Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networks
The present study aims to experimentally investigate the Nusselt number and friction factor in a double-pipe heat exchanger equipped with wire coils and aluminum oxide nanofluid, with a particle size of approximately 55 nm, in Reynolds numbers from 4000 to 14000, volume fractions of 0.02, 0.04, and...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-07-01
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| Series: | Case Studies in Thermal Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25004927 |
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| author | Roohallah Karimpooremam Fatemeh poursaied Bahram Keyvani Milad Razmi Reza Aghayari Davood Toghraie Soheil Salahshour |
| author_facet | Roohallah Karimpooremam Fatemeh poursaied Bahram Keyvani Milad Razmi Reza Aghayari Davood Toghraie Soheil Salahshour |
| author_sort | Roohallah Karimpooremam |
| collection | DOAJ |
| description | The present study aims to experimentally investigate the Nusselt number and friction factor in a double-pipe heat exchanger equipped with wire coils and aluminum oxide nanofluid, with a particle size of approximately 55 nm, in Reynolds numbers from 4000 to 14000, volume fractions of 0.02, 0.04, and 0.06 %, and pitch ratios of 0, 1, 1.6, and 2.4. Then, a proposed correlation for the Nusselt number is presented, and finally, the experimental data are evaluated using an artificial neural network. The optimum increase of 135.6 % in the Nusselt number with aluminum oxide nanofluid occurs at a volume fraction of 0.06 %, a Reynolds number of 14000, and a pitch ratio of 1. The increase in the friction factor with nanofluid and wire coils, compared to the base fluid (water) without the wire coils, is approximately 7.06 %. The correlation coefficient, mean squared error, root mean squared error, and mean absolute error are calculated for the proposed correlation and artificial neural network. Furthermore, the maximum and minimum deviation margins obtained are +3.4211 and −3.2120, respectively. The results indicated that perceptron neural network of a 3-22-1 topology with Levenberg-Marquardt algorithm has successfully predicted the experimental data. |
| format | Article |
| id | doaj-art-a88affceed1d40d5b486c6fec0c86f37 |
| institution | OA Journals |
| issn | 2214-157X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Thermal Engineering |
| spelling | doaj-art-a88affceed1d40d5b486c6fec0c86f372025-08-20T02:04:37ZengElsevierCase Studies in Thermal Engineering2214-157X2025-07-017110623210.1016/j.csite.2025.106232Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networksRoohallah Karimpooremam0Fatemeh poursaied1Bahram Keyvani2Milad Razmi3Reza Aghayari4Davood Toghraie5Soheil Salahshour6Institute of Higher Education Energy, Saveh, IranIslamic Azad University, Science and Research Branch, Faculty of Chemical Engineering, Tehran, IranDepartment of Chemistry, Sav.C., Islamic Azad University, Saveh, Iran; Corresponding author.Department of Management, Faculty of Humanities, Saveh Branch, Islamic Azad University, Saveh, IranDepartment of Chemistry, Sav.C., Islamic Azad University, Saveh, Iran; Corresponding author.Department of Mechanical Engineering, Khomeinishahr branch, Islamic Azad University, Khomeinishahr, Iran; Corresponding author.Faculty of Engineering and Natural Sciences, Istanbul Okan University, Istanbul, Turkey; Faculty of Engineering and Natural Sciences, Bahcesehir University, Istanbul, Turkey; Research Center of Applied Mathematics, Khazar University, Baku, AzerbaijanThe present study aims to experimentally investigate the Nusselt number and friction factor in a double-pipe heat exchanger equipped with wire coils and aluminum oxide nanofluid, with a particle size of approximately 55 nm, in Reynolds numbers from 4000 to 14000, volume fractions of 0.02, 0.04, and 0.06 %, and pitch ratios of 0, 1, 1.6, and 2.4. Then, a proposed correlation for the Nusselt number is presented, and finally, the experimental data are evaluated using an artificial neural network. The optimum increase of 135.6 % in the Nusselt number with aluminum oxide nanofluid occurs at a volume fraction of 0.06 %, a Reynolds number of 14000, and a pitch ratio of 1. The increase in the friction factor with nanofluid and wire coils, compared to the base fluid (water) without the wire coils, is approximately 7.06 %. The correlation coefficient, mean squared error, root mean squared error, and mean absolute error are calculated for the proposed correlation and artificial neural network. Furthermore, the maximum and minimum deviation margins obtained are +3.4211 and −3.2120, respectively. The results indicated that perceptron neural network of a 3-22-1 topology with Levenberg-Marquardt algorithm has successfully predicted the experimental data.http://www.sciencedirect.com/science/article/pii/S2214157X25004927Nusselt numberDouble-pipe heat exchangerNanofluidWire coilsArtificial neural network |
| spellingShingle | Roohallah Karimpooremam Fatemeh poursaied Bahram Keyvani Milad Razmi Reza Aghayari Davood Toghraie Soheil Salahshour Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networks Case Studies in Thermal Engineering Nusselt number Double-pipe heat exchanger Nanofluid Wire coils Artificial neural network |
| title | Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networks |
| title_full | Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networks |
| title_fullStr | Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networks |
| title_full_unstemmed | Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networks |
| title_short | Effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double-pipe heat exchanger and predicting data with artificial neural networks |
| title_sort | effect of using wire coils and aluminum oxide nanofluid on heat transfer in a double pipe heat exchanger and predicting data with artificial neural networks |
| topic | Nusselt number Double-pipe heat exchanger Nanofluid Wire coils Artificial neural network |
| url | http://www.sciencedirect.com/science/article/pii/S2214157X25004927 |
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