Modified Prediction Model for Thermal Conductivity of Spherical Nanoparticle Suspensions (Nanofluids) By Introducing Static and Dynamic Mechanisms

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• 作者：Wenzheng Cui ; Zhaojie Shen ; Jianguo Yang ; Shaohua Wu
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2014
• 出版时间：November 19, 2014
• 年：2014
• 卷：53
• 期：46
• 页码：18071-18080
• 全文大小：445K
• ISSN：1520-5045

文摘

Nanofluids possess significantly increased thermal conductivity that conventional heat conduction theories and models for nanoparticles鈥搇iquid suspensions cannot explain, which provides new scientific challenges. The aim of this study is to establish a modified prediction model for thermal conductivity of nanofluids that takes into account more comprehensive mechanisms. Based on effective medium theory, the role of dynamics and static mechanisms including the absorption liquid layer at the liquid/nanoparticle interface, the effect of aggregate structure of nanoparticles, and the impact of random motions of nanoparticles have been considered to establish the model. The parameters in the model have definite physical meaning and are more precise. For instance, the thermal conductivity of nanoparticles, k_p, is replaced with thermal conductivity of nanoparticles aggregate, and the volume fraction of nanoparticles along with the absorption layer in nanofluids 蠒 is used instead of the volume fraction of aggregate. It is found that by considering roundly the mechanisms for heat conduction enhancement, the predictions by the present model are closer to the real situation. For various types of nanofluids (with different materials including metal, metallic oxide and nonmetallic oxide, different volume fractions, or different nanoparticle diameters), the present model gives good predictions. And the prediction results of the present model also coincide with molecular dynamics simulation, which further proves the advantages of the present model.