Thermal conductivity of CuO–DI water nanofluids using 3-ω measurement technique in a suspended micro-wire

Karthik, R.; Nagarajan, R.; Raja, B.; Damodharan, P.

doi:10.1016/j.expthermflusci.2012.01.006

Cited by 46 publications

(20 citation statements)

References 25 publications

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“…Based on a proper application of the technique, the method allows for an absolute and fast measurement of the thermal conductivity with an expanded uncertainty of about 2 % [6]. Other transient methods including the hot-disk instrument [24,25], the temperature-oscillation method [15,26], or the 3ω-method [27,28] have a limited theoretical basis and often require calibration [5]. Furthermore, the presence of advection during the measurement may affect the obtained effective thermal conductivities.…”

Section: Introductionmentioning

confidence: 99%

“…Another imbalance applies to the systems studied experimentally, where the focus lies on nanofluids with particles of relatively large thermal conductivities such as metal oxide particles or carbon nanotubes; see, e.g., Refs. [5,6,16,22,27]. Only a few experimental studies on the effective thermal conductivity of nanofluids where the particles show similar or smaller thermal conductivities than the base fluid are available [31,[33][34][35][36][37].…”

Section: Introductionmentioning

confidence: 99%

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Effective Thermal Conductivity of Nanofluids: Measurement and Prediction

et al. 2020

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In the present study, the effective thermal conductivity of nanoparticle dispersions, so-called nanofluids, is investigated experimentally and theoretically. For probing the influence of the nanoparticles on the effective thermal conductivity of dispersions with water as liquid continuous phase, nearly spherical and monodisperse titanium dioxide (TiO 2 ), silicon dioxide (SiO 2 ), and polystyrene (PS) nanoparticles with strongly varying thermal conductivities were used as model systems. For the measurement of the effective thermal conductivity of the nanofluids with particle volume fractions up to 0.31, a steady-state guarded parallel-plate instrument was applied successfully at temperatures between (298 and 323) K. For the same systems, dynamic light scattering (DLS) was used to analyze the collective translational diffusion, which provided information on the dispersion stability and the distribution of the particle size as essential factors for the effective thermal conductivity. The measurement results for the effective thermal conductivity show no temperature dependency and only a moderate change as a function of particle volume fraction, which is positive or negative for particles with larger or smaller thermal conductivities than the base fluid. Based on these findings, our theoretical model for the effective thermal conductivity originally developed for nanofluids containing fully dispersed particles of large thermal conductivities was revisited and also applied for a reliable prediction in the case of particles of relatively low thermal conductivities.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effective Thermal Conductivity of Nanofluids: Measurement and Prediction

et al. 2020

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“…He used the nanofluid for optimization of thermal conductivity. Since then there have been several experimental studies over the thermal conductivity analysis of different nanoparticles in various base fluids [5,[7][8][9].…”

Section: Background Knowledgementioning

confidence: 99%

“…By looking at thermal conductivity improvement, other researchers came up with different ideas and formulations for utilization of this technique in various fields of science. Today, nanofluids are being used in biological, pharmaceuticals and medicine [10], engineering [7], lubrication industries [11,12]. The major work on experimental side in all these industries has been carried out; however, these experiments of nanofluid require high skilled labour and expensive equipment.…”

Section: Background Knowledgementioning

confidence: 99%

Problems Faced While Simulating Nanofluids

Loya¹

2017

Nanofluid Heat and Mass Transfer in Engineering Problems

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Problems are faced when something is already been adopted for a considerable amount of time-here the problem that is discussed is related with nanofluids. The nanofluids have been considered for different engineering applications since last three decades; however, the work on its simulation has been started since last two decades. With the time, nanofluid simulations are increasing as compared to experimental testing. Researchers conducting nanofluid simulations do find difficulties and problems while trying to simulate this system. In addition to this, most of the time researchers are unaware of some basic problems and they find themselves stuck in relentless difficulties. Most of the time, these problems are very basic and can waste a lot of useful time of a research. Therefore, this chapter introduces some fundamental problems which a researcher can find while simulating nanofluids and with a simple way of dealing with it. Moreover, the chapter withholds lots of information regarding the way to design and to model a nanofluid system. Not only this, it also tends to elaborate the nanofluid simulation methodology in a precise manner. Moreover, the literature shows that nanofluid simulation has gained high consideration since last two decades, as experimental techniques are out of reach for everyone. In addition to experimental techniques, they are expensive, time-consuming and require high skills. However, it seems the simulation is picking pace with the due time and is considerably being adopted by the expertise dealing with nanofluids. This opens a high prospect of simulating nanofluids in future. Nevertheless, it seems there will be user-friendly software to conduct nanofluid simulations. Finally, issues and their resolution have also been conveyed which is the main aspect of this topic.

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“…[1][2][3][4][5][6] Such nanofluids have been prepared by dispersing nanoparticles in a vast diversity of fluids, such as water, oils, ethylene glycol, and glycerol. [7][8][9] The thermal properties of these nanofluids have been widely studied, and it is now well established that the addition of nanoparticles to base fluids greatly enhances their thermal conductivity.…”

Section: Introductionmentioning

confidence: 99%

Impedance Spectroscopy of Nanofluids based on Multiwall Carbon Nanotubes

Tagmouti

Bouzit

Costa

et al. 2015

Spectroscopy Letters

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This work is a contribution to the understanding of the dielectric properties of nanofluids prepared by dispersing multiwalled carbon nanotubes in transformer oil. The dielectric measurements were carried out in the frequency range 100 Hz-1 MHz at constant temperature, T ¼ 300 K, for several volume fractions of the nanotubes in the base fluid. A relaxation phenomenon was induced in the nanofluid comparing to the base fluid. In addition, both the real and imaginary part of the dielectric permittivity changed with volume fraction of the nanotubes. These results suggest that the presence of the nanotubes greatly affect the dielectric properties of the oil as a result of polarization phenomenon induced by these nanoparticles.It was found that the measured effective dielectric permittivity follows the empirical Havriliak-Negami model. Nevertheless to take into account the electrode polarization effects, we rewrote this model, with a new term, which fits accurately the experimental data.

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Thermal conductivity of CuO–DI water nanofluids using 3-ω measurement technique in a suspended micro-wire

Cited by 46 publications

References 25 publications

Effective Thermal Conductivity of Nanofluids: Measurement and Prediction

Effective Thermal Conductivity of Nanofluids: Measurement and Prediction

Problems Faced While Simulating Nanofluids

Impedance Spectroscopy of Nanofluids based on Multiwall Carbon Nanotubes

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