Analytical analyzing mixed convection flow of nanofluid in a vertical channel using python approach

This study uses analytical methods to investigate the impact of parameters on the mixed convection flow of nanofluid in a vertical channel. The research aims to explore the heat transfer characteristics of nanofluids for more efficient heat transfer in devices. The study analyzes the influence of the Reynolds, Grashof, and Prandtl numbers on nanofluid flows. It also examines the effects of temperature and nanoparticle concentration distributions on parameters such as Brownian motion (Nb), thermophoresis (Nt), and Lewis number (Le). The presence of nanoparticles significantly enhances the heat transfer characteristics in the flow problem. Reynolds number, Grashof number, and Prandtl number significantly impact flow behavior. Velocity, temperature, and nanoparticle volume fraction profile trends are thoroughly investigated and found to vary. Akbari-Ganji's method (AGM) and the homotopy perturbation method (HPM) demonstrate the potential of computational tools in analyzing nanotechnology fluid dynamics. The accuracy and reliability of the proposed analytical techniques are confirmed through comparisons with a numerical method. The novelty of this research lies in its comprehensive analysis of parameter effects on the mixed convection flow of nanofluid, the enhanced heat transfer characteristics in the presence of nanoparticles, and the unique contributions offered by the utilization of Python programming in this field. The outcomes of this study provide insights for designing and optimizing heat transfer systems using nanofluids, contributing to advancements in nanotechnology.

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