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<p>The present communication explores the Darcy-Forchheimer flow of Maxwell nanofluid through an exponentially expanding surface with motile microorganisms and slip conditions. This precise fluid model is employed in several industrial areas, such as polymer extrusion, energy harvesting, thin-film processing, design of heat sinks, cooling nuclear reactors, etc. This analysis is considered the consequences of magnetic field, heat consumption, thermal radiation, thermophoresis and Brownian motion. Appropriate translations are implemented to transfer the formulated models into nonlinear ODEs (Ordinary Differential Equations), which are then computationally tackled by incorporating the bvp4c solver in MATLAB. The current findings are evaluated in comparison with previously published outcomes. The ANFIS (Adaptive Neuro-Fuzzy Inference System) is integrated to predict the flow motion, temperature, nanofluid concentration and microorganisms fields. The thermal and nanofluid concentration fields amplify when the magnitude of the thermophoresis parameter improves. The surface drag force, mass transport rate and motile density microorganisms decrease when augmenting the amount of the magnetic field parameter . Furthermore, it is noted that the lowest heat transfer enhancement percentage <InlineEquation ID="IEq1"><EquationSource Format="TEX">\((9.22\%)\)</EquationSource></InlineEquation> is achieved when the radiation parameter varies from 1.6 to 2 and the highest heat transfer enhancement percentage <InlineEquation ID="IEq2"><EquationSource Format="TEX">\((31.59\%)\)</EquationSource></InlineEquation> is acquired when the radiation parameter changes from 0 to 0.4. The highest heat transfer rate improvement in lower radiation helps the manufacturing industry to cool and control the thermal power, while small enhancements in high levels of radiation regulate the larger temperature conditions.</p>

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Adaptive neuro-fuzzy inference system-based analysis of Maxwell nanofluid flow over an exponentially expanding surface with radiation and multiple slip conditions

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月5日

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  • J. Jagadeeswaran,
  • N. Thamaraikannan,
  • K. Loganathan,
  • S. Eswaramoorthi,
  • S. Divya,
  • P. Senthilkumar

摘要

The present communication explores the Darcy-Forchheimer flow of Maxwell nanofluid through an exponentially expanding surface with motile microorganisms and slip conditions. This precise fluid model is employed in several industrial areas, such as polymer extrusion, energy harvesting, thin-film processing, design of heat sinks, cooling nuclear reactors, etc. This analysis is considered the consequences of magnetic field, heat consumption, thermal radiation, thermophoresis and Brownian motion. Appropriate translations are implemented to transfer the formulated models into nonlinear ODEs (Ordinary Differential Equations), which are then computationally tackled by incorporating the bvp4c solver in MATLAB. The current findings are evaluated in comparison with previously published outcomes. The ANFIS (Adaptive Neuro-Fuzzy Inference System) is integrated to predict the flow motion, temperature, nanofluid concentration and microorganisms fields. The thermal and nanofluid concentration fields amplify when the magnitude of the thermophoresis parameter improves. The surface drag force, mass transport rate and motile density microorganisms decrease when augmenting the amount of the magnetic field parameter . Furthermore, it is noted that the lowest heat transfer enhancement percentage \((9.22\%)\) is achieved when the radiation parameter varies from 1.6 to 2 and the highest heat transfer enhancement percentage \((31.59\%)\) is acquired when the radiation parameter changes from 0 to 0.4. The highest heat transfer rate improvement in lower radiation helps the manufacturing industry to cool and control the thermal power, while small enhancements in high levels of radiation regulate the larger temperature conditions.