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Aggregation and Effective Thermal Conductivity of Nanofluids: Dependence on Cluster Size and Morphology

[+] Author Affiliations
Miguel Reyes-Mata, Mauricio Zurita-Gotor

Abengoa Research S.L., Seville, Spain

Jerzy Blawzdziewicz

Texas Tech. University, Lubbock, TX

Eligiusz Wajnryb

Polish Academy of Sciences, Warsaw, Poland

Paper No. IMECE2014-38256, pp. V007T09A013; 2 pages
  • ASME 2014 International Mechanical Engineering Congress and Exposition
  • Volume 7: Fluids Engineering Systems and Technologies
  • Montreal, Quebec, Canada, November 14–20, 2014
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4954-5
  • Copyright © 2014 by ASME


We combine a multipolar expansion technique and a cluster-cluster aggregation algorithm to accurately compute the effect of aggregation on the thermal conductivity of nanofluids. Results show that the normalized enhancement in the effective conductivity of nanofluids exhibits a power law dependence on average cluster size. The exponent in the power law is a decreasing function of the fractal dimension, and is always larger than zero, thus predicting enhancements in excess of Maxwell’s theory for well dispersed individual nanoparticles. Results are interpreted in terms of an effective particle size for heat conduction of aggregates which approximately scales as the gyration radius, specially at larger fractal dimensions.

Copyright © 2014 by ASME



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