Summary
A theoretical model of CO2 gas cooler with PAG lubricant was developed. The heat transfer coefficient was predicted based on artificial neural network, and then the model was validated with experimental results. Further calculation shows that the thermal effectiveness increases with the length of the gas cooler tube, but the increase rate decreases gradually. Therefore, the length of the gas cooler tube should be properly designed considering the economical running in the practical applications.For the gas cooler with a smaller diameter (Dh = 2 mm), a small amount of lubricant significantly deteriorates the thermal effectiveness while for that with a larger diameter (Dh= 4 mm), the influence is not so apparent. Consequently, the oil concentration should be decreased as far as possible to keep high heat transfer performance of the small diameter gas cooler. The gas cooler performances better at higher CO2 side pressure.However, the increase rate of the thermal effectiveness decrease gradually as the pressure increases. At pressure approaching to the critical pressure, the degradation of the thermal effectiveness is more significant. Additionally, the deterioration is more apparent as the diameter decreases.
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Details
- Original title: [In Chinese. / En chinois.]
- Record ID : 30020633
- Languages: Chinese
- Source: Journal of Refrigeration - vol. 35 - n. 160
- Publication date: 2014/12
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Indexing
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Themes:
Heat transfer;
CO2;
Lubricants - Keywords: Lubricant; Heat transfer; Artificial neural network; Gas cooler; Performance; Modelling; CO2
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Simulation of heat exchanger performance by art...
- Author(s) : DIAZ G., YANG K. T., SEN M., MCCLAIN R. L.
- Date : 1999/07
- Languages : English
- Source: HVAC&R Research - vol. 5 - n. 3
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Prediction of cooling heat transfer coefficient...
- Author(s) : DANG C., HIHARA E.
- Date : 2008/07/14
- Languages : English
- Source: 2008 Purdue Conferences. 19th International Compressor Engineering Conference at Purdue & 12th International Refrigeration and Air-Conditioning Conference at Purdue [CD-ROM].
- Formats : PDF
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Predicting the cooling heat transfer coefficien...
- Author(s) : DANG C., HIHARA E.
- Date : 2012/06
- Languages : English
- Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 35 - n. 4
- Formats : PDF
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Neural network-based prediction of the oscillat...
- Author(s) : FICHERA A., PAGANO A.
- Date : 2002/08
- Languages : English
- Source: International Journal of Heat and Mass Transfer - vol. 45 - n. 18
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Predictions of heat transfer coefficients of su...
- Author(s) : CHEN J., WANG K. P., LIANG M. T.
- Date : 2005/05
- Languages : English
- Source: International Journal of Heat and Mass Transfer - vol. 48 - n. 12
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