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<p>For improving efficiency and long-term reliability, the enhancement of heat transfer in renewable energy systems is vital. In particular, Photovoltaic systems suffer significant thermal losses as surface temperature decelerates their electrical conversion efficiency. To overcome these challenges, hybrid nanofluid shows promising coolant because of their superior conductivity and radiative properties. The proposed investigation deal with the free convective transport of aluminium alloy (AA7072 and AA7075)-water hybridized nanoliquid over circular disc where the incorporation of multiple slip effect along with radiation is vital. The mathematical model with the proposed assumptions for the profiles and the boundary conditions are presented in the dimensional form and further suitable transformations are adopted for the re-modelling of the mathematical equations into dimensionless. Moreover, bvp4c built-in function is utilized in tackling these transformed equations. The description of the physical factors is reported briefly via graphs. The study reveals that velocity is controlled by the incorporation of the resistive forces organized by the enrolment of porosity and magnetization whereas hybrid nanofluid provides greater role in enhancing the profile. The proposed nonlinear heat flux projected as thermal radiation give rise a maximum strength in the heat transport phenomena at all points. The importance of the projected investigation is due to the predictive Nusselt number model for the analysis of deep learning using artificial neural network which validates the physical behavior of certain factors under varying operational conditions. Also, the proposed study is relevant to PV systems where effective thermal management shows a vital role sustaining efficiency.</p>

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Data-driven artificial neural network predictive design of heat transfer rate in a hybrid nanofluid dynamics and heat transfer over a circular disc used in photovoltaic thermal systems

  • 期刊论文

  • 发表日期：

    2026年3月8日

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  • Subhajit Panda,
  • S. R. Mishra,
  • Rupa Baithalu,
  • MD. Shamshuddin

摘要

For improving efficiency and long-term reliability, the enhancement of heat transfer in renewable energy systems is vital. In particular, Photovoltaic systems suffer significant thermal losses as surface temperature decelerates their electrical conversion efficiency. To overcome these challenges, hybrid nanofluid shows promising coolant because of their superior conductivity and radiative properties. The proposed investigation deal with the free convective transport of aluminium alloy (AA7072 and AA7075)-water hybridized nanoliquid over circular disc where the incorporation of multiple slip effect along with radiation is vital. The mathematical model with the proposed assumptions for the profiles and the boundary conditions are presented in the dimensional form and further suitable transformations are adopted for the re-modelling of the mathematical equations into dimensionless. Moreover, bvp4c built-in function is utilized in tackling these transformed equations. The description of the physical factors is reported briefly via graphs. The study reveals that velocity is controlled by the incorporation of the resistive forces organized by the enrolment of porosity and magnetization whereas hybrid nanofluid provides greater role in enhancing the profile. The proposed nonlinear heat flux projected as thermal radiation give rise a maximum strength in the heat transport phenomena at all points. The importance of the projected investigation is due to the predictive Nusselt number model for the analysis of deep learning using artificial neural network which validates the physical behavior of certain factors under varying operational conditions. Also, the proposed study is relevant to PV systems where effective thermal management shows a vital role sustaining efficiency.