Critical evaluation of anomalous thermal conductivity and convective heat transfer enhancement in nanofluids

While robust progress has been made towards the practical use of nanofluids, uncertainties remain concerning the fundamental effects of nanoparticles on key thermo-physical properties. Nanofluids have higher thermal conductivity and single-phase heat transfer coefficients than their base fluids. The possibility of very large thermal conductivity enhancement in nanofluids and the associated physical mechanisms are a hotly debated topic, in part because the thermal conductivity database is sparse and inconsistent. This thesis reports on the International Nanofluid Property Benchmark Exercise (INPBE) in which the thermal conductivity of identical samples of colloidally stable dispersions of nanoparticles, or 'nanofluids', was measured by over 30 organizations worldwide, using a variety of experimental approaches, including the transient hot wire method, steady-state methods and optical methods. The nanofluids tested were comprised of aqueous and non-aqueous basefluids, metal and metal oxide particles, near-spherical and elongated particles, at low and high particle concentrations. The data analysis reveals that the data from most organizations lie within a relatively narrow band (± 10% or less) about the sample average, with only few outliers. The thermal conductivity of the nanofluids was found to increase with particle concentration and aspect ratio, as expected from classical theory. The effective medium theory developed for dispersed particles by Maxwell in 1881, and recently generalized by Nan et al., was found to be in good agreement with the experimental data. The nanofluid literature contains many claims of anomalous convective heat transfer enhancement in both turbulent and laminar flow. To put such claims to the test, we have performed a critical detailed analysis of the database reported in 12 nanofluid papers (8 on laminar flow and 4 on turbulent flow). The methodology accounted for both modeling and experimental uncertainties in the following way. The heat transfer coefficient for any given data set was calculated according to the established correlations (Dittus-Boelter's for turbulent flow and Shah's for laminar flow). The uncertainty in the correlation input parameters (i.e. nanofluid thermo-physical properties and flow rate) was propagated to get the uncertainty on the predicted heat transfer coefficient. The predicted and measured heat transfer coefficient values were then compared to each other. If they differed by more than their respective uncertainties, we called the deviation anomalous. According to this methodology, it was found that in nanofluid laminar flow in fact there seems to be anomalous heat transfer enhancement in the entrance region, while the data are in agreement (within uncertainties) with the Shah's correlation in the fully developed region. On the other hand, the turbulent flow data could be reconciled (within uncertainties) with the Dittus-Boelter's correlation, once the temperature dependence of viscosity was included in the prediction of the Reynolds number. While this finding is plausible, it could not be directly confirmed, because most papers do not report information about the temperature dependence of the viscosity for their nanofluids.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Nuclear Science and Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Prabhat, Naveen

Advisor dc:contributor.advisor

• Jacopo Buongiorno and Lin-Wen Hu.

• Nuclear Science and Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/62707

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/62707