Elsevier

Thermochimica Acta

Volume 661, 10 March 2018, Pages 84-97
Thermochimica Acta

Measurement of the thermal conductivity of SiO2 nanofluids with an optimized transient hot wire method

https://doi.org/10.1016/j.tca.2018.01.008Get rights and content

Highlights

  • Detailed error analysis regarding THW for thermal conductivity measurement was made.

  • Optimized measuring parameters of THW were acquired.

  • Thermal conductivity and particle size distribution of SiO2 nanofluids were measured.

  • Thermal conductivity enhancement for EG is much higher than DW.

Abstract

Thermal conductivity enhancement of nanofluids can be affected by measurement deviation and particle size distribution. In the present work, deionized water (DW) and ethylene glycol (EG) based nanofluids were made and characterized. A nanofluid thermal conductivity measurement system founded on transient hot wire method was built up and a comprehensive analysis regarding measurement error was made for the two base fluids. The proper hot wire working current and the measurement time were acquired to decrease the measurement error caused by non-constant heating power and natural convection. Then, the nanofluid thermal conductivity was measured with optimized measuring parameters. It was found that the thermal conductivity increases 3.2% and 9.6% for 0.5 vol.% SiO2-EG and 1.0 vol.% SiO2-EG, higher than the result for DW based nanofluids (1.0% and 3.4%). This may be attributed to the higher value of λBrownian and the difference in particle shape distribution.

Introduction

As a new heat transfer medium with high thermal conductivity, nanofluid has aroused increasing attention since the concept was firstly proposed in 1995 by Choi et al. [1]. Then nanoparticles of metals or oxides began to be used as additives to traditional heat transfer fluids (water, alcohol, heat conduction oil, etc.) to form uniform and stable nanofluids. Nanofluid has much higher heat-conducting capability than conventional fluid. It’s available for improving the rate of heat transfer and reducing the dimensions of heat exchanger. And thus nanofluid has a promising prospect in many industrial applications.

Nanofluid thermal conductivity enhancement is considered to be closely associated with the characteristics of nano-particles and the type of base fluid [[2], [3]]. Much attention has been paid to enhance the nanofluid thermal conductivity in previous research. Different nanoparticles were applied in making nanofluids, including metal oxides (CuO, Al2O3, SiO2, TiO2, ZrO2, etc.), new carbon materials with high thermal conductivity (carbon nanotube and graphene, etc.) and hybrid nanoparticles [4]. Masuda et al. [5] used ultrasonic dispersion method to prepare water based nanofluids and found that the base fluid thermal conductivity would rise by 30% and 10% with the addition of 4.0 vol.% Al2O3 and TiO2 respectively. Sundar et al. [6] studied the magnetic Fe3O4 nanofluids and reported that 2.0 vol.% Fe3O4 nanofluid prepared by precipitation method can increase 25% thermal conductivity at 20 °C. Carbon based nano-materials were also used to prepare nanofluids and showed extraordinary enhancement effect on thermal conductivity in literatures [[7], [8], [9]]. Wusiman et al. [8] prepared water based MWCNT nanofluids with addition of SDBS as a dispersant. They found that the thermal conductivity enhanced 2.8% when 0.5 wt.% CNTs and 0.25 wt.% SDBS were added to water. Chen and Xie [9] prepared double and single walled carbon nanofluids without dispersant addition and claimed that the nanotubes with smaller diameter can contribute to higher thermal conductivity.

Base fluid is also of vital importance to the thermal conductivity increment. Compared with deionized water (DW), ethylene glycol (EG) has a longer temperature range of liquid state, and EG-based nanofluids have attracted the attention of researchers due to its potential in refrigeration and heat transfer engineering [10]. Lee et al. [11] prepared CuO-EG nanofluids and found that with the addition of 4.0 vol.% CuO (particle size of 23.6 nm) the thermal conductivity presented an 20% increase. Agarwal et al. [12] investigated the influence factors on the thermal conductivity of Al2O3 nanofluid. It was reported that the EG base fluid had a great impact on thermal conductivity increase when nanoparticle concentration was kept unchanged. When 0.5 vol.% Al2O3 nanoparticles were added in, the thermal conductivity was increased 3.5% and 5.0% for water base fluid and EG base fluid respectively.

There have been many published data on nanofluid thermal conductivity measurement. These results, however, differ from one another even for one type of nanofluid with similar volume concentration and primary particle size. Table 1 lists the thermal conductivity enhancement results from literatures (water based Al2O3 nanofluids). Perhaps part of the reason for the deviation was that while the primary particle sizes are similar, the real particle sizes in nanofluids are distinct from each other due to the particle agglomeration and the difference in preparation method (ultrasonic time, dispersant type, etc.). In fact, the real particle size of nanofluids should be measured for the better understanding of the thermal conductivity enhancement effect. Another influence factor lies in the measurement deviation [13]. How to precisely obtain the nanofluid thermal conductivity is where the shoe pinches. Various approaches are used to measure nanofluid thermal conductivity: transient hot wire method (THW) [14], parallel-plate technique (STPPH) [15], coaxial cylinders method (SSCCM) [16] and temperature oscillation technique (TOT) [17], among which THW is one of the most widely used methods due to its short measurement time and convenient operation.

The general idea of THW method is to generate heat in a thin metallic wire (often called hot wire). The hot wire is immersed in the fluid where it acts as heat source and thermometer. The temperature rise rate of the hot wire can reflect the fluid thermal conductivity [18]. The THW method is widely used in the thermal conductivity measurement of liquid, gases, etc. Coated with a thin electrical insulation layer, hot wire can be applied to measure the thermal conductivity of electrically conducting liquids [[19], [20], [21]]. A few authors also did research on simultaneous measurement on liquid thermal conductivity and thermal diffusivity [[22], [23]]. Some factors in the THW method, such as natural convection and hot wire heat capacity, can influence the measurement accuracy directly. Yu et al. [24] claimed that the thickness of hot wire insulation layer showed no significant effect on the slope of ΔT-lnt curve in a relatively large time range. Shi et al. [25] investigated the effect of radiation on the measure accuracy of liquid propane, and demonstrated the radiation effect could not be neglected at 372 K. De Castro et al. [26] studied the influence of hot wire heat capacity on the thermal diffusivity measurement accuracy of liquid and gas. The proper tstart time for gas and liquid were discussed and obtained.

Recently, several papers reported the measurement accuracy about nanofluids thermal conductivity by THW method. Hong et al. [27] studied the influence of convection on EG-based 1.06 vol.% ZnO thermal conductivity measurement accuracy by THW method, and found that the thermal conductivity results calculated from different temperature ranges were remarkably different. While Lee et al. [28] found the thermal conductivity measurement accuracy for EG was not affected by natural convection during the test time range (tstart = 0 ∼ 15s, tend = 0 ∼ 20s) at a selected voltage value of 1.0 V. Then they applied the optimized measurement system with the voltage to measure the thermal conductivity of Al2O3-EG nanofluids accurately.

To improve the measurement accuracy of nanofluid thermal conductivity, detailed error analysis is needed. But as yet few papers have made detailed error analysis regarding nanofluid thermal conductivity measurement based on THW method. In the present work, a comprehensive analysis of measurement error for THW method has been made to determine the key parameters (hot wire temperature rise, measurement time range, etc.) that influence the measurement accuracy of nanofluid thermal conductivity. Then the thermal conductivity and particle size distribution measurement of two types of SiO2 nanofluid were implemented. And the effects of nanoparticle volume concentration, particle size and base fluid type on nanofluid thermal conductivity were further investigated.

Section snippets

Principle of THW method

The ideal model of THW method is built grounded on the following assumptions: (1) the hot wire is infinitely long and vertically placed in isotropic fluid. (2) The thermal conductivity of the hot wire is infinite and the heat capacity is zero. Initially, the system is thermodynamically balanced at T0. Then a constant heat flow is applied to the hot wire. The temperature rise at a radial position r conforms to the following equation:ΔT(r,t)=T(r,t)T0

According to Fourier’s heat conduction

Analysis of model error

Some deviations in thermal conductivity results derive from the model error and the random error. The model error, i.e. systematic error, is mainly caused by the difference between theoretical modeling and practical testing condition. The random error includes the error produced from the observation of physical quantities (voltage, wire length, etc.). Two base fluids, DW and EG, were applied in the error analysis of the measurement system in order to optimize the measurement parameters and

Conclusions

In the present work, a nanofluid thermal conductivity measurement system based on THW method was built up. To find out the key parameters that influence the measurement accuracy, a comprehensive analysis of system error and random error was made and the thermal conductivity of two types of SiO2 nanofluids were measured with the optimized measuring parameters. The conclusions drawn from the experimental study are as follows:

  • (1)

    Among all the model errors in the thermal conductivity measurement by

Acknowledgment

We acknowledge the financial support from the National Natural Science Foundation of China (No. 51476146, 51476145, 51606169).

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