Accurate basis of comparison for convective heat transfer in nanofluids

Haghighi, Ehsan Bitaraf; Saleemi, Mohsin; Nikkam, Nader; Khodabandeh, Rahmatollah; Toprak, Muhammet S.; Muhammed, Mamoun; Palm, Björn

doi:10.1016/j.icheatmasstransfer.2014.01.002

Cited by 51 publications

(31 citation statements)

References 21 publications

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“…The left part of Fig. 7 shows for the TiO 2 -based systems with a λ p /λ bf ratio of about 20 that most of the experimental data in literature [6,62,77,78] associated with particle volume fractions up to 0.06 provide moderate enhancement factors which scatter around the HC model [18] and our model [21]. Only the data obtained by Reddy and Rao [79] with the steady-state concentric-cylinder method with a stated uncertainty of 0.6 % and especially those obtained by Maheshway et al [80] with a hot-wire method of unknown uncertainty show clearly larger enhancement factors.…”

Section: Data Comparisonmentioning

confidence: 80%

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: Data Comparisonmentioning

confidence: 80%

Effective Thermal Conductivity of Nanofluids: Measurement and Prediction

et al. 2020

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“…Haghighi et al [82] performed experiments to measure thermal conductivity and viscosity of alumina zirconia, titania at 20°C. They concluded that heat transfer coefficients of the nanofluids can be determined using correlations such as Shah in accuracy of ±15%.…”

Section: Studies With Various Metallic Nanoparticlesmentioning

confidence: 99%

Heat transfer augmentation in a tube using nanofluids under constant heat flux boundary condition: A review

Singh

Gupta

2016

Energy Conversion and Management

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“…However, the three other models are not suitable here. As known, the larger dynamic viscosity causes more pumping power consumption, which might counterbalance the benefits of greater thermal conductivity [36]. Thus, the tradeoff between these two properties is important when considering nanofluids as working fluids.…”

Section: Thermophysical Property Measurements Of Nanofluidsmentioning

confidence: 99%