Artificial neural network (ANN) analysis on thermophysical properties of magnetohydrodynamics flow with radiation in an arc-shaped enclosure with a rotating cylinder.

Autor: Bairagi T; Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh., Jahid Hasan M; Department of Mechanical and Production Engineering, Islamic University of Technology, Board Bazar, Gazipur, 1704, Bangladesh., Hudha MN; Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh., Azad AK; Department of Natural Sciences, Islamic University of Technology, Board Bazar, Gazipur, 1704, Bangladesh., Rahman MM; Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.
Jazyk: angličtina
Zdroj: Heliyon [Heliyon] 2024 Mar 24; Vol. 10 (7), pp. e28609. Date of Electronic Publication: 2024 Mar 24 (Print Publication: 2024).
DOI: 10.1016/j.heliyon.2024.e28609
Abstrakt: The objective of this research is to examine the thermophysical features of magnetic parameter ( Ha ) and time step (τ) in a lid-driven cavity using a water-based Al 2 O 3 nanofluid and the efficacy of ANN models in accurately predicting the average heat transfer rate. The Galerkin weighted residual approach is used to solve a set of dimensionless nonlinear governing equations. The Levenberg-Marquardt back propagation technique is used for training ANN using sparse simulated data. The findings of the investigation about the flow and thermal fields are shown. Furthermore, a comparative study and prediction have been conducted on the impact of manipulating factors on the average Nusselt number derived from the numerical heat transfer analysis. The findings of the research indicate that, in the absence of magnetohydrodynamics, a rise in the Hartmann number resulted in a drop in both the fluid velocity profile and magnitude. Conversely, it was observed that the temperature and Nusselt number exhibited an increase under these conditions. The mean temperature of the fluid rises as the Hartmann number drops, reaching a peak value of 0.114 when Ha  = 0. The scenario where Ha  = 0, representing the lack of magnetohydrodynamics, shows the highest average Nusselt number, whereas the instance with Ha  = 45 presents the lowest Nusselt number. The ANN model has a high level of accuracy, as seen by an MSE value of 0.00069 and a MAE value of 0.0175, resulting in a 99% accuracy rate.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2024 The Author(s).)
Databáze: MEDLINE
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