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The effects of L-shaped heat source in a quarter-tube enclosure filled with MHD nanofluid on heat transfer and irreversibilities, using LBM: numerical data, optimization using neural network algorithm (ANN)

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Abstract

In this paper, the process of natural convection heat transfer (NCHT) and production of entropy (POF) in a portion of a tube has been modeled two-dimensionally. The examined problem is a quarter-tubular enclosure (quarter of a tube) which is filled with water-alumina nanofluid and subjected to a magnetic field (MF) of strength B0 at angle ω relative to horizon. Lattice Boltzmann Method (LBM) is used to simulate this problem. The ranges of parameters used in this investigation are: 0 < ω < 90, 0 < Ha < 60, and 0.1 < L, H < 0.5, and the obtained results include the Nusselt number (Nu), generated entropy, and Bejan number (Be). The results of thermal and dynamic analyses indicate that by growing the Hartmann number (Ha), the NCHT and POF values go up and the Bediminishes. Heat transfer is also improved by increasing the length of the enclosure’s hot walls. The highest amount of heat transfer occurs at the MF angle of 60º, and it is 10.3% greater than the amount of heat transfer occurring at horizontal MF. Finally, an artificial neural network was used to simulate the cavity performance based on these parameters. An optimization is performed on the parameters of heat source length and Ha. The optimization is aimed at finding suitable parameter values that lead to the highest heat transfer rate and lowest POF. A table listing a number of optimal points has been presented at the end of the paper. The optimization results indicate a desirability of about 0.56, which is achieved under the best conditions at defined parameter ranges. In this case, the values of Nu and POF are 7.26 and 3.54, respectively. The optimal state occurs at the non-dimensional hot wall length of about 0.5 and Ha of 37.7.

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Acknowledgements

This work was supported by the University of Science and Technology Beijing. Muhammad Ibrahim acknowledges the Office of China Postdoctoral Council (OCPC) for the postdoctoral international exchange program. The research was supported by the National Natural Science Foundation of China (Grant Nos. 11971142, 61673169). This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, Saudi Arabia, under grant number (KEP-17-130-41). The authors, therefore, acknowledge with thanks DSR for technical and financial support.

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Authors and Affiliations

  1. School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083, China

    Muhammad Ibrahim

  2. Nonlinear Analysis and Applied Mathematics (NAAM)-Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah, 21589, Saudi Arabia

    Tareq Saeed

  3. Department of Mathematics, Faculty of Sciences, University of Tabuk, P.O.Box741, Tabuk, 71491, Saudi Arabia

    Ebrahem A. Algehyne

  4. School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Majid Khan

  5. Department of Mathematics, Huzhou University, Huzhou, 313000, People’s Republic of China

    Yu-Ming Chu

  6. Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering, Changsha University of Science and Technology, Changsha, 410114, People’s Republic of China

    Yu-Ming Chu

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  1. Muhammad Ibrahim
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Ibrahim, M., Saeed, T., Algehyne, E.A. et al. The effects of L-shaped heat source in a quarter-tube enclosure filled with MHD nanofluid on heat transfer and irreversibilities, using LBM: numerical data, optimization using neural network algorithm (ANN). J Therm Anal Calorim 144, 2435–2448 (2021). https://doi.org/10.1007/s10973-021-10594-9

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