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<p>The present study examines the impact of heat source/sink, magnetic dipole and heterogeneous–homogeneous chemical reactions on the hybrid nanofluid flow via a stretching cylinder in the presence of porous media. Scientists and engineers can enhance the efficiency of heat transfer by optimising system flow and investigating the impact of chemical reactions on flow dynamics. Many chemical engineering activities, including absorption, leaching, drying, adsorption, evaporation and solvent extraction, can be used in the analysis of mass transfer to or from surfaces. The governing partial differential equations (PDEs) are modelled and presented. The use of similarity variables transforms the modelled PDEs of the present problem into non-dimensional ordinary differential equations (ODEs). The resultant ordinary differential equations (ODEs) are solved using the Runge–Kutta–Fehlberg fourth–fifth order (RKF-45) method and the obtained results are compared using the physics-informed neural network (PINN) approach. Graphical representations illustrate the effects of various parameters on temperature, concentration and velocity profiles. The thermal profile increases as the ferromagnetic interaction and heat source/sink parameters increase. As homogeneous and heterogeneous reaction parameters rise, the concentration profile decreases. The outcomes obtained by PINN are in good agreement with the solution obtained by RKF-45, indicating good convergence. </p>

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Influence of magnetic dipole on the hybrid nanofluid flow with chemical reactions due to the generated and absorbed heat

  • 期刊论文

  • 发表日期：

    2025年5月15日

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  • R S Varun Kumar,
  • K Chandan,
  • K Venkadeshwaran,
  • Taseer Muhammad,
  • R J Punith Gowda,
  • B C Prasannakumara

摘要

The present study examines the impact of heat source/sink, magnetic dipole and heterogeneous–homogeneous chemical reactions on the hybrid nanofluid flow via a stretching cylinder in the presence of porous media. Scientists and engineers can enhance the efficiency of heat transfer by optimising system flow and investigating the impact of chemical reactions on flow dynamics. Many chemical engineering activities, including absorption, leaching, drying, adsorption, evaporation and solvent extraction, can be used in the analysis of mass transfer to or from surfaces. The governing partial differential equations (PDEs) are modelled and presented. The use of similarity variables transforms the modelled PDEs of the present problem into non-dimensional ordinary differential equations (ODEs). The resultant ordinary differential equations (ODEs) are solved using the Runge–Kutta–Fehlberg fourth–fifth order (RKF-45) method and the obtained results are compared using the physics-informed neural network (PINN) approach. Graphical representations illustrate the effects of various parameters on temperature, concentration and velocity profiles. The thermal profile increases as the ferromagnetic interaction and heat source/sink parameters increase. As homogeneous and heterogeneous reaction parameters rise, the concentration profile decreases. The outcomes obtained by PINN are in good agreement with the solution obtained by RKF-45, indicating good convergence.