Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network
In this paper, at first, a new correlation was proposed to predict the relative viscosity of MWCNTs-SiO2/AE40 nano-lubricant using experimental data. Then, considering minimum prediction error, an optimal artificial neural network was designed to predict the relative viscosity of the nano-lubricant....
| Main Authors: | , , , , , , |
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| Format: | Article |
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Elsevier
2016
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| _version_ | 1825721046337060864 |
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| author | Afrand, M. Nazari Najafabadi, K. Sina, N. Safaei, M.R. Kherbeet, A.Sh. Wongwises, S. Dahari, M. |
| author_facet | Afrand, M. Nazari Najafabadi, K. Sina, N. Safaei, M.R. Kherbeet, A.Sh. Wongwises, S. Dahari, M. |
| author_sort | Afrand, M. |
| collection | UM |
| description | In this paper, at first, a new correlation was proposed to predict the relative viscosity of MWCNTs-SiO2/AE40 nano-lubricant using experimental data. Then, considering minimum prediction error, an optimal artificial neural network was designed to predict the relative viscosity of the nano-lubricant. Forty-eight experimental data were used to feed the model. The data set was derived to training, validation and test sets which contained 70%, 15% and 15% of data points, respectively. The correlation outputs showed that there is a deviation margin of 4%. The results obtained from optimal artificial neural network presented a deviation margin of 1.5%. It can be found from comparisons that the optimal artificial neural network model is more accurate compared to empirical correlation. |
| first_indexed | 2024-03-06T05:44:23Z |
| format | Article |
| id | um.eprints-18078 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:44:23Z |
| publishDate | 2016 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | um.eprints-180782017-10-24T02:24:58Z http://eprints.um.edu.my/18078/ Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network Afrand, M. Nazari Najafabadi, K. Sina, N. Safaei, M.R. Kherbeet, A.Sh. Wongwises, S. Dahari, M. TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering In this paper, at first, a new correlation was proposed to predict the relative viscosity of MWCNTs-SiO2/AE40 nano-lubricant using experimental data. Then, considering minimum prediction error, an optimal artificial neural network was designed to predict the relative viscosity of the nano-lubricant. Forty-eight experimental data were used to feed the model. The data set was derived to training, validation and test sets which contained 70%, 15% and 15% of data points, respectively. The correlation outputs showed that there is a deviation margin of 4%. The results obtained from optimal artificial neural network presented a deviation margin of 1.5%. It can be found from comparisons that the optimal artificial neural network model is more accurate compared to empirical correlation. Elsevier 2016 Article PeerReviewed Afrand, M. and Nazari Najafabadi, K. and Sina, N. and Safaei, M.R. and Kherbeet, A.Sh. and Wongwises, S. and Dahari, M. (2016) Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network. International Communications in Heat and Mass Transfer, 76. pp. 209-214. ISSN 0735-1933, DOI https://doi.org/10.1016/j.icheatmasstransfer.2016.05.023 <https://doi.org/10.1016/j.icheatmasstransfer.2016.05.023>. http://dx.doi.org/10.1016/j.icheatmasstransfer.2016.05.023 doi:10.1016/j.icheatmasstransfer.2016.05.023 |
| spellingShingle | TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering Afrand, M. Nazari Najafabadi, K. Sina, N. Safaei, M.R. Kherbeet, A.Sh. Wongwises, S. Dahari, M. Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network |
| title | Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network |
| title_full | Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network |
| title_fullStr | Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network |
| title_full_unstemmed | Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network |
| title_short | Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network |
| title_sort | prediction of dynamic viscosity of a hybrid nano lubricant by an optimal artificial neural network |
| topic | TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering |
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