Razavi Dehkordi Mohammad Hossein, Alizadeh As'ad, Zekri Hussein, Rasti Ehsan, Kholoud Mohammad Javad, Abdollahi Ali, Azimy Hamidreza
Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
Department of Civil Engineering, College of Engineering, Cihan University-Erbil, Erbil, Iraq.
Heliyon. 2023 Jun 22;9(6):e17539. doi: 10.1016/j.heliyon.2023.e17539. eCollection 2023 Jun.
In the present study, the effects of nanoparticles, mass fraction percentage and temperature on the conductive heat transfer coefficient of Graphene nanosheets- Tungsten oxide/Liquid paraffin 107160 hybrid nanofluid was investigated. For this purpose, four different mass fractions were used in the range of 0.005%-5% in a number of examinations. The results illustrated that the thermal conductivity coefficient was increased with the increment of the mass fraction percentage and the temperature of Graphene nanosheets- Tungsten oxide nanomaterials in the base fluid. Then, a feed-forward artificial neural network was used to model the thermal conductivity coefficient. In general, with the increase in temperature and concentration of nanofluid, the value of thermal conductivity increases. The optimum value of thermal conductivity for this experiment was observed in the volume fraction of 5% and at the temperature of 70 °C. The results of this modeling indicated that the fault of the data estimated for the coefficient of thermal conductivity in the Graphene nanosheets- Tungsten oxide/Liquid paraffin 107160 nanofluid, as a function of mass fraction percentage and temperature, was less than 3%, as compared to the experimental data.
在本研究中，研究了纳米颗粒、质量分数百分比和温度对氧化石墨烯-氧化钨/液体石蜡107160混合纳米流体导热系数的影响。为此，在多次实验中使用了0.005%-5%范围内的四种不同质量分数。结果表明，基础流体中氧化石墨烯-氧化钨纳米材料的质量分数百分比和温度升高时，热导率系数增加。然后，使用前馈人工神经网络对热导率系数进行建模。总体而言，随着纳米流体温度和浓度的增加，热导率值增大。本实验中热导率的最佳值出现在体积分数为5%且温度为70℃时。该建模结果表明，与实验数据相比，氧化石墨烯-氧化钨/液体石蜡107160纳米流体中作为质量分数百分比和温度函数的热导率系数估计数据的误差小于3%。
