Biomedical Engineering Reference
In-Depth Information
data from several research articles measuring the thermal conductivity as a
function of temperature are collated and plotted in a single graph to show a
general trend for the nature of variation of thermal conductivity ratio. As is
evident from the graph, the general trend follows a linearly increasing
thermal conductivity ratio with an increase in temperature. Most researchers
reporting thermal conductivity ratio as a function of temperature used Ag,
Au, Al
2
O
3
, and CuO as the dispersoid. The trend of a gradual increase in
thermal conductivity ratio with an increase in temperature is encouraging
for engine and heat exchanger applications in the transportation industry,
where fluids operate at elevated temperatures. However, studies investigat-
ing the influence of temperature in the reverse trend of variation (with a
decrease in temperature at sub-zero regime) have not been attempted or
reported. Such investigations are warranted to probe the possible role of
Brownian motion on the enhancement of thermal conductivity of nanofluid.
11.4 Modeling of thermal conductivity
Experimental investigations of the thermal conductivity of nanofluids
indicate a substantial increment that needs to be understood and explained
through suitable theoretical models. It has also been pointed out that the
thermal conductivity of nanofluids depends on the concentration, size,
shape/morphology of particles, the base fluid medium, and operating
temperature. Originally, the thermal conductivity of nanofluids was
attributed to formulations involving the effective thermal conductivity of
mixtures from continuum formulations that typically involve only the
particle size/shape and volume fraction and assume diffusive heat transfer in
both fluid and solid phases. This approach can give a good prediction for
micrometer or larger-size solid/fluid systems, but it fails to explain the
anomalously high thermal conductivity of nanofluids. Details of previously
developed models are given in Table 11.2.
Since most classical models fail to explain the thermal conductivity
enhancement of nanofluids, the nanofluid community has intensively
investigated this phenomenon and a number of mechanisms have been
proposed. Keblinski et al. (2002) investigated the possible factors that may
enhance the thermal conductivity in nanofluids such as particle size,
Brownian motion, the clustering of particles, and the existence of a
nanolayer between the nanoparticles and the base fluid. The possible
mechanisms are schematically shown in Fig. 11.7. Based on this study
several other models have been developed by researchers to validate the
thermal conductivity enhancement of nanofluids.
