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A Novel Statistical Clustering Model for Predicting Thermal Conductivity of Nanofluid

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Abstract

An analytical method is proposed to predict the thermal conductivity of nanofluids by use of the macroscopic statistical characteristics of particle clustering suspensions. The algorithm is much simpler and more convenient than the fractal model method suggested and reported before. It is shown with numerical calculation and discussion that reliable predictions of the thermal conductivity for a nanofluid can be reached with the method presented in this paper. The physical meaning and practical prospects in the research and development for screening and optimizing nanofluids as new advanced working fluids are presented.

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Authors and Affiliations

  1. Thermal Engineering Department, Tsinghua University, 100084, Beijing, People’s Republic of China

    Bu-Xuan Wang, Wen-Yan Sheng & Xiao-Feng Peng

Authors
  1. Bu-Xuan Wang
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  2. Wen-Yan Sheng
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  3. Xiao-Feng Peng
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Correspondence to Bu-Xuan Wang.

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Wang, BX., Sheng, WY. & Peng, XF. A Novel Statistical Clustering Model for Predicting Thermal Conductivity of Nanofluid. Int J Thermophys 30, 1992–1998 (2009). https://doi.org/10.1007/s10765-009-0673-4

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  • DOI: https://doi.org/10.1007/s10765-009-0673-4

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