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Experimental validation of numerical predictions for forced convective heat transfer of nanofluids in a microchannel
Year of publication 2016
Title of paper Experimental validation of numerical predictions for forced convective heat transfer of nanofluids in a microchannel
Authors Yu, J., Kang, S.-W., Jeong, R.-G., and Banerjee, D.
Volume 62
Pages 203 - 212
Journal International Journal of Heat and Fluid Flow
Link 관련링크 http://dx.doi.org/10.1016/j.ijheatfluidflow.2016.11.001 26회 연결
In this study, we postulated and demonstrated that surface conditions have a dominant role in multi- phase flows that leverage stable colloidal nanoparticle suspensions (i.e., nanofluids) in determining their efficacy as heat transfer fluids (HTF). Forced convective heat transfer rates during the flow of de-ionized water (DIW) and aqueous TiO 2 nanofluids inside a microchannel were studied numerically as well as experimentally under constant wall temperature boundary conditions. A brief literature review of the theoretical investigations involving the thermal-conductivity of nanofluids as heat transfer fluids (HTF) was also carried out. This enabled the development of a numerical model and computational analysis for forced convective heat transfer of nanofluids in a microchannel using conventional CFD (Computa- tional Fluid Dynamics) techniques. Experimental validation of the numerical predictions was in accor- dance with the predicted values of the temperature profile near the walls of the microchannel for the base fluid. Anomalous enhancement of the convective heat flux values was observed in the experiments using nanofluids (e.g., an increase of 91.9%). However, this trend was not seen in the computational anal- ysis because the numerical models were based on continuum assumptions and flow features involving nanoparticles in a stable colloidal solution involving non-continuum effects. The anomalous enhance- ments are postulated to be caused by isolated and dispersed precipitation of nanoparticles on the flow conduits (the precipitated nanoparticles are called “nanofins”) which in turn enhance the surface area available for heat exchange (this is called the “nanofin effect”). The numerical validation of nanoparticle precipitation was successfully achieved by additionally considering particle tracking (i.e., DPM: Discrete Phase Model) and two-phase flow modeling based on conventional CFD and HT methods.
The “nanofin effect”consists of the cumulative influence of several transport mechanisms at the solid- fluid interface on a nanoscale level - arising from the increase in the effective surface area caused by the formation of surface nanofins - which in turn modulates the effective thermal impedance (resistance, capacitance, inductance, etc.) as well as thermal diodic effects. The efficacy of the nanofins depends on various parameters such as the local profiles for the wall temperature, concentration and flow rates of each phase.