Numerical study of natural convection in a square cavity under non-boussinesq conditions

Hamimid, Saber; Guellal, Messaoud; Bouafia, Madiha

doi:10.2298/tsci130810084h

Cited by 13 publications

(9 citation statements)

References 9 publications

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“…The following assumptions are adopted for simplification purpose: -Since the temperature differences of the studied conditions are not high (most less than 100 ˚C), Boussinesq assumption should be adopted for the approximation of air density [26]. -The wood is actually porous medium.…”

Section: Mathematical Descriptionmentioning

confidence: 99%

Comparison study of CFD and artificial neural networks in predicting temperature fields induced by natural convention in a square enclosure

Zhou

Liu

et al. 2019

THERM SCI

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Natural convection in an enclosure is a classical problem in heat transfer field. In this study, natural convection induced by the heat source in the enclosure is studied with two analysis methods, i. e. CFD and artificial neural networks (ANN). The heat transfer in the enclosure is an unsteady process. During this process, the temperature fields in the enclosure are changing with time. The vertical temperature field of y = 0 at one moment is picked up for investigation. Firstly, FLUENT software which is a simulation program of CFD is adopted to simulate the temperature fields under different computation conditions. Then part of the simulation condition's temperature data is picked for training an ANN model and the rest of data is used for validating the ANN model. It has been found from the comparison between the CFD simulation and ANN prediction that the two results have a good agreement with each other. In the comparison, the max relative errors are around 12%, mean relative errors are around 0.3%, mean square errors are around 0.6%, values of absolute fraction of variance are all not less than 0.99. The results demonstrated that the ANN prediction have enough accuracy.

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Section: Mathematical Descriptionmentioning

confidence: 99%

Comparison study of CFD and artificial neural networks in predicting temperature fields induced by natural convention in a square enclosure

Zhou

Liu

et al. 2019

THERM SCI

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“…The Low Mach Number approximation (Ma( 1) suggested by Paolucci 24 was developed in our previous works for natural convection; natural convection coupled with surface radiation and combined natural convection-volumetric radiation. [25][26][27][28] This approach is used in this study to solve the momentum, heat, and solute equations, which lead to take into account fluid flows under large temperature/concentration gradients and variable transport coefficients.…”

Section: Introductionmentioning

confidence: 99%

Limit of the buoyancy ratio in Boussinesq approximation for double-diffusive convection in binary mixture

2021

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This paper deals with a mathematical and numerical investigation of double-diffusive natural convective heat and mass transfer in a cavity filled with Newtonian fluid with significant density and mass diffusivity changes. In such a situation, the assumption of the Boussinesq approximation is not justified, and an appropriate model based on a set of Low Mach Number equations is used. The active parts of two vertical walls of the cavity are maintained at fixed but different temperatures and concentrations, while the other two walls, as well as inactive areas of the sidewalls, are considered to be adiabatic and impermeable to mass transfer. The coupled momentum, energy, and solute transfer equations in binary mixtures of ideal gases are solved through a global iterative procedure based on the finite volume methods in the context of the low Mach number approximation. The study includes the effect of the buoyancy ratio N with the aim to find its application limit in the Boussinesq conditions. The results show that if we use the Boussinesq approximation to study double-diffusive convection, the value of parameter N must be between À6 and 27.M Ã þC10ð1ÀM Ã Þ kinematic viscosity, m 2 =s P ¼ðp À p þ q 0 gyÞ=q 0 ða 0 =HÞ 2 dimensionless dynamic pressure

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“…During the last few decades, the lid-driven cavity problem has been extensively studied both experimentally and computationally. The single-sided lid-driven cavity flow has been studied extensively by many researchers [9][10][11][12] using the conventional numerical methods such as finite element, finite difference, stream function vorticity approach for incompressible flows whereas the DSMC method, the Bhatnagar-Gross-Krook (BGK) method, the unified gas kinetic scheme and the Lattice-Boltzmann method for rarefied flows.…”

Section: Introductionmentioning

confidence: 99%

Simulation of flow in single and double-sided lid driven square cavities by direct simulation Monte Carlo method

Nabapure

Murthy

2020

THERM SCI

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The gaseous flow of monoatomic Argon in a double-sided lid-driven square cavity is investigated using the direct simulation Monte Carlo method for different degrees of rarefaction. The effect of the direction of wall motion and the magnitude of wall velocities on the flow physics are analyzed. Unlike the single-sided cavity flow, the double-sided cavity flow generates different vortex formations especially for the parallel wall motion of the wall. The problem, therefore, merits a thorough study, which is attempted in the present paper using the direct simulation Monte Carlo method. Certain complex flow phenomena which are not captured using the numerical methods for continuum flows are revealed by the current method employed in the study. Two counter-rotating vortices are observed for the parallel wall motion whereas only one primary vortex can be observed for the antiparallel case. The variation in the flow and thermal properties is found to be significant at the onset of the transition regime and much smaller in the free molecular regime.

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Numerical study of natural convection in a square cavity under non-boussinesq conditions

Cited by 13 publications

References 9 publications

Comparison study of CFD and artificial neural networks in predicting temperature fields induced by natural convention in a square enclosure

Comparison study of CFD and artificial neural networks in predicting temperature fields induced by natural convention in a square enclosure

Limit of the buoyancy ratio in Boussinesq approximation for double-diffusive convection in binary mixture

Simulation of flow in single and double-sided lid driven square cavities by direct simulation Monte Carlo method

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