Literature DB >> 36014668

Particle Distribution and Heat Transfer of SiO2/Water Nanofluid in the Turbulent Tube Flow.

Ruifang Shi1, Jianzhong Lin2, Hailin Yang1.   

Abstract

In order to clarify the effect of particle coagulation on the heat transfer properties, the governing equations of nanofluid together with the equation for nanoparticles in the SiO2/water nanofluid flowing through a turbulent tube are solved numerically in the range of Reynolds number 3000 ≤ Re ≤ 16,000 and particle volume fraction 0.005 ≤ φ ≤ 0.04. Some results are validated by comparing with the experimental results. The effect of particle convection, diffusion, and coagulation on the pressure drop ∆P, particle distribution, and heat transfer of nanofluid are analyzed. The main innovation is that it gives the effect of particle coagulation on the pressure drop, particle distribution, and heat transfer. The results showed that ∆P increases with the increase in Re and φ. When inlet velocity is small, the increase in ∆P caused by adding particles is relatively large, and ∆P increases most obviously compared with the case of pure water when the inlet velocity is 0.589 m/s and φ is 0.004. Particle number concentration M0 decreases along the flow direction, and M0 near the wall is decreased to the original 2% and decreased by about 90% in the central area. M0 increases with increasing Re but with decreasing φ, and basically presents a uniform distribution in the core area of the tube. The geometric mean diameter of particle GMD increases with increasing φ, but with decreasing Re. GMD is the minimum in the inlet area, and gradually increases along the flow direction. The geometric standard deviation of particle diameter GSD increases sharply at the inlet and decreases in the inlet area, remains almost unchanged in the whole tube, and finally decreases rapidly again at the outlet. The effects of Re and φ on the variation in GSD along the flow direction are insignificant. The values of convective heat transfer coefficient h and Nusselt number Nu are larger for nanofluids than that for pure water. h and Nu increase with the increase in Re and φ. Interestingly, the variation in φ from 0.005 to 0.04 has little effect on h and Nu.

Entities:  

Keywords:  SiO2/water; heat transfer; numerical simulation; particle distribution; pressure drop; turbulent tube flow

Year:  2022        PMID: 36014668      PMCID: PMC9414640          DOI: 10.3390/nano12162803

Source DB:  PubMed          Journal:  Nanomaterials (Basel)        ISSN: 2079-4991            Impact factor:   5.719


  7 in total

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Authors:  Ravi Prasher; Patrick E Phelan; Prajesh Bhattacharya
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2.  Thermal conductivity and particle agglomeration in alumina nanofluids: experiment and theory.

Authors:  Elena V Timofeeva; Alexei N Gavrilov; James M McCloskey; Yuriy V Tolmachev; Samuel Sprunt; Lena M Lopatina; Jonathan V Selinger
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4.  Mathematical analysis of COVID-19 via new mathematical model.

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Journal:  Chaos Solitons Fractals       Date:  2020-12-26       Impact factor: 5.944

5.  Forced Convective Heat Transfer Coefficient Measurement of Low Concentration Nanorods ZnO-Ethylene Glycol Nanofluids in Laminar Flow.

Authors:  Md Shah Alam; Bodrun Nahar; Md Abdul Gafur; Gimyeong Seong; Muhammad Zamir Hossain
Journal:  Nanomaterials (Basel)       Date:  2022-05-05       Impact factor: 5.076

6.  Analysis of Heat Transfer Characteristics of a GnP Aqueous Nanofluid through a Double-Tube Heat Exchanger.

Authors:  Uxía Calviño; Javier P Vallejo; Matthias H Buschmann; José Fernández-Seara; Luis Lugo
Journal:  Nanomaterials (Basel)       Date:  2021-03-25       Impact factor: 5.076

  7 in total

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