Effective Thermal Conductivity of Nanofluids Containing Silicon Dioxide or Zirconium Dioxide Nanoparticles Dispersed in a Mixture of Water and Glycerol - Bioucas, Francisco; Koehn, Christian; Jean-Fulcrand, Annelise; Garnweitner, Georg; Koller, Thomas Manfred; Fröba, Andreas Paul (International Journal of Thermophysics, 2022)
The present study investigates the effective thermal conductivity of nanofluids containing crystalline or amorphous silicon dioxide (SiO2), or zirconium dioxide (ZrO2) nanoparticles dispersed in a mixture of water and glycerol with a mass ratio of 60:40. Such fluids are relevant as potential cutting fluids in tribology and feature a broad distribution of irregularly shaped non-spherical particles of dimensions on the order of (100 to 200) nm that were produced by comminution of larger particles or particle aggregates. A new steady-state guarded parallel-plate instrument was applied for the absolute measurement of the effective thermal conductivity of the nanofluids with an expanded uncertainty (coverage factor k = 2) of 3% for temperatures from (293 to 353) K and particle volume fractions up to 0.1. For a constant volume fraction of 0.03 for the three particle types, the measured thermal-conductivity ratios, i.e. the effective thermal conductivity of the nanofluids relative to the thermal conductivity of the base fluid, are less than 1.05 and not affected by temperature. In the case of the nanofluids with crystalline SiO2, with increasing particle volume fraction from 0.03 to 0.10 the thermal-conductivity ratios increase up to values of about 1.18 for all temperatures. A comparison of the measurement results with the Hamilton-Crosser model and an analytical resistance model for the effective thermal conductivity of nanofluids shows that the former one allows for better predictions for the present nanofluids with a relatively large viscosity. In this context, it could be shown that detailed knowledge about the sphericity and thermal conductivity of the dispersed nanoparticles is required for the modeling approaches.
CRIS-Team WoS Importer:2022-09-23