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建立余热回收中纳米工质的导热系数预测模型
引用本文:周树光,翟玉玲,王江.建立余热回收中纳米工质的导热系数预测模型[J].工业加热,2020(4):23-26,31.
作者姓名:周树光  翟玉玲  王江
作者单位:国家能源集团云南阳宗海发电有限公司;昆明理工大学省部共建复杂有色金属重点实验室
基金项目:国家自然科学基金项目(51806090)。
摘    要:采用两步法制备质量分数为1%的Cu/Al2O3-H2O/EG混合纳米流体。首先,研究其导热系数随温度和基液混合比的变化情况。然后,根据多项式回归理论建立Cu/Al2O3-H2O/EG混合纳米流体的导热系数预测模型。实验结果表明,纳米流体的稳定性随乙二醇含量的增大而增强,由于不同种类粒子间的分子吸附力不同,导致相同种类粒子容易结合形成团聚体,而Cu粒子与Al2O3粒子的团聚体则较少。导热系数随着温度的升高非线性升高,随基液中水含量的增大而下降。根据实验数据,拟合了导热系数与温度及基液混合比的多项式预测模型,回归系数R2达0. 998,精度较高可以很好地预测Cu/Al2O3-H2O/EG混合纳米流体的导热系数。该模型可以指导工程应用。

关 键 词:纳米流体  导热系数  预测模型  基液混合比  余热利用

A Prediction Model of Thermal Conductivity of Nanofluids in the Waste Heat Recovery System
ZHOU Shuguang,ZHAI Yuling,WANG Jiang.A Prediction Model of Thermal Conductivity of Nanofluids in the Waste Heat Recovery System[J].Industrial Heating,2020(4):23-26,31.
Authors:ZHOU Shuguang  ZHAI Yuling  WANG Jiang
Affiliation:(National Energy Group Yunnan Yangzonghai Power Generation Co.Ltd.,Kunming 652103,China;State Key Laboratory of Complex Nonferrous Metal Resources Clean Utilization,Faculty of Metallurgical and Energy Engineering,Kunming University of Science and Technology,Kunming 650093,China)
Abstract:A two-step method was used to prepare a Cu/Al2 O3-H2 O/EG mixed nanofluid with a mass fraction of 1%,and the change of its thermal conductivity with temperature and the mixing ratio of the base liquid was studied. Then,a thermal conductivity prediction model of Cu/Al2 O3-H2 O/EG mixed nanofluid was established based on polynomial regression theory. The experimental results show that the stability of nanofluids increases with the increase of ethylene glycol content. Due to the different molecular adsorption forces between different kinds of particles,the same kinds of particles are easy to combine to form aggregates,while Cu particles and Al2 O3 particles are aggregated. Less.The thermal conductivity increases non-linearly with increasing temperature and decreases with increasing water content in the base fluid.According to the experimental data,a polynomial prediction model of thermal conductivity,temperature,and mixing ratio of the base fluid was fitted. The regression coefficient R2 was 0. 998,and the thermal conductivity of the Cu/Al2 O3-H2 O/EG mixed nanofluid was predicted with high accuracy. The model can guide engineering applications.
Keywords:nanofluids  thermal conductivity  prediction model  mixture ratio  waste heat utilization
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