Heat transfer coefficients in two-phase flow for mixtures used in solar absorption refrigeration systems

As an excellent cryogenic cooling medium, Nitrogen (N2) has been used in a variety of engineering fields, where the determination of N2 two-phase flow boiling heat transfer is required. There were some studies evaluating the correlations of flow boiling heat transfer coefficient for N2. However, either the number of correlations covered or the number of data used was limited. This work presents a comparative review of existing correlations of flow boiling heat transfer coefficients for N2 applications. A database of N2 flow boiling heat transfer containing 1043 experimental data points is compiled to evaluate 45 correlations of two-phase flow boiling heat transfer. The experimental parameters cover the ranges of mass flux from 28.0 to 1684.8 kg/m2s, heat flux from 0.2 to 135.6 kW/m2, vapor quality from 0.002 to 0.994, saturation pressure from 0.1 to 3.16 MPa, and channel inner diameter from 0.351 to 14 mm. The results show that the best correlation has a mean absolute deviation of 31.8% against the whole database, suggesting that more efforts should be made to study N2 flow boiling heat transfer to develop a more accurate correlation.

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Correlation for Predicting Two-Phase Flow Boiling Heat Transfer Coefficients for Refrigerant HFO-1234yf

10.4271/2018-01-0055 ◽

2018 ◽

Cited By ~ 1

Author(s):

Gursaran D. Mathur

Keyword(s):

Heat Transfer ◽

Boiling Heat Transfer ◽

Two Phase Flow ◽

Flow Boiling ◽

Phase Flow ◽

Transfer Coefficients ◽

Two Phase ◽

Heat Transfer Coefficients ◽

Flow Boiling Heat Transfer

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Two Phase Flow Patterns and Boiling Heat Transfer in Tubes Containing Helical Wire Inserts--Part I --Flow Patterns and Boiling Heat Transfer Coefficients

Journal of Enhanced Heat Transfer ◽

10.1615/jenhheattransf.v4.i4.30 ◽

1997 ◽

Vol 4 (4) ◽

pp. 269-281 ◽

Cited By ~ 3

Author(s):

J. Lan ◽

Peter J. Disimile ◽

J. Weisman

Keyword(s):

Heat Transfer ◽

Boiling Heat Transfer ◽

Two Phase Flow ◽

Flow Patterns ◽

Phase Flow ◽

Transfer Coefficients ◽

Two Phase ◽

Heat Transfer Coefficients

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Prediction of Two-Phase Heat Transfer Coefficients in a Horizontal Pipe for Different Inclined Positions With Artificial Neural Networks

Journal of Heat Transfer ◽

10.1115/1.4029865 ◽

2015 ◽

Vol 137 (6) ◽

Cited By ~ 6

Author(s):

Najmeh Sobhanifar ◽

Ebrahim Ahmadloo ◽

Sadreddin Azizi

Keyword(s):

Neural Network ◽

Heat Transfer ◽

Experimental Data ◽

Neural Networks ◽

Two Phase Flow ◽

Reynolds Numbers ◽

Phase Flow ◽

Transfer Coefficients ◽

Two Phase ◽

Heat Transfer Coefficients

This paper presents the application of artificial neural network (ANN) in prediction of heat transfer coefficients (HTCs) of two-phase flow of air–water in a pipe in the horizontal and slightly upward inclined (2, 5, and 7 deg) positions. For this purpose, the superficial liquid and gas Reynolds numbers and the inclination of the pipe were used as input parameters, while the HTCs of two-phase flow were used as output parameters in training and testing of the multilayered, feedforward, backpropagation neural networks. In this present study, experimental data were taken from literature and then used for the ANN model. The superficial liquid and gas Reynolds numbers ranged from 740 to 26,100 and 560 to 47,600 for water and air, respectively. The mean deviations against experimental data were determined for the model. Results showed that the network predictions were in very good agreement with the experimental HTC data, whereas the correlation showed more deviations. Finally, results showed that the accuracy between the neural network predictions and experimental data was achieved with mean relative error (MRE) of 2.92% and correlation coefficient (R) that was 0.997 for all datasets, which suggests the reliability of the ANNs as a strong tool for predicting HTCs with two-phase flows.

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