An introduction to heat transfer

This article reports on the International Nanofluid Property Benchmark Exercise, or 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 in the exercise were comprised of aqueous and nonaqueous 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. There are (small) systematic differences in the absolute values of the nanofluid thermal conductivity among the various experimental approaches; however, such differences tend to disappear when the data are normalized to the measured thermal conductivity of the basefluid. The effective medium theory developed for dispersed particles by Maxwell in 1881 and recently generalized by Nan et al. [J. Appl. Phys. 81, 6692 (1997)], was found to be in good agreement with the experimental data, suggesting that no anomalous enhancement of thermal conductivity was achieved in the nanofluids tested in this exercise.

A Benchmark Study on the Thermal Conductivity of Nanofluids

The growth of a vapor bubble in a superheated liquid is controlled by three factors: the inertia of the liquid, the surface tension, and the vapor pressure. As the bubble grows, evaporation takes place at the bubble boundary, and the temperature and vapor pressure in the bubble are thereby decreased. The heat inflow requirement of evaporation, however, depends on the rate of bubble growth, so that the dynamic problem is linked with a heat diffusion problem. Since the heat diffusion problem has been solved, a quantitative formulation of the dynamic problem can be given. A solution for the radius of the vapor bubble as a function of time is obtained which is valid for sufficiently large radius. This asymptotic solution covers the range of physical interest since the radius at which it becomes valid is near the lower limit of experimental observation. It shows the strong effect of heat diffusion on the rate of bubble growth. Comparison of the predicted radius‐time behavior is made with experimental observations in superheated water, and very good agreement is found.

The growth of vapor bubbles in superheated liquids. report no. 26-6

Recent advances in modeling and simulation of nanofluid flows-Part I: Fundamentals and theory

Geometry: shape, size, aspect ratio and orientation Flow Type: forced, natural, laminar, turbulent, internal, external Boundary: isothermal (Tw = constant) or isoflux (q̇w = constant) Fluid Type: viscous oil, water, gases or liquid metals Properties: all properties determined at film temperature Tf = (Tw + T∞)/2 Note: ρ and ν ∝ 1/Patm ⇒ see Q12-40 density: ρ ((kg/m) specific heat: Cp (J/kg ·K) dynamic viscosity: μ, (N · s/m) kinematic viscosity: ν ≡ μ/ρ (m/s) thermal conductivity: k, (W/m ·K) thermal diffusivity: α, ≡ k/(ρ · Cp) (m/s) Prandtl number: Pr, ≡ ν/α (−−) volumetric compressibility: β, (1/K)

Convection Heat Transfer

A thermal transport mechanism leading to the enhanced thermal conductivity of Graphene nanofluids has been proposed. The Graphene sheet size is postulated to be the key to the underlying mechanism. Based on a critical sheet size derived from Stokes-Einstein equation for the poly-dispersed nanofluid, sheet percolation and Brownian motion assisted sheet collisions are used to explain the heat conduction. A collision dependant dynamic conductivity considering Debye approximated volumetric specific heat due to phonon transport in Graphene has been incorporated. The model has been found to be in good agreement with experimental data.

The Role of Percolation and Sheet Dynamics during Heat Conduction in poly-dispersed Graphene Nanofluids

The primary objective of this study is to investigate the effect of slip mechanisms in nanofluids through scaling analysis. The role of nanoparticle slip mechanisms in both water- and ethylene glycol-based nanofluids is analyzed by considering shape, size, concentration, and temperature of the nanoparticles. From the scaling analysis, it is found that all of the slip mechanisms are dominant in particles of cylindrical shape as compared to that of spherical and sheet particles. The magnitudes of slip mechanisms are found to be higher for particles of size between 10 and 80 nm. The Brownian force is found to dominate in smaller particles below 10 nm and also at smaller volume fraction. However, the drag force is found to dominate in smaller particles below 10 nm and at higher volume fraction. The effect of thermophoresis and Magnus forces is found to increase with the particle size and concentration. In terms of time scales, the Brownian and gravity forces act considerably over a longer duration than the other forces. For copper-water-based nanofluid, the effective contribution of slip mechanisms leads to a heat transfer augmentation which is approximately 36% over that of the base fluid. The drag and gravity forces tend to reduce the Nusselt number of the nanofluid while the other forces tend to enhance it.

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Scaling analysis for the investigation of slip mechanisms in nanofluids

A thermal transport mechanism leading to the enhanced thermal conductivity of graphene nanofluids has been proposed. The graphene sheet size is postulated to be the key to the underlying mechanism. Based on a critical sheet size derived from Stokes-Einstein equation for the poly-dispersed nanofluid, sheet percolation and Brownian motion assisted sheet collisions are used to explain the heat conduction. A collision dependant dynamic conductivity considering Debye approximated volumetric specific heat due to phonon transport in graphene has been incorporated. The model has been found to be in good agreement with experimental data.

Arvind Pattamatta

Papers

The Role of Percolation and Sheet Dynamics during Heat Conduction in poly-dispersed Graphene Nanofluids

Scaling analysis for the investigation of slip mechanisms in nanofluids

The role of percolation and sheet dynamics during heat conduction in poly-dispersed graphene nanofluids

Effect of flow maldistribution on the thermal performance of parallel microchannel cooling systems

Modeling heat transfer in Bi2Te3–Sb2Te3 nanostructures