Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data
In this paper, the experimental data on the thermal conductivity of EG based hybrid nanofluid containing zinc oxide and titanium oxide have been used. At the first, three two-variable correlations have been proposed using curve-fitting on experimental data. After that, the best transfer function for...
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my.um.eprints.200012019-01-15T02:08:45Z http://eprints.um.edu.my/20001/ Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data Safaei, Mohammad Reza Hajizadeh, Ahmad Afrand, Masoud Qi, Cong Yarmand, Hooman Zulkifli, Nurin Wahidah Mohd Q Science (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering In this paper, the experimental data on the thermal conductivity of EG based hybrid nanofluid containing zinc oxide and titanium oxide have been used. At the first, three two-variable correlations have been proposed using curve-fitting on experimental data. After that, the best transfer function for training the artificial neural network has been selected. The input variables of neural network were temperature and solid volume fraction, while the output variable was the thermal conductivity enhancement of the nanofluid. Moreover, the correlation outputs, ANN results and experimental data have been compared. The results showed that there is a good agreement between experimental data and neural network results so that the resulting model of the neural network is able to predict the thermal conductivity enhancement of the nanofluid. The findings also indicated that the accuracy of the neural network is much greater than the curve fitting method to predict thermal conductivity enhancement of ZnO-TiO2/EG hybrid nanofluid. Elsevier 2019 Article PeerReviewed Safaei, Mohammad Reza and Hajizadeh, Ahmad and Afrand, Masoud and Qi, Cong and Yarmand, Hooman and Zulkifli, Nurin Wahidah Mohd (2019) Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data. Physica A: Statistical Mechanics and its Applications, 519. pp. 209-216. ISSN 0378-4371 https://doi.org/10.1016/j.physa.2018.12.010 doi:10.1016/j.physa.2018.12.010 |
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Q Science (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering Safaei, Mohammad Reza Hajizadeh, Ahmad Afrand, Masoud Qi, Cong Yarmand, Hooman Zulkifli, Nurin Wahidah Mohd Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data |
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In this paper, the experimental data on the thermal conductivity of EG based hybrid nanofluid containing zinc oxide and titanium oxide have been used. At the first, three two-variable correlations have been proposed using curve-fitting on experimental data. After that, the best transfer function for training the artificial neural network has been selected. The input variables of neural network were temperature and solid volume fraction, while the output variable was the thermal conductivity enhancement of the nanofluid. Moreover, the correlation outputs, ANN results and experimental data have been compared. The results showed that there is a good agreement between experimental data and neural network results so that the resulting model of the neural network is able to predict the thermal conductivity enhancement of the nanofluid. The findings also indicated that the accuracy of the neural network is much greater than the curve fitting method to predict thermal conductivity enhancement of ZnO-TiO2/EG hybrid nanofluid. |
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Article |
author |
Safaei, Mohammad Reza Hajizadeh, Ahmad Afrand, Masoud Qi, Cong Yarmand, Hooman Zulkifli, Nurin Wahidah Mohd |
author_facet |
Safaei, Mohammad Reza Hajizadeh, Ahmad Afrand, Masoud Qi, Cong Yarmand, Hooman Zulkifli, Nurin Wahidah Mohd |
author_sort |
Safaei, Mohammad Reza |
title |
Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data |
title_short |
Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data |
title_full |
Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data |
title_fullStr |
Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data |
title_full_unstemmed |
Evaluating the effect of temperature and concentration on the thermal conductivity of ZnO-TiO2/EG hybrid nanofluid using artificial neural network and curve fitting on experimental data |
title_sort |
evaluating the effect of temperature and concentration on the thermal conductivity of zno-tio2/eg hybrid nanofluid using artificial neural network and curve fitting on experimental data |
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Elsevier |
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2019 |
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http://eprints.um.edu.my/20001/ https://doi.org/10.1016/j.physa.2018.12.010 |
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1643691149534167040 |
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13.160551 |