Abstract In this study, the thermal conductivity ( k n f ) of a ternary hybrid nanofluid containing Multi-walled Carbon Nanotubes (MWCNTs) - titania-zinc oxide/water-ethylene glycol (EG) (80:20) as well as binary and mono nanofluids has been studied. The nanofluid fabrication was performed by the two-step method by dispersing the nanoparticles in the base fluid using ultrasonic waves. The volume fractions of ternary hybrid nanofluids were φ = 0.1 % to 0.4 %, and mono and binary hybrid nanofluids were fabricated in φ = 0.1 % and φ = 0.4 %, respectively. After ensuring the stability of the nanofluids, the k n f was measured by the transient hot-wire method at a temperature range of T = 25−50 °C. The experimental results show that with increasing the temperature, the k n f also increases. Also, increasing the φ increases the k n f . At higher φ , the effect of increasing temperature is even more evident. According to the results, the highest increase in k n f containing MWCNTs/water-EG was observed at a φ = 0.4 % and T = 50 °C, which showed an increase of 17.82 % compared to the base fluid. Finally, a mathematical model was proposed as a function of temperature and φ to estimate the k n f of a ternary hybrid nanofluid. A comparison of the results of the proposed mathematical model with the experimental results showed that the proposed model is highly accurate.

中文翻译：

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包含 MWCNTs-二氧化钛-氧化锌/水-乙二醇 (80:20) 以及二元和单纳米流体的三元混合纳米流体的热导率的综合实验研究

摘要 在这项研究中，包含多壁碳纳米管 (MWCNT) - 二氧化钛-氧化锌/水-乙二醇 (80:20) 以及二元和单纳米流体的三元混合纳米流体的热导率 (knf)已被研究。通过使用超声波将纳米颗粒分散在基液中，通过两步法进行纳米流体制造。三元混合纳米流体的体积分数为 φ = 0.1 % 至 0.4 %，单元和二元混合纳米流体分别以 φ = 0.1 % 和 φ = 0.4 % 制造。在确保纳米流体的稳定性后，通过瞬态热线法在 T = 25-50 °C 的温度范围内测量 knf。实验结果表明，随着温度的升高，knf也增加。此外，增加 φ 会增加 knf 。在较高的 φ 下，温度升高的效果更加明显。根据结果​​，在 φ = 0.4 % 和 T = 50 °C 时观察到含有 MWCNTs/水-EG 的 knf 的最大增加，与基液相比增加了 17.82%。最后，提出了一个数学模型作为温度和 φ 的函数来估计三元混合纳米流体的 knf。将所提出的数学模型的结果与实验结果进行比较，表明所提出的模型是高度准确的。提出了一个数学模型作为温度和 φ 的函数来估计三元混合纳米流体的 knf。将所提出的数学模型的结果与实验结果进行比较，表明所提出的模型是高度准确的。提出了一个数学模型作为温度和 φ 的函数来估计三元混合纳米流体的 knf。将所提出的数学模型的结果与实验结果进行比较，表明所提出的模型是高度准确的。