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Viscosity of nanofluids containing anisotropic particles: A critical review and a comprehensive model
The European Physical Journal E ( IF 1.8 ) Pub Date : 2019-12-24 , DOI: 10.1140/epje/i2019-11923-7 Xuemin Ye 1 , Satish G Kandlikar 2 , Chunxi Li 1
中文翻译:
包含各向异性粒子的纳米流体的粘度:关键评论和全面的模型
更新日期:2019-12-24
The European Physical Journal E ( IF 1.8 ) Pub Date : 2019-12-24 , DOI: 10.1140/epje/i2019-11923-7 Xuemin Ye 1 , Satish G Kandlikar 2 , Chunxi Li 1
Affiliation
Abstract.
Compared to nanofluids with spherical particles, nanofluids with anisotropic particles possess higher thermal conductivity and present a better enhancement option in heat transfer applications. The viscosity variation of such nanofluids becomes of great importance in evaluating their pumping power in thermal systems. This paper presents a comprehensive review of the experimental and theoretical studies on the viscosity of nanofluids with anisotropic particles. The internal mechanisms of viscosity evolution are investigated considering three aspects: particle clustering, particle interactions, and Brownian motion. In experimental studies, important factors including classification and synthetic methods for particle preparation, base fluid, particle loading, particle shape and size, temperature, p H, shear stress and electric field are investigated in detail. Classical theoretical models and empirical relations of the effective viscosity of suspensions are discussed. Some crucial factors such as maximum particle packing fraction, fractal index and intrinsic viscosity models, are examined. A comparison of predictions and experimental results shows that the classical models underestimate suspension viscosity. A comprehensive combination of the modified Krieger-Dougherty (K-D) model with intrinsic viscosity relations for different aspect ratios is suggested for low particle loadings, and the modified Maron-Pierce model (M-D) is recommended for high particle loadings. Possible directions for future works are discussed.Graphical abstract
中文翻译:
包含各向异性粒子的纳米流体的粘度:关键评论和全面的模型