Hybrid nanofluids for heat transfer applications – A state-of-the-art review

Huminic, Gabriela; Huminic, Angel

doi:10.1016/j.ijheatmasstransfer.2018.04.059

Cited by 351 publications

(133 citation statements)

References 74 publications

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“…To solve the above equations, we need the thermophysical properties of the nanoliquids. Density, specific heat, volumetric expansion coefficient, and electrical conductivity were calculated through the relations presented in Table 2 [18][19][20]38,39]. Table 2.…”

Section: Governing Equationsmentioning

confidence: 99%

“…For the stable distribution of nanoparticles in the closed chambers, energy transport can be essentially improved compared to the absence of nanoparticles (i.e., base fluid only). It should be noted that nanofluids are used in different engineering applications such electronics cooling, solar collectors, heat exchangers, building insulation systems, and so on [18][19][20]. Khanafer et al [21] are the first who numerically simulated the thermal transmission of the nanoliquid within the square-shaped chamber.…”

Section: Introductionmentioning

confidence: 99%

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Free Convection of Hybrid Nanofluids in a C-Shaped Chamber under Variable Heat Flux and Magnetic Field: Simulation, Sensitivity Analysis, and Artificial Neural Networks

et al. 2019

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In the present investigation, the free convection energy transport was studied in a C-shaped tilted chamber with the inclination angle α that was filled with the MWCNT (MultiWall Carbon Nanotubes)-Fe3O4-H2O hybrid nanofluid and it is affected by the magnetic field and thermal flux. The control equations were numerically resolved by the finite element method (FEM). Then, using the artificial neural network (ANN) combined with the particles swarm optimization algorithm (PSO), the Nusselt number was predicted, followed by investigating the effect of parameters including the Rayleigh number (Ra), the Hartmann number (Ha), the nanoparticles concentration (φ), the inclination angle of the chamber (α), and the aspect ratio (AR) on the heat transfer rate. The results showed the high accuracy of the ANN optimized by the PSO algorithm in the prediction of the Nusselt number such that the mean squared error in the ANN model is 0.35, while in the ANN model, it was optimized using the PSO algorithm (ANN-PSO) is 0.22, suggesting the higher accuracy of the latter. It was also found that, among the studied parameters with an effect on the heat transfer rate, the Rayleigh number and aspect ratio have the greatest impact on the thermal transmission intensification. The obtained data also showed that a growth of the Hartmann number illustrates a reduction of the Nusselt number for high Rayleigh numbers and the heat transfer rate is almost constant for low Rayleigh number values.

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Section: Governing Equationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Free Convection of Hybrid Nanofluids in a C-Shaped Chamber under Variable Heat Flux and Magnetic Field: Simulation, Sensitivity Analysis, and Artificial Neural Networks

et al. 2019

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“…The thermal performance of the plate heat exchanger (PHE) can be improved by providing grooves on the plate surface 3 . The thermal performance of the heat exchanger can also be upgraded by using hybrid nanofluids (HyNfs) 4‐6 in place of base fluid due to adjustable properties suitable for distinct purposes. These facts motivated to perform research with HyNfs in the plate heat exchanger.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation of Al₂O₃–MgO hot hybrid nanofluid in a plate heat exchanger

Bhattad

2020

Heat Trans

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Exergy-energy analysis of the plate heat exchanger is experimentally performed with different Al 2 O 3 -MgO hybrid nanofluid (HyNf) as a hot fluid. There were six combinations of fluids, namely, deionized (DI) water, ethylene glycol-DI water brine (1:9 volume ratio), propylene glycol-DI water brine (1:9 volume ratio), base fluids and their respective Al 2 O 3 -MgO (4:1 particle volume ratio) HyNfs of 0.1% total volume concentration. The effects of different flow rates and hot inlet temperatures on the heat transfer rate, heat transfer coefficient, pump work, irreversibility, and performance index (PI) are investigated. It is witnessed that the heat transfer rate, heat transfer coefficient, pump work, and irreversibility enhances with the flow rate and nanoparticle suspension. While the PI declines with a rise in the flow rate, the heat transfer rate, heat transfer coefficient, PI, and irreversibility rise up maximum for MgO-alumina (1:4) DI water HyNf upto 11.8%, 31.7%, 11.1%, and 4.05%, respectively. The pump work enhances upto 1.6% for MgO-alumina (1:4)/EG-DI water (1:9) HyNf. K E Y W O R D Sheat transfer coefficient, heat transfer rate, hybrid nanofluid, irreversibility, performance index, plate heat exchanger Abbreviations: Al 2 O 3 , aluminum oxide/alumina particles; CTAB, cetyl trimethyl ammonium bromide; DI, deionized water; EG, ethylene glycol; HyNf, hybrid nanofluid; L/min, litre per minute; MgO, magnesium oxide/magnesia particles; MWCNT, multi-walled carbon nanotube particles; PG, propylene glycol; PHE, plate heat exchanger; PI, performance index; SiC, silicon carbide particles.

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“…Despite having all these superior properties, the stability of nanofluids is still a challenge in the practical field of nanofluids because the nanoparticles tend to be agglomerated or sedimented causing pressure drops because of robust Van der Waals attraction among particles [14,15]. It leads to the reduction of stability as well as thermal properties of nanofluids [16][17][18] as stability directly correlated with the thermal properties [19,20]. Hence, the stability of the nanofluids is an essential factor for sustaining the enhanced thermal features [19,21].…”

Section: Introductionmentioning

confidence: 99%

“…It leads to the reduction of stability as well as thermal properties of nanofluids [16][17][18] as stability directly correlated with the thermal properties [19,20]. Hence, the stability of the nanofluids is an essential factor for sustaining the enhanced thermal features [19,21]. So, stability analysis is the prior most work in the field of nanofluids.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation on the Stability of 40% Ethylene Glycol Based TiO2-Al2O3 Hybrid Nanofluids

Urmi¹,

Rahman²,

Azmi³

et al. 2020

ARFMTS

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This paper is presented to investigate experimentally on the stability of 40% ethylene glycol-based TiO2-Al2O3 hybrid nanofluids. Recently, the research is more highlighted on the thermophysical-properties of nanofluids. Hence, the stability of the hybrid nanofluids thoroughly assessed in this research work. The study uses the two-step method for preparing 40% ethylene glycol-based TiO2-Al2O3 hybrid nanofluids. The experiment is carried out for the various combination of mixture ratios including 20:80, 40:60, 50:50, 60:40 and 80:20 of TiO2-Al2O3 nanoparticles with a volume concentration of 0.1%. The stability assessment of hybrid nanofluids is accomplished through visualisation effect, transmission electronic microscopic observation, UV-Vis spectrophotometry and zeta potential value from particle size analyser. The findings show the optimum mixing ratios of TiO2-Al2O3 nanoparticles in terms of stability which is further confirmed by Zeta potential and absorbency from UV-Vis spectrophotometry. The results from the study reveal that 80:20 ratio of TiO2-Al2O3 nanoparticles possesses the best uniformity for over 21 days without any noticeable settlement of particles in the colloidal suspension. Moreover, 50:50 and 60:40 ratios show modest stability for almost two weeks while 20:80 and 40:60 ratios of TiO2-Al2O3 nanoparticles show minimum stability along with rapid sedimentation in the dispersion. However, it is also evident that the optimum mixing ratio of TiO2-Al2O3 hybrid nanofluids has excellent stability which will lead to further study on the thermal properties of nanofluids and finally motivate engineers to the real-life application of nanofluids.

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Hybrid nanofluids for heat transfer applications – A state-of-the-art review

Cited by 351 publications

References 74 publications

Free Convection of Hybrid Nanofluids in a C-Shaped Chamber under Variable Heat Flux and Magnetic Field: Simulation, Sensitivity Analysis, and Artificial Neural Networks

Free Convection of Hybrid Nanofluids in a C-Shaped Chamber under Variable Heat Flux and Magnetic Field: Simulation, Sensitivity Analysis, and Artificial Neural Networks

Experimental investigation of Al₂O₃–MgO hot hybrid nanofluid in a plate heat exchanger

Experimental Investigation on the Stability of 40% Ethylene Glycol Based TiO2-Al2O3 Hybrid Nanofluids

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Hybrid nanofluids for heat transfer applications – A state-of-the-art review

Cited by 351 publications

References 74 publications

Free Convection of Hybrid Nanofluids in a C-Shaped Chamber under Variable Heat Flux and Magnetic Field: Simulation, Sensitivity Analysis, and Artificial Neural Networks

Free Convection of Hybrid Nanofluids in a C-Shaped Chamber under Variable Heat Flux and Magnetic Field: Simulation, Sensitivity Analysis, and Artificial Neural Networks

Experimental investigation of Al2O3–MgO hot hybrid nanofluid in a plate heat exchanger

Experimental Investigation on the Stability of 40% Ethylene Glycol Based TiO2-Al2O3 Hybrid Nanofluids

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Experimental investigation of Al₂O₃–MgO hot hybrid nanofluid in a plate heat exchanger