Natural convection of nanofluids in enclosures with low aspect ratios

Bouhalleb, Mefteh; Abbassi, Hassan

doi:10.1016/j.ijhydene.2014.04.069

Cited by 57 publications

(15 citation statements)

References 32 publications

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“…In this study, the values of the nanoparticle parameters R np , Le nf , and NA nf are taken in the range of 1∼10, 1∼100, and 1∼10, respectively. According to several published articles and Table , these ranges of the governing parameters satisfy for most of the nanofluids. For a choice of parametric values taken, it is obtained that σ i is for all time zero showing that the stability of the considered problem is stationary.…”

Section: Resultsmentioning

confidence: 99%

Numerical solution of the onset of Buoyancy‐driven nanofluid convective motion in an anisotropic porous medium layer with variable gravity and internal heating

Yadav

2020

Heat Trans

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The onset of buoyancy-driven convective motion in a nanofluid saturated anisotropic porous medium layer is examined numerically in the occurrence of uniform internal heat source under the variable gravity field.Three kinds of gravity force variation functions: (a) G(z) = −z (linear), (b) G(z) = −z 2 (parabolic), and (c) G(z) = −z 3 (cubic) are considered. Wide-range governing parameters impacts are inspected on the beginning of convective motion under the zero nanoparticle flux situation at the boundaries using the higher term Galerkin technique. It is established that the thermal anisotropy parameter η and the gravity variation parameter λ delay the arrival of convective motion, while the mechanical anisotropy parameter ξ, the internal heating parameter Hs, the nanoparticle Rayleigh-Darcy number R np , the modified diffusivity ratio NA nf , and the modified nanofluid Lewis number Le nf rapid the start of convective motion. The size of the convective cells reduces on raising the internal heating parameter Hs, while the gravity variation parameter λ, the mechanical anisotropy parameter ξ, the thermal anisotropy parameter η, the nanoparticle Rayleigh-Darcy number R np , the modified diffusivity ratio NA nf , and the modified nanofluid Lewis number Le nf amplify the dimension of the convective cells. It is also detected that the arrangement is more unstable for case (c), while it is more stable for case (a). K E Y W O R D Sanisotropic porous medium, convective instability, internal heating and variable gravity, nanofluids 1 | INTRODUCTION Anisotropy in porous medium plays in role due to asymmetric arrangement of porous matrix or fibers. Rock, soils, and fibrous insulating materials are good examples of anisotropic porous medium. Thermal convective motion in fluid-flooded anisotropic porous medium with different geometries and different configuration has been a topic of great attention by the scientific community in the earlier few decades due to their widespread uses in nature and engineering such as the pollutant transport in saturated soils, cooling of electronic devices, the underground disposal of nuclear discarded, heat exchangers, fuel drilling, nuclear and packed bed reactors, chemical and food processing, and so forth. 1-12 Different working fluid can be utilized for these systems but utilizing the nanoscale solid particles diffused in working fluids coined by Choi and Eastman, 13 which are called nanofluids, is the useful method to reduce the size and advance the performance of such arrangements by improving their heat transfer characteristics. [14][15][16][17][18] Nguyen et al 19 experimentally examined the heat transport characteristics of Al 2 O 3 -H 2 O nanofluid for relevance in a closed cooling structures such as microprocessors or other heated electronic devices. They observed a 40% enhanced in Nusselt number via Al 2 O 3 nanoparticles at 6.8% concentration when compared with water. Very recently, Yadav 20 studied the convective heat transport of nanofluids in porous enclosures and proved that the he...

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Section: Resultsmentioning

confidence: 99%

Numerical solution of the onset of Buoyancy‐driven nanofluid convective motion in an anisotropic porous medium layer with variable gravity and internal heating

Yadav

2020

Heat Trans

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“…Then, for obtaining the accuracy of simulation in modeling the inclined enclosure containing nanofluid with boundary conditions based on boundary conditions of present research, the validation has been done according to the numerical study of Bouhalleb and Abbassi for the laminar natural convection of water/CuO nanofluid with 4% volume fraction in the inclined rectangular enclosure with an aspect ratio of 0.1 and a Ra number of 10 7 , and the results are indicated in Figure . The validation results of the present study are in good agreement with the results of Dixit and Babu and Bouhalleb and Abbassi …”

Section: Solving Procedure Results Independency From the Grid And Vamentioning

confidence: 99%

“…Also, the general pattern of flow in the present study is quite similar to the papers by Dixit and Babu 4 (Figure 4), but there is a little deviation between both results in terms of isotherms because in the present study and in the study by Dixit and Babu, 4 the finite volume method and the lattice Boltzmann method have been used, respectively. Then, for obtaining the accuracy of simulation in modeling the inclined enclosure containing nanofluid with boundary conditions based on boundary conditions of present research, the validation has been done according to the numerical study of Bouhalleb and Abbassi 29 for the laminar natural convection of water/CuO nanofluid with 4% volume fraction in the inclined rectangular enclosure with an aspect ratio of 0.1 and a Ra number of 10 7 , and the results are indicated in Figure 5. The validation results of the present study are in good agreement with the results of Dixit and Babu 4 and Bouhalleb and Abbassi.…”

Section: Solving Procedure Results Independency From the Grid And mentioning

confidence: 99%

“…The validation results of the present study are in good agreement with the results of Dixit and Babu 4 and Bouhalleb and Abbassi. 29 T A B L E 2 Thermophysical properties of water and Ag at 300 K 33 34 Radial basis function artificial neural networks (RBF-ANN) is one of the favorable neural networked, which has simple implementation with good generalization and strong tolerance to input noise. It was first introduced by Broomhead and Lowe 35 in 1988.…”

Section: Solving Procedure Results Independency From the Grid And mentioning

confidence: 99%

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Study of flow field, heat transfer, and entropy generation of nanofluid turbulent natural convection in an enclosure utilizing the computational fluid dynamics‐artificial neural network hybrid method

Sepehrnia

Sheikhzadeh

Abaei

et al. 2019

Heat Trans. Asian Res.

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In this study, the turbulent natural convection of Ag‐water nanofluid in a tall, inclined enclosure has been investigated. The main objective of this study is finding the optimized angle of the enclosure with operational boundary condition in cooling from ceiling utilizing the computational fluid dynamics‐artificial neural network (CFD‐ANN) hybrid method, which has not been noticed in previous studies. To achieve this, we proposed two approaches. First, the simulations have been done with a deviation angle of 0 to 90° by using water and Ag‐water nanofluid. And second, a new prediction approach is proposed based on radial basis function artificial neural networks (RBF‐ANN) to predict the mean Nusselt number and entropy generation with the variation of Rayleigh numbers, deviation angles, and volume fractions as inputs. The results from the first approach indicate that the Rayleigh number has a considerable function in the determination of optimized angle. The results from the second approach, which used the first approach simulation results as training data set, could predict the mean Nusselt number and entropy generation with 1.4577e−022 and 1.552e−015 mean square error, respectively. Moreover, a new set of data for Rayleigh numbers, deviation angles, and volume fractions were used to test the performance of the prediction model, which shows promising and superior prospects for RBF‐ANN.

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“…By increasing Ra, the heat transfer near the heating wall will be intensified, whereas Nu will be reduced by increasing the aspect ratio, which coincided with the research of Bouhalleb. 61 Additionally, the partial enlarged view shows that nanofluids with 1.0 wt% nanoparticles have the largest local Nu. Figure 12 shows the average Nu along the heating wall.…”

Section: Ncht Of Nanofluidsmentioning

confidence: 98%

Regulation of natural convection heat transfer for SiO₂–solar salt nanofluids by optimizing rectangular vessels design

Zhang

Tan

et al. 2020

Asia-Pacific J Chem Eng

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Natural convection heat transfer of molten salt is widely used in concentrated solar plants, such as the solar receiver, the single‐tank thermal energy storage system, and so forth. Meanwhile, adding nanoparticles into molten salts to form nanofluids can obviously improve the thermal properties of the working medium. However, the heat transfer performance of the molten salt‐based nanofluids has not been investigated extensively, and the action mechanism between base fluids and nanoparticles is still unclear. In the present work, a lattice Boltzmann model considering fluid and nanoparticles as two different phases was developed, and various interactions were taken into consideration. Meanwhile, the effects of nanoparticle concentrations, aspect ratios of the rectangular vessel, and Ra on natural convection heat transfer of solar salt‐based SiO2 nanofluids were analysed. The results show that specific heat capacity contributes substantially to heat transfer for all aspect ratios, and the maximum enhancement of natural convection heat transfer is obtained with a mass fraction of 1.0%. However, increase in Ra intensifies the effect of viscosity and weakens the heat transfer enhancement. Through interaction analysis, it indicated that nanoparticles tend to be driven to the top area of the rectangular vessel by temperature difference, driving force, and drag force. Meanwhile, a Nu enhancement contour was provided to optimize the design of a single energy storage tank.

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Natural convection of nanofluids in enclosures with low aspect ratios

Cited by 57 publications

References 32 publications

Numerical solution of the onset of Buoyancy‐driven nanofluid convective motion in an anisotropic porous medium layer with variable gravity and internal heating

Numerical solution of the onset of Buoyancy‐driven nanofluid convective motion in an anisotropic porous medium layer with variable gravity and internal heating

Study of flow field, heat transfer, and entropy generation of nanofluid turbulent natural convection in an enclosure utilizing the computational fluid dynamics‐artificial neural network hybrid method

Regulation of natural convection heat transfer for SiO₂–solar salt nanofluids by optimizing rectangular vessels design

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Natural convection of nanofluids in enclosures with low aspect ratios

Cited by 57 publications

References 32 publications

Numerical solution of the onset of Buoyancy‐driven nanofluid convective motion in an anisotropic porous medium layer with variable gravity and internal heating

Numerical solution of the onset of Buoyancy‐driven nanofluid convective motion in an anisotropic porous medium layer with variable gravity and internal heating

Study of flow field, heat transfer, and entropy generation of nanofluid turbulent natural convection in an enclosure utilizing the computational fluid dynamics‐artificial neural network hybrid method

Regulation of natural convection heat transfer for SiO2–solar salt nanofluids by optimizing rectangular vessels design

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Regulation of natural convection heat transfer for SiO₂–solar salt nanofluids by optimizing rectangular vessels design