• 설비공학논문집
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• 제7권2호
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• pp.276-286
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• 1995

In this study, pressure drop and heat transfer coefficients were measured in tubes with three dimensional roughness. Dimples were made by rotating the saw-tooth shaped finning disc on the outer tube surface. Resultant dimple shape was oval. Friction and heat transfer tests were performed with a range of roughness variables-roughness height 'e', axial roughness pitch 'p', circumferential roughness pitch 'z'. Within the test range, tube with e=0.5mm, z=5mm, p=3mm performed best. The efficiency ratio(rati of the heat transfer improvement and the pressure drop increase) of the tube approached 1.0 at low Reynolds number, and it was higher than that of the two-dimensional roughess tube of the same roughness height. Test data were predicted by 'discrete element method'. Results show that discrete element method underpredicts the friction data by 2% to 32%, and overpredicts the heat transfer data by-12% to 113%.

• 펄프종이기술
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• 제36권3호
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• pp.44-51
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• 2004

The effect of refining conditions and grammage on the stiffness of linerboard was investigated. The correlations between Taber stiffness and resonance stiffness were very low due to the different measuring principle. The refining conditions did not affect sig nificantly on both Taber and resonance stiffness estimated here. This means that it is strongly recommended to find and apply the refining conditions which can reduce specific energy consumption. Taber stiffness showed very high correlation for the thickness and elastic modulus of linerboard, while the resonance stiffness showed much lower correlation. Effective thicknesses for Taber stiffness were very well fitted with measured thickness, while those for resonance stiffness depended on the grammage of linerboard.

• 한국정밀공학회지
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• 제9권4호
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• pp.72-77
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• 1992

In this study, using in-process tool failure detecting system by AE method in turning machining, we measured AE signal from the tool, and the surface roughness of workpiece and then compared it with tool wear. As a result, we found that tool failure can be predicted by means of surface roughness of the workpiece and it can be predicted more precisely by the arithmetical average roughness (Ra) than by the maximum height of irregularities (Rmax) of the workpiece. Also, we found that we could judge whether it was sudden failure or the wear by means of the shape of AE signal and the range distri- bution of power spectrum frequency when tool danage was happened.