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Thermal conductivity of Cu/TiO_2-water/EG hybrid nanofluid: Experimental data and modeling using artificial neural network and correlation

机译:Cu / TiO_2-水/ EG杂化纳米流体的热导率:使用人工神经网络和相关性的实验数据和建模

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摘要

In the present paper, the thermal conductivity of hybrid nanofluids is experimentally investigated. The studied nanofluid was produced using a two-step method by dispersing Cu and TiO_2 nanoparticles with average diameter of 70 and 40 nm in a binary mixture of water/EG (60:40). The properties of this nanofluid were measured in various solid concentrations (0.1,02,0.4,0.8,1,1.5, and 2%) and temperatures ranging from 30 to 60 ℃ Next, two new correlations for predicting the thermal conductivity of studied hybrid nanofluids, in terms of solid concentration and temperature, are proposed that use an artificial neural network (ANN) and are based on experimental data. The results indicate that these two new models have great ability to predict thermal conductivity and show excellent agreement with the experimental results.
机译:在本文中,对杂化纳米流体的热导率进行了实验研究。使用两步法将平均直径分别为70和40 nm的Cu和TiO_2纳米颗粒分散在水/ EG(60:40)的二元混合物中,制成了研究的纳米流体。在各种固体浓度(0.1、02、0.4、0.8、1、1.5和2%)和温度范围为30到60℃的条件下测量了这种纳米流体的特性。接下来,两个新的相互关系用于预测研究的混合纳米流体的热导率根据固体浓度和温度,提出了使用人工神经网络(ANN)并基于实验数据的方法。结果表明,这两个新模型具有很好的预测热导率的能力,并且与实验结果具有极好的一致性。

著录项

  • 来源
    《Letters in heat and mass transfer》 |2015年第8期|100-104|共5页
  • 作者单位

    Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran;

    Fluid Mechanics, Thermal Engineering and Multiphase Flow Research Lab (FUTURE), Department of Mechanical Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangmod, Bangkok 10140, Thailand;

    Faculty of Mechanical Engineering, Semnan University, P.O. Box 35131-19111, Semnan, Iran;

    Department of Mechanical Engineering, Semnan Branch, Islamic Azad University, Semnan, Iran;

    Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran;

    Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran;

    Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;

    Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Thermal conductivity; Artificial neural network; Experimental data; Correlation;

    机译:导热系数;人工神经网络;实验数据;相关性;

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