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Using artificial neural network to optimize the flow and natural heat transfer of a magnetic nanofluid in a square enclosure with a fin on its vertical wall: a lattice Boltzmann simulation

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Abstract

The heat transfer of a nanofluid in a square enclosure is numerically simulated using FORTRAN software in this paper, by considering the radiation (Rad) effect. The enclosure is under a magnetic field (MaF) and can also deviate from the horizontal axis. The enclosure has insulated top and bottom walls, as well as hot and cold right and left walls. There is a fin (0.1 × 0.4) with constant thermal conductivity on its hot wall. Entropy generation (EnG) is investigated as one of the important results in this paper. The lattice Boltzmann method is used for the simulations. A sensitivity analysis is performed on three parameters; including Rayleigh (Ra), Hartmann (Ha), and enclosure angle are introduced as the most effective parameters. Finally, based on these parameters, the performance of the cavity was simulated using an artificial neural network. The results show that the Nusselt (Nu) and EnG increase with the Ra and decrease with the Ha. The parameters mentioned above are subjected to optimization, indicating that the maximum Nu which is equal to 22.24 corresponds to the Ra of 992,409, the Ha of 0.004, and the inclination angle of 34.74°.

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Acknowledgements

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through research groups program under Grant No. RGP.2/38/42.

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Authors and Affiliations

  1. College of Aeronautical Engineering, Jilin Institute of Chemical Technology, Jilin, China

    Haiji Chen

  2. Department of Mathematics. College of Science, King Khalid University, Abha, 61413, Saudi Arabia

    S. Saleem

  3. Independent Researcher, Rostock, Germany

    Mohammad Ghaderi

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  1. Haiji Chen
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  2. S. Saleem
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  3. Mohammad Ghaderi
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HC was involved in conceptualization, methodology, software, writing, performing revise, and project administration. SS helped in writing, formal analysis, and methodology. MG contributed to writing—review and editing, and supervision.

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Correspondence to Mohammad Ghaderi.

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Chen, H., Saleem, S. & Ghaderi, M. Using artificial neural network to optimize the flow and natural heat transfer of a magnetic nanofluid in a square enclosure with a fin on its vertical wall: a lattice Boltzmann simulation. J Therm Anal Calorim 145, 2261–2276 (2021). https://doi.org/10.1007/s10973-021-10767-6

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