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Condensation in Horizontal Smooth Tubes: A New Heat Transfer Model for Heat Exchanger Design
This paper proposes a new method to determine the condensation heat transfer coefficient of fluids flowing into horizontal smooth tubes with internal diameters D > 3 mm. The method has been drawn up as simply as possible and is ready to use in heat exchanger modeling and design applications. It i...
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Published in: | Heat transfer engineering 2006-09, Vol.27 (8), p.31-38 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper proposes a new method to determine the condensation heat transfer coefficient of fluids flowing into horizontal smooth tubes with internal diameters D > 3 mm. The method has been drawn up as simply as possible and is ready to use in heat exchanger modeling and design applications. It is also suitable to work very well with old and new fluids used in the refrigeration, air conditioning, and heat pump industries. Particular attention is given to accuracy: it has been tested over a wide updated experimental database and comes from many different independent researchers with reduced experimental uncertainties. In order to obtain an easy structure, only two equations are employed, related respectively to & Delta; T-independent and to & Delta; T-dependent fluid flows. All the parameters that influence the condensation heat transfer have been included.
A comparison has been conducted against HCFCs, HFCs, HCs, carbon dioxide, ammonia, and water data. Zeotropic mixtures with two and three components are also considered in the comparison by applying the Bell and Ghaly [
1
] correction to calculate the relative heat transfer penalization. A model has been developed with the idea of getting high accuracy through an easy structure, and the results show a very satisfactory agreement with experimental data: average deviation e
R
= +2%, absolute mean deviation e
AB
= 14%, and standard deviation σ
N
= 19% for the total number of 5478 data points. |
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ISSN: | 0145-7632 1521-0537 |
DOI: | 10.1080/01457630600793970 |