290 increased with increasing mass flux and saturation temperature, wherein the effect of mass flux was higher than that of the saturation temperature. Heat flux has a low effect on the increasing of heat transfer coefficient. The heat transfer coefficient was compared with six existing heat transfer coefficient correlations. The Zhang et al.'s correlation (2004) gave the best prediction of heat transfer coefficient. A new correlation to predict the two-phase flow heat transfer coefficient was developed based on the Chen correlation. The new correlation predicted the experimental data well with a mean deviation of 11.78% and average deviation of -0.07%.
Park, So Hee;Nam, Yoonho;Choi, Hyun Seok;Woo, Seung Tae
Investigative Magnetic Resonance Imaging
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v.21
no.3
/
pp.171-176
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2017
Purpose: To compare different MR sequences for quantification of gadolinium concentration. Materials and Methods: Gadolinium contrast agents were diluted into 36 different concentrations. They were scanned using gradient echo (GRE) and ultrashort echo time (UTE) and R1, $R2^*$ and phase values were estimated from collected data. For analysis, ROI masks were made for each concentration and then ROI value was measured by mean and standard deviation from the estimated quantitative maps. Correlation analysis was performed and correlation coefficient was calculated. Results: Using GRE sequence, R1 showed a strong linear correlation at concentrations of 10 mM or less, and $R2^*$ showed a strong linear correlation between 10 to 100 mM. The phase of GRE generally exhibited a negative linear relationship for concentrations of 100 mM or less. In the case of UTE, the phase had a strong negative linear relationship at concentrations 100 mM or above. Conclusion: R1, which was calculated by conventional GRE, showed a high performance of quantification for lower concentrations, with a correlation coefficient of 0.966 (10 mM or less). $R2^*$ showed stronger potential for higher concentrations with a correlation coefficient of 0.984 (10 to 100 mM), and UTE phase showed potential for even higher concentrations with a correlation coefficient of 0.992 (100 mM or above).
This study was conducted to find out the coefficient relationships between intensity values image processing and pollution density of slurries. Slurry images were obtained from the image processing system using personnel computer and CCD-camera. Software, written in Visual $c^{++}$, combined the functions of the image capture, image processing and image analysis. The data of image processing for slurries were analyzed by the method of regression analysis. The results are as follows. 1. Red(R)-values among image processing data were obtained the highest correlation coefficient 0.9213 for detecting COD. Also, green(G)-value were obtained the highest correlation coefficient 0.9019 fur detecting BOD. Blue(B)-value could not find significant values to detect the pollution resources density. 2. Hue(H)-values among image processing data were obtained the highest correlation coefficient 0.9466 for detecting BOD. This fact could be used in detecting BOD 3. Green(G)-value, GRAY-value, Hue(H)-value, Saturation(5)-value and Intensity(I)-value were the correlation coefficient more than 0.8 for BOD. Hue(H)-value was higher correlation coefficient than any other value. It was possible to detect pollution density of slurries by using the image processing system. 4. Red(R)-value, GRAY-value and Saturation(5)-value were obtained the correlation coefficient more than 0.8 for detecting COD. a-value had the highest correlation coefficient Among these values. It was possible to detect density indirectly by using the image processing system. 5. SS-density were obtained the correlation coefficient less than 0.8 by using the image processing system. The density of $NH_4$-N and $NO_3$-N were obtained correlation coefficient less than 0.2.
Relationships between red ceil volume $(^{51}Cr-cell)$, total blood volume (red cell volume divided by hematocrit ratio), and extracellular fluid volume (SCN distribution space) and body weight (ranging between 73 and 384 grams) or lean body mass were studied in 59 nembutalized rats. Lean body mass was determined by means of underwater weighing method on rats clipped and eviscerated. There were positive correlations between body weight or lean body mass and the absolute values (in milliliters) of body fluid volumes. Body fluid volumes expressed on the body weight or lean body mass basis, however, showed negative correlations between body weight (grams) or lean body weight (grams) with one exception. Red cell volume expressed as % lean body mass showed a positive correlation with lean body mass. The other results are summarized as follows: 1. Body density of rats was 1.0561 $(range:\;1.0123{\sim}1.0781)$ and 19.8% body weight of total body fat was obtained. The mean value of lean body mass was 80.2% body weight 2. The correlation between body weight and lean body mass was high, namely, coefficient of correlation was r=.99. 3. The correlation between the absolute value of red cell volume (ml) and body weight showed a high correlation, namely, r= 92 and between the lean body mass coefficient of correlation was r=.93. On a weight basis, red cell volume was 2.67 ml/100 gm body weight or 3.48 ml/100 gm lean body mass. The coefficient of correlation between body weight (grams) and red cell volume (% body weight) was r=-. 30. The coefficient of correlation between lean body mass (grams) and red cell volume (% lean body mass) was r=. 50. Thus, the following regression equation was obtained. Red cell volume (% lean body mass)=. 00243 Lean body mass (gm)+3. 12. 4. Total blood volume was 6.06% body weight or 7.83% lean body mass. The correlation between these blood volume values and body weight or lean body mass were negative, namely, r= -.43 and r=-.42 respectively. 5. Extracellular volume (SCN space) was 30.0% body weight or 37.2% lean body mass. These percentage values showed negative correlations between body weight or lean body mass and coefficients of correlation were r=-.40 and r=-.54 respectively. 6. The rate of increase in body weight or lean body mass is accompanied by a smaller rate of increase in blood volume and extracellular fluid volume. The rate of increase in red ceil volume paralled that of lean body mass.
Laboratory methods commonly used today are biochemical oxygen demand, chemical oxygen demand, and total organic carbon. Establishment of constant relationships among the various measures of organic content depends primarily on the nature of the wastewater and its source. Of all the measures, the most difficult to correlate to the others is the BODs test, because of the problems associated with biological tests. The results were summarized as follwos, 1. For typical municipal wastes, however, the SBOD$_{5}$/SCOD$_{cr}$ ratio varies from 0.14 to 0.34(mean 0.21), SBOD$_{5}$/STOC ratio varies from 0.35 to 1.19(mean 0.69) 2. Correlation analysis between the SBOD$_{5}$ and SCOD$_{cr}$ gave good correlation coefficient r = 0.903 and the equation Y = 3.756X + 16,221 was obtained. 3. The correlation between the SBOD$_{5}$ and STOC was well presented with equation : Y = 1,070X + 7,637, and also correlation coefficient r = 0.821 4. The correlation between the SCOD$_{cr}$ and STOC was well presented with equation : Y = 0.256X +5.513 and also correlation coefficient r = 0.816. 5. Because of the rapidity with which the TOC test can be conducted, it is anticipated that more use will be made of these tests in the future.
The purpose of this study was to develop a simple, valid, and reliable instrument for measuring forward flexion of trunk-hip joint. The subject included 44 females for sports major of volunteers at D. Women's University. In establishing the validity, objectivity the reliability of the new flexibility test(NF-test) for trunk-hip joint, Takei- flexometer(modified Leighton flexometer) was administered as the reference instrument, and test-retest method was utilized with the best scores. Intraclass correlation coefficient was obtained to use two way-mixed effect model and this value was average measure. The Pearson product correlation coefficient of L in this study were; the new flexibility test and Takei-flexometer as the reference tool correlated r = .962 in the first test, r = .960 in the second test. The intraclass correlation coefficient of the new flexibility test between in the initial test and in the retest were R = .994 for L, R =.993 for Y, and the intraclass correlation coefficient of the new flexibility test between L and Y were R =.985 in the initial test, and R =.986 in the retest. Based on the above findings, the following conclusions are presented. It was found the new flexibility test (NF test) was a valid, reliable, objective tool for measuring forward flexion of trunk-hip joint, and possible to be recommended as he test for measuring trunk-hip flexibility in the field.
Sanitary condition for raw milk in Korea was investigated in this study. It is hoped that the information will be used for reference in future endeavors of study in the field of public health and food sanitation in Korea. The results were summerized as follows: 1) The viable cell counts of bacteria in raw milk were tend to be increased under the various atmospheric temperature, and the correlation coefficient between temperature and total viable cells was r=+0.921(p<0.01). 2) The correlation coefficient between methylene blue reduction time test and viable cell counts of bacteria in raw milk was r=-0.799(p<0.01). 3) The relationship between total solid rate(%) and milk fat rate(%) was highly significant level as r=+0.745(p<0.01). 4) Highly significant correlation coefficient was r= +0.945(p<0.01) between milk fat and protein rate in raw milk.
Two-phase flow boiling heat transfer of R-410A in horizontal small tubes was reported in the present experimental study. The local heat transfer coefficients were obtained over a heat flux range of 5 to 40 kW/$m^2$, a mass flux range of 170 to 600 kg/$m^2s$, a saturation temperature range of 3 to $10^{\circ}C$, and quality up to 1.0. The test section was made of stainless steel tubes with inner diameters of 0.5 and 3.0 mm, and lengths of 330 and 3000 mm, respectively. The section was heated uniformly by applying a direct electric current to the tubes. The effects on heat transfer of mass flux, heat flux, inner tube diameter, and saturation temperature were presented. The experimental heat transfer coefficient is compared with six existing heat transfer coefficient correlations. A new boiling heat transfer coefficient correlation based on the superposition model for R-410A in small tubes was developed with mean deviation of 10.13%.
This study is an attempt to investigate the chemical components of precipitation and its variation according to surface wind. Precipitation samples were collected by an wet-only precipitation sampler during the period of October 1994 to September 1995 at Kyungsan in Korea. The results obtained in t체s study are summerized as follows. The annual average of precipitation pH is 5.0, the highest month of pH is July of 5.5, and the lowest month of pH is December of 4.4. The most frequent appearance is in the range of pH 5.0 to 5.5 and its rate is 56.8%, The order of ion concentration In precipitation is SO42->NO3->Cl- in case of anion and $Ca^{2+}$>$NH_4^{+}$>$Na^+$>$Mg^{2+}$ in case of cation. It is found from our analysis that the correlation coefficient among the precipitation pH and ion components is below r=0.3, while the correlation coefficient between $SO_4^{2-}$ and NO_3^{-}$, $Na^+$ and $Cl^+$ is above r=0.8, respectively. The mean pH of precipitation is 4.8 under the westerly wind and 5.2 under the easterly wind. The concentrations of anion and cation under the westerly wind are more than the concentrations under the easterly wind. In autumn, the concentration of Na+ and $Cl^+$ under the easterly wind are higher than the concentration under the westerly wind. The correlation coefficients between wind speed and pH, ion components show very low correlation of -0.41 r 0.2. But the present study show that the correlation coefficient between wind speed and pH of precipitation is positive and the correlation coefficients between wind speed and ion concentration is negative.
To estimate nondestructively strength performances of laminated woods, 3-ply parallel- and cross-laminated wood specimens exposed under atmosphere conditions after bending creep test were prepared for this study. The effects of density of species, arrangement of laminae and lamination types on dynamic MOE obtained by flexural vibration were investigated, and regression analyses were conducted in order to estimate static bending strength and bending creep performances. Dynamic MOE of parallel-laminated woods showed 1.0~1.2 times higher values than static bending MOE, and those of cross-laminated woods showed 1.0~1.4 times higher values than static bending MOE. The degree of anisotropy of dynamic MOE perpendicular to the grain of face laminae versus that parallel to the grain of face laminae was markedly decreased by cross-laminating. There were strong correlations between dynamic MOE by flexural vibration and static bending MOE (correlation coefficient r = 0.919~0.972) or bending MOR (correlation coefficient r = 0.811~0.947) of 3-ply laminated woods, and the correlation coefficient were higher in parallel-laminated woods than in cross-laminated woods. It indicated that static bending strength performances were able to be estimated from dynamic MOE by flexural vibration. Also, close correlations between the reciprocal of dynamic MOE by flexural vibration and initial compliance at 0.008 h of 3-ply laminated woods were found (correlation coefficient r = 0.873~0.991). However, the correlation coefficient between the reciprocal of dynamic MOE and creep compliance at 168 h of 3-ply laminated woods was considerably lower than those between dynamic MOE and initial compliance, and it was hard to estimate creep compliance with a high accuracy from dynamic MOE due to the variation of creep deformation.
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