Thermal performance, entropy generation, and machine learning insights of Al₂O₃-TiO₂ hybrid nanofluids in turbulent flow

This study investigates the heat transfer performance of water-based Al2O3-TiO2 (50:50) hybrid nanofluids under turbulent flow conditions. Al2O3 and TiO2 nanoparticles (13 and 21 nm, respectively) were dispersed in water to prepare the nanofluids in the concentrations range of 0 to 1 vol%. Thermal conductivity and viscosity are measured in the temperature range of 30 to 60oC for the prepared nanofluids. Experimental and numerical analyses explored the effect of concentration and Reynolds number on Nusselt number, entropy generation, and friction factor. The results demonstrate that maximum viscosity enhancement of 15.77 and 14.76% is observed for 1 vol% of hybrid nanofluid and Al2O3 nanofluid compared to base fluid at 30 oC, respectively. The maximum Nusselt number enchantment is 70.4% for 1 vol% of hybrid nanofluid compared to the water. Similarly, hybrid nanofluids achieved a remarkable reduction in total entropy generation of 46% in contrast to the base fluid. New correlations are proposed to predict both the Nusselt number and friction factor for hybrid nanofluids. Furthermore, employing machine learning techniques, highly accurate models are developed. These findings highlight the promising role of hybrid nanofluids in achieving efficient thermal management in various applications.

相关文章

  • Experimental investigation and optimization of mechanical and tribological performances of bio-based sustainable hybrid composites incorporating Nano-SiO₂ fillers
    [G. Velmurugan, Jasgurpreet Singh Chohan, Ramya Maranan, Prabhu Paramasivam, N. Manikandan, P. Thejasree, S. Lakshmi Narayana, Bamidele Charles Olaiya, Mukesh Kumar]
  • Machine learning analysis of thermophysical and thermohydraulic properties in ethylene glycol- and glycerol-based SiO2 nanofluids
    [Suleiman Akilu, K. V. Sharma, Aklilu Tesfamichael Baheta, Praveen Kumar Kanti, Prabhu Paramasivam]
  • Deep Learning for Enhanced Fault Diagnosis of Monoblock Centrifugal Pumps: Spectrogram-Based Analysis
    [Prasshanth Chennai Viswanathan, Prabhu Paramasivam, Sridharan Naveen Venkatesh, Vaithiyanathan Sugumaran, Sakthivel Nanjagoundenpalayam Ramasamy, Tapan Kumar Mahanta, Seshathiri Dhanasekaran, Natrayan Lakshmaiya]
  • qq

    成果名称:低表面能涂层

    合作方式:技术开发

    联 系 人:周老师

    联系电话:13321314106

    ex

    成果名称:低表面能涂层

    合作方式:技术开发

    联 系 人:周老师

    联系电话:13321314106

    yx

    成果名称:低表面能涂层

    合作方式:技术开发

    联 系 人:周老师

    联系电话:13321314106

    ph

    成果名称:低表面能涂层

    合作方式:技术开发

    联 系 人:周老师

    联系电话:13321314106

    广告图片

    润滑集