Heat Transfer-Asian Research, Volume (42), No (7), Year (2013-10) , Pages (630-650)

Title : ( Effects of a Nanofluid and Magnetic Field on the Thermal Efficiency of a Two-Phase Closed Thermosyphon )

Authors: , Saeed Zeinali Heris , Fateme Sharifi , Mohammad Amin Razbani ,

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Heat transfer of a CuO/water nanofluid in a two-phase closed thermosyphon (TPCT) that is thermally enhanced by a magnetic field has been predicted by an optimized artificial neural network (ANN). The magnetic field strength, volume fraction of nanoparticles in water, and inlet power were used as input parameters and the thermal efficiency was used as the output parameters. The correlation coefficient (R2 = 0.924), mean square error (MSE = 0.000340231), mean absolute error (MAE = 0.012410941), and normalized mean-squared error (NMSE = 0.112417498) between the measured and predicted thermal efficiency by the ANN model were developed. The results were compared with experimental data and it was found that the thermal efficiency estimated by the multi-layer perception neural network is accurate. In this study, a new approach for the auto-design of neural networks, based on a genetic algorithm, has been used to predict collection output of a TPCT.

Keywords

TPCT; CuO/water nanofluid; magnetic field; artificial neural network (ANN); thermal
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@article{paperid:1037000,
author = {, and Zeinali Heris, Saeed and Fateme Sharifi and Razbani, Mohammad Amin},
title = {Effects of a Nanofluid and Magnetic Field on the Thermal Efficiency of a Two-Phase Closed Thermosyphon},
journal = {Heat Transfer-Asian Research},
year = {2013},
volume = {42},
number = {7},
month = {October},
issn = {1099-2871},
pages = {630--650},
numpages = {20},
keywords = {TPCT; CuO/water nanofluid; magnetic field; artificial neural network (ANN); thermal efficiency},
}

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%0 Journal Article
%T Effects of a Nanofluid and Magnetic Field on the Thermal Efficiency of a Two-Phase Closed Thermosyphon
%A ,
%A Zeinali Heris, Saeed
%A Fateme Sharifi
%A Razbani, Mohammad Amin
%J Heat Transfer-Asian Research
%@ 1099-2871
%D 2013

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