Numerical study of mixed convection and entropy generation of Water-Ag nanofluid filled semi-elliptic lid-driven cavity

Zhang, Haiying; Nie, Xiujun; Bokov, Dmitry Olegovich; Toghraie, Davood; Akbari, Omid Ali; Montazerifar, Farnaz; Pourfattah, Farzad; Esmaeili, Yousof; Khodaparast, Roohollah

doi:10.1016/j.aej.2022.02.028

Cited by 20 publications

(3 citation statements)

References 52 publications

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“…It has become trendy due to its high thermal conductivity and energy efficiency. Zang et al [ 7 ] did a study on the mixed convection in a semi-elliptic cavity flow under mixed convection using water-silver nanofluid varying the nanofluid concentrations and Grashoff number. They concluded that with the rise of nanofluid concentrations, the heat transfer rate shoots up significantly.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural network (ANN) analysis on thermophysical properties of magnetohydrodynamics flow with radiation in an arc-shaped enclosure with a rotating cylinder

Bairagi,

Jahid Hasan,

Hudha

et al. 2024

Heliyon

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Section: Introductionmentioning

confidence: 99%

Artificial neural network (ANN) analysis on thermophysical properties of magnetohydrodynamics flow with radiation in an arc-shaped enclosure with a rotating cylinder

Bairagi,

Jahid Hasan,

Hudha

et al. 2024

Heliyon

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“…A hybrid nanofluid (HBNF) comprising of Al2O3-Cu and water is poured into the cavity. The primary objective of Zhang et al [8] research was to numerically simulate heat transfer and laminar and mixed flow inside a closed, semi-elliptic lid-driven cavity. Within a two-dimensional viscoplastic fluid-filled lid-driven cavity, the study of Ferrari et al [9] examines the flow properties.…”

Section: Introductionmentioning

confidence: 99%

Heat Transfer Neural Analysis of Bingham-Papanastasiou Fluid in Lid-driven Rectangular Cavity with viscous dissipation

Tanveer,

Ul-Haq,

Ashraf

2024

Preprint

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The study of Bingham-Papanastasiou fluids is conducted in lid-driven cavity with consideration of viscous dissipation. The left wall of the cavity is adiabatic while other walls are insulated. Numerical simulations are conducted to study the isotherms, temperature profile and Nusselt number. An inventive artificial neural network (ANN) model for precise predictions is made using the simulation data. Both COMSOL and ANN are used to find the best values for each input parameter to maximize the output parameters. The effectiveness of these two approaches in obtaining the best results is then evaluated through a comparison study. Plotting isotherms for larger Bingham numbers shows that the temperature distribution toward the left wall is behaving more and more rapidly. The rate of heat transfer rises with increasing Re values, but it exhibits the opposite behavior when Bn values are high close to the left adiabatic wall. After 406 epochs, the training state plot demonstrated convergence and optimization progress with gradient = 0.018363 and Mu = 0.0001. The novelty of this work is that the integrated approach involving Artificial Neural Networks (ANN) described in this study allows the prediction of flow behaviors for various cases without additional real-time CFD simulations once sufficient information is gathered through Computational Fluid Dynamics (CFD) simulations for a few flow cases. In real-world flow control applications where real-time CFD simulations might not be possible, this method seems to be beneficial.

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“…Furthermore, the overall irreversibility and heat transfer diminish with rising Ha and declining Ri. Haiying et al [ 6 ] modeled the laminar regime’s mixed flow and nanofluid’s heat transfer within an enclosed semi-elliptic lid-driven chamber. The collected findings suggest that introducing a greater volume percentage of nanoparticles at small values of Richardson numbers contributes to the augmentation of heat transfer and the mean Nusselt number.…”

Section: Introductionmentioning

confidence: 99%

Irreversibility Interpretation and MHD Mixed Convection of Hybrid Nanofluids in a 3D Heated Lid-Driven Chamber

et al. 2022

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This paper presents a numerical simulation of a magneto-convection flow in a 3D chamber. The room has a very specific permeability and a zigzag bottom wall. The fluid used in this study is Al2O3-Cu/water with 4% nanoparticles. The Galerkin finite element technique (GFEM) was developed to solve the main partial equations. The hybrid nanofluid inside the container is subjected to the horizontal motion of the upper wall, an external magnetic field, and a thermal buoyancy force. The present numerical methodology is validated by previous data. The goal of this investigation was to understand and determine the percentage of heat energy transferred between the nanofluid and the bottom wall of the container under the influence of a set of criteria, namely: the movement speed of the upper wall of the cavity (Re = 1 to 500), the amount of permeability (Da = 10−5 to 10−2), the intensity of the external magnetic field (Ha = 0 to 100), the number of zigzags of the lower wall (N = 1 to 4), and the value of thermal buoyancy when the force is constant (Gr = 1000). The contours of the total entropy generation, isotherm, and streamline are represented in order to explain the fluid motion and thermal pattern. It was found that the heat transfer is significant when (N = 4), where the natural convection is dominant and (N = 2), and the forced convection is predominant.

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Numerical study of mixed convection and entropy generation of Water-Ag nanofluid filled semi-elliptic lid-driven cavity

Cited by 20 publications

References 52 publications

Artificial neural network (ANN) analysis on thermophysical properties of magnetohydrodynamics flow with radiation in an arc-shaped enclosure with a rotating cylinder

Artificial neural network (ANN) analysis on thermophysical properties of magnetohydrodynamics flow with radiation in an arc-shaped enclosure with a rotating cylinder

Heat Transfer Neural Analysis of Bingham-Papanastasiou Fluid in Lid-driven Rectangular Cavity with viscous dissipation

Irreversibility Interpretation and MHD Mixed Convection of Hybrid Nanofluids in a 3D Heated Lid-Driven Chamber

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