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Cited by 41Nanofluid Flow and Heat TransferHeat Transfer and OptimizationParticle Dynamics in Fluid Flows

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Numerical investigation of nanoparticles slip mechanisms impact on the natural convection heat transfer characteristics of nanofluids in an enclosure

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Amidu, Muritala Alade, Addad, Yacine, Riahi, Mohamed Kamel, Abu-Nada, Eiyad·2021·Scientific Reports
DOI 10.1038/s41598-021-95269-zPMC PMC8333057
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Abstract

This study intends to give qualitative results toward the understanding of different slip mechanisms impact on the natural heat transfer performance of nanofluids. The slip mechanisms considered in this study are Brownian diffusion, thermophoretic diffusion, and sedimentation. This study compares three different Eulerian nanofluid models; Single-phase, two-phase, and a third model that consists of incorporating the three slip mechanisms in a two-phase drift-flux. These slip mechanisms are found to have different impacts depending on the nanoparticle concentration, where this effect ranges from negligible to dominant. It has been reported experimentally in the literature that, with high nanoparticle volume fraction the heat transfer deteriorates. Admittingly, classical nanofluid models are known to underpredict this impairment. To address this discrepancy, this study focuses on the effect of thermophoretic diffusion and sedimentation outcome as these two mechanisms turn out to be influencing players in the resulting heat transfer rate using the two-phase model. In particular, the necessity to account for the sedimentation contribution toward qualitative modeling of the heat transfer is highlighted. To this end, correlations relating the thermophoretic and sedimentation coefficients to the nanofluid concentration and Rayleigh number are proposed in this study. Numerical experiments are presented to show the effectiveness of the proposed two-phase model in approaching the experimental data, for the full range of Rayleigh number in the laminar flow regime and for nanoparticles concentration of (0% to 3%), with great satisfaction.

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Figure 1 Illustration of nanoparticle sedimentation in a quadrate enclosure.
Figure 1 Illustration of nanoparticle sedimentation in a quadrate enclosure.CC BY · PubMed Central
Figure 2 Illustration of nanoparticle slip motions: (a) thermophoresis; (b) Brownian diffusions.
Figure 2 Illustration of nanoparticle slip motions: (a) thermophoresis; (b) Brownian diffusions.CC BY · PubMed Central
Figure 3 Geometric configuration and boundary conditions.
Figure 3 Geometric configuration and boundary conditions.CC BY · PubMed Central
Figure 4 Flow Chart of the OpenFoam PIMPLE algorithm.
Figure 4 Flow Chart of the OpenFoam PIMPLE algorithm.CC BY · PubMed Central
Figure 5 Sensitivity test of the time discretization on the temperature profile at the mid-point of the computational domain using the mixture model: (a) with maximum number PIMPLE iterations equal to 3, and (b) with a variable number of PIMPLE iterations but with convergence criteria (absolute residual) for the variables set to 10–6.
Figure 5 Sensitivity test of the time discretization on the temperature profile at the mid-point of the computational domain using the mixture model: (a) with maximum number PIMPLE iterations equal to 3, and (b) with a variable number of PIMPLE iterations but with convergence criteria (absolute residual) for the variables set to 10–6.CC BY · PubMed Central
Figure 6 Models’ validation with Ho et al.4 experimental data for pure water.
Figure 6 Models’ validation with Ho et al.4 experimental data for pure water.CC BY · PubMed Central
Figure 7 Comparison of the simulation data with the experimental data using 1% nanoparticle concentration.
Figure 7 Comparison of the simulation data with the experimental data using 1% nanoparticle concentration.CC BY · PubMed Central
Figure 8 Comparison of the simulation data with the experimental data using 3% nanofluid.
Figure 8 Comparison of the simulation data with the experimental data using 3% nanofluid.CC BY · PubMed Central
Figure 9 Isotherm (top) calculated as a dimensionless parameter (T-TC)/ΔT, Streamline (middle) calculated as dimensionless parameter uρcpL/k, and contour of volume fraction of nanoparticle (bottom) calculated as dimensionless parameter φ/φavg using the three modeling approaches with nanoparticle concentration of 1% at Ra = 1 × 106: (a) single-phase model, (b) mixture model, and (c) two-component model.
Figure 9 Isotherm (top) calculated as a dimensionless parameter (T-TC)/ΔT, Streamline (middle) calculated as dimensionless parameter uρcpL/k, and contour of volume fraction of nanoparticle (bottom) calculated as dimensionless parameter φ/φavg using the three modeling approaches with nanoparticle concentration of 1% at Ra = 1 × 106: (a) single-phase model, (b) mixture model, and (c) two-component model.CC BY · PubMed Central
Figure 10 The heat transfer characteristics of the nanofluid with increasing nanoparticle concentration at Ra = 6 × 106.
Figure 10 The heat transfer characteristics of the nanofluid with increasing nanoparticle concentration at Ra = 6 × 106.CC BY · PubMed Central
Figure 11 Comparison of the predicted slip velocities with the nanofluid velocity with the nanoparticle volume fraction of 1% at Ra = 1 × 106 at the middle plane: (a) mixture model, and (b) two-component model.
Figure 11 Comparison of the predicted slip velocities with the nanofluid velocity with the nanoparticle volume fraction of 1% at Ra = 1 × 106 at the middle plane: (a) mixture model, and (b) two-component model.CC BY · PubMed Central
Figure 12 Comparison of the proposed model with single-phase model and mixture model using the default values of settling and thermophoretic coefficients.
Figure 12 Comparison of the proposed model with single-phase model and mixture model using the default values of settling and thermophoretic coefficients.CC BY · PubMed Central
Figure 13 Volume fraction (φ/φavg) distribution of nanoparticle concentration resulting from the slip mechanisms at Ra = 6 × 106 and the average concentration of 3% using: (a) ST=0.01, (b) ST=2, (c) ST=5, (d) A=285, (e) A=50, (f) A=20.
Figure 13 Volume fraction (φ/φavg) distribution of nanoparticle concentration resulting from the slip mechanisms at Ra = 6 × 106 and the average concentration of 3% using: (a) ST=0.01, (b) ST=2, (c) ST=5, (d) A=285, (e) A=50, (f) A=20.CC BY · PubMed Central
Figure 14 (Red line) Impact of and sedimentation (A=50, ST=0.01), (blue line) thermophoretic diffusion (A=285.84, ST=0.5), (a) vertical velocity profile, (b) temperature profile at mid-plane of the cavity.
Figure 14 (Red line) Impact of and sedimentation (A=50, ST=0.01), (blue line) thermophoretic diffusion (A=285.84, ST=0.5), (a) vertical velocity profile, (b) temperature profile at mid-plane of the cavity.CC BY · PubMed Central
Figure 15 Variation of the temperature and volume fraction profiles at Ra = 6 × 106, nanoparticle concentration of 3%, A = 150.0 and ST=0.1: (a) horizontal mid-plane, and (b) vertical mid-plane.
Figure 15 Variation of the temperature and volume fraction profiles at Ra = 6 × 106, nanoparticle concentration of 3%, A = 150.0 and ST=0.1: (a) horizontal mid-plane, and (b) vertical mid-plane.CC BY · PubMed Central
Figure 16 Migration of nanoparticles due to the three slip mechanisms at A = 150.0 and ST=0.1: (a) horizontal mid-plane and (b) vertical mid-plane.
Figure 16 Migration of nanoparticles due to the three slip mechanisms at A = 150.0 and ST=0.1: (a) horizontal mid-plane and (b) vertical mid-plane.CC BY · PubMed Central
Figure 17 Local Nusselt number along the hot wall: (a) under the influence of thermophoretic diffusion, and (b) under the influence of sedimentation.
Figure 17 Local Nusselt number along the hot wall: (a) under the influence of thermophoretic diffusion, and (b) under the influence of sedimentation.CC BY · PubMed Central
Figure 18 Impact of the slip mechanisms on the nanofluid heat transfer: (a) thermophoretic diffusion, (b) sedimentation of nanoparticles.
Figure 18 Impact of the slip mechanisms on the nanofluid heat transfer: (a) thermophoretic diffusion, (b) sedimentation of nanoparticles.CC BY · PubMed Central
Figure 19 Impact of the calibrated sedimentation and thermophoretic parameters.
Figure 19 Impact of the calibrated sedimentation and thermophoretic parameters.CC BY · PubMed Central
Figure 20 Computation cost of the three models.
Figure 20 Computation cost of the three models.CC BY · PubMed Central

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Cited by

Metadata

Authors
Amidu, M. A., Addad, Y., Riahi, M. K., & Abu-Nada, E.
Affiliations
Khalifa University of Science and Technology (AE)
Corresponding author
Addad, Yacine
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2021-08-03
Volume
11
Issue
1
Pages
15678-15678
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-021-95269-z
PMC
PMC8333057
OpenAlex
W3190379671
Cited by
41
References
0
Citations by year
2026: 5 · 2025: 6 · 2024: 9 · 2023: 11 · 2022: 10
FWCI
2.28
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Emirates Nuclear Technology Center (8434000360)
Topics
  • Physical Sciences › Chemical Engineering › Fluid Flow and Transfer Processes › Nanofluid Flow and Heat Transfer
  • Physical Sciences › Engineering › Mechanical Engineering › Heat Transfer and Optimization
  • Physical Sciences › Chemical Engineering › Fluid Flow and Transfer Processes › Particle Dynamics in Fluid Flows
Keywords
nanofluids, natural convection, Brownian diffusion, thermophoretic diffusion, sedimentation, nanoparticle volume fraction, laminar flow

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