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<p>This study proposes a novel analytical approach, Shehu Legendre homotopy perturbation method (SLHPM), to enhance the analysis of heat transfer in ternary hybrid nanofluids composed of graphene, graphene oxide, and silver nanoparticles suspended in water. The objective is to investigate the squeezing flow of the nanofluid between parallel plates under a magnetic field and thermal radiation effects. The governing equations are reduced to ordinary differential equations using a similarity transformation and solved via SLHPM. Validation against published data shows the method provides accurate results for key physical quantities, including the Nusselt number, Sherwood number, and skin friction coefficient. Parametric studies reveal the significant effects of physical parameters such as the squeezing number, magnetic parameter, and thermophoresis on velocity, temperature, and concentration profiles. The findings demonstrate that SLHPM is both effective and computationally efficient, offering improved convergence and reduced CPU time compared to traditional methods. This work emphasizes the intriguing possibilities of ternary hybrid nanofluids and advanced analytical methods for improved heat transfer applications.</p>

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An innovative composite method for analyzing the effects of coupled thermal and magnetic squeezing nanofluid flows between parallel plates

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月16日

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  • Abdul-Sattar Jaber Al-Saif,
  • Ammar Al-Salih

摘要

This study proposes a novel analytical approach, Shehu Legendre homotopy perturbation method (SLHPM), to enhance the analysis of heat transfer in ternary hybrid nanofluids composed of graphene, graphene oxide, and silver nanoparticles suspended in water. The objective is to investigate the squeezing flow of the nanofluid between parallel plates under a magnetic field and thermal radiation effects. The governing equations are reduced to ordinary differential equations using a similarity transformation and solved via SLHPM. Validation against published data shows the method provides accurate results for key physical quantities, including the Nusselt number, Sherwood number, and skin friction coefficient. Parametric studies reveal the significant effects of physical parameters such as the squeezing number, magnetic parameter, and thermophoresis on velocity, temperature, and concentration profiles. The findings demonstrate that SLHPM is both effective and computationally efficient, offering improved convergence and reduced CPU time compared to traditional methods. This work emphasizes the intriguing possibilities of ternary hybrid nanofluids and advanced analytical methods for improved heat transfer applications.