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Backpropagated Neural Network Modeling for the Non-Fourier Thermal Analysis of a Moving Plate

Author

Listed:
  • R. S. Varun Kumar

    (Department of Studies in Mathematics, Davangere University, Davangere 577002, Karnataka, India)

  • M. D. Alsulami

    (Department of Mathematics, College of Sciences and Arts at Alkamil, University of Jeddah, Jeddah 23218, Saudi Arabia)

  • I. E. Sarris

    (Department of Mechanical Engineering, University of West Attica, 12244 Athens, Greece)

  • B. C. Prasannakumara

    (Department of Studies in Mathematics, Davangere University, Davangere 577002, Karnataka, India)

  • Saurabh Rana

    (Department of Mathematics, University Centre for Research & Development, Chandigarh University, Mohali 140413, Punjab, India)

Abstract

The present article mainly focuses on the transient thermal dispersal within a moving plate using the non-Fourier heat flux model. Furthermore, the innovative, sophisticated artificial neural network strategy with the Levenberg-Marquardt backpropagated scheme (ANNS-LMBS) is proposed for determining the transient temperature in the convective-radiative plate. Using dimensionless terms, the energy model for transient heat exchange is simplified into a non-dimensional form. The arising partial differential equation (PDE) is then numerically tackled using the finite difference method (FDM). A data set for the various scenarios of the thermal parameters influencing the thermal variation through the plate has been generated using the FDM. In addition, the effect of the dimensionless physical variables on the thermal profile of a moving plate has been examined and discussed in detail. Increments in the convection-conduction and radiation-conduction parameters are figured to yield a reduction in the transient thermal dispersion. An upsurge in the Peclet number caused the improvement of thermal dispersal in the plate.

Suggested Citation

  • R. S. Varun Kumar & M. D. Alsulami & I. E. Sarris & B. C. Prasannakumara & Saurabh Rana, 2023. "Backpropagated Neural Network Modeling for the Non-Fourier Thermal Analysis of a Moving Plate," Mathematics, MDPI, vol. 11(2), pages 1-32, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:2:p:438-:d:1035414
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    References listed on IDEAS

    as
    1. Zhu, Yuxiao & Newbrook, Daniel W. & Dai, Peng & de Groot, C.H. Kees & Huang, Ruomeng, 2022. "Artificial neural network enabled accurate geometrical design and optimisation of thermoelectric generator," Applied Energy, Elsevier, vol. 305(C).
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    3. Elahi, Ehsan & Zhang, Zhixin & Khalid, Zainab & Xu, Haiyun, 2022. "Application of an artificial neural network to optimise energy inputs: An energy- and cost-saving strategy for commercial poultry farms," Energy, Elsevier, vol. 244(PB).
    4. Mabood, F. & Shamshuddin, MD. & Mishra, S.R., 2022. "Characteristics of thermophoresis and Brownian motion on radiative reactive micropolar fluid flow towards continuously moving flat plate: HAM solution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 191(C), pages 187-202.
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