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<p>This research conducts a theoretical analysis of the intertwined roles of activation energy and binary chemical reactions on the transient mixed convective flow past a vertical semi-infinite plate. Emphasis is placed on the interplay of Brownian diffusion, thermophoretic migration, and viscous dissipation in shaping the nanofluid dynamics, particularly under the Buongiorno model framework. The thermophysical behaviour governing momentum, thermal, and concentration fields is modeled through nonlinear partial differential equations and tackled by means of the finite element technique. A key outcome of this study reveals the complementary effects of thermophoresis and Brownian motion on thermal and mass transport. With an increase in the thermophoretic parameter, nanoparticles drift from high-temperature zones to cooler areas, which slightly raises the fluid temperature. Enhanced Brownian motion amplifies stochastic particle movement, resulting in a considerable augmentation of concentration distribution throughout the flow domain. Amplifying the suction parameter consistently enhances the skin friction coefficient with successive increments, yielding approximately a 17–21% rise. Enhancing the heat source parameter leads to a significant rise Nu from 1.681020 to 2.601414, which translates to a 54.7% improvement in thermal transport. An increase in the chemical reaction rate parameter from 0.20 to 0.80 leads to a 35.5% decline in Sh. This study performs a high-fidelity optimization and sensitivity analysis of convective heat transfer in nanofluid systems, considering thermophoretic effects, internal heat generation, and thermal radiation as the governing input parameters, with the Nusselt number serving as the key performance metric. A comprehensive quadratic model built using Response Surface Methodology integrated with Central Composite Design enables accurate prediction and interaction assessment among the variables. The numerical outcomes are rigorously validated to ensure reliability and precision. The findings hold significant promise for enhancing thermal management in microelectronic cooling, energy systems, and industrial heat exchangers.</p>

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Numerical investigation and optimization of unsteady convective nanofluid flow over a vertical surface with binary chemical reactions and activation energy using the Buongiorno framework

  • 期刊论文

  • 发表日期：

    2025年9月22日

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  • Rupalakshmi Dharanikota,
  • Thirupathi Thumma,
  • Surender Ontela

摘要

This research conducts a theoretical analysis of the intertwined roles of activation energy and binary chemical reactions on the transient mixed convective flow past a vertical semi-infinite plate. Emphasis is placed on the interplay of Brownian diffusion, thermophoretic migration, and viscous dissipation in shaping the nanofluid dynamics, particularly under the Buongiorno model framework. The thermophysical behaviour governing momentum, thermal, and concentration fields is modeled through nonlinear partial differential equations and tackled by means of the finite element technique. A key outcome of this study reveals the complementary effects of thermophoresis and Brownian motion on thermal and mass transport. With an increase in the thermophoretic parameter, nanoparticles drift from high-temperature zones to cooler areas, which slightly raises the fluid temperature. Enhanced Brownian motion amplifies stochastic particle movement, resulting in a considerable augmentation of concentration distribution throughout the flow domain. Amplifying the suction parameter consistently enhances the skin friction coefficient with successive increments, yielding approximately a 17–21% rise. Enhancing the heat source parameter leads to a significant rise Nu from 1.681020 to 2.601414, which translates to a 54.7% improvement in thermal transport. An increase in the chemical reaction rate parameter from 0.20 to 0.80 leads to a 35.5% decline in Sh. This study performs a high-fidelity optimization and sensitivity analysis of convective heat transfer in nanofluid systems, considering thermophoretic effects, internal heat generation, and thermal radiation as the governing input parameters, with the Nusselt number serving as the key performance metric. A comprehensive quadratic model built using Response Surface Methodology integrated with Central Composite Design enables accurate prediction and interaction assessment among the variables. The numerical outcomes are rigorously validated to ensure reliability and precision. The findings hold significant promise for enhancing thermal management in microelectronic cooling, energy systems, and industrial heat exchangers.