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Mathematical Problems in Engineering
Volume 2017, Article ID 5830279, 9 pages
https://doi.org/10.1155/2017/5830279
Research Article

CuO–Water Nanofluid Magnetohydrodynamic Natural Convection inside a Sinusoidal Annulus in Presence of Melting Heat Transfer

1Department of Mechanical Engineering, Babol Noshirvani University of Technology, Babol, Iran
2Department of Mathematics & Statistics, FBAS, IIUI, H-10 Sector, Islamabad, Pakistan
3Academy of Romanian Scientists, 050094 Bucharest, Romania

Correspondence should be addressed to R. Ellahi; moc.oohay@ihalletamhar

Received 23 April 2017; Accepted 3 July 2017; Published 31 July 2017

Academic Editor: Efstratios Tzirtzilakis

Copyright © 2017 M. Sheikholeslami et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Impact of nanofluid natural convection due to magnetic field in existence of melting heat transfer is simulated using CVFEM in this research. KKL model is taken into account to obtain properties of CuO–H2O nanofluid. Roles of melting parameter , CuO–H2O volume fraction , Hartmann number (Ha), and Rayleigh (Ra) number are depicted in outputs. Results depict that temperature gradient improves with rise of Rayleigh number and melting parameter. Nusselt number detracts with rise of Ha. At the end, a comparison as a limiting case of the considered problem with the existing studies is made and found in good agreement.

1. Introduction

Melting process has various uses such as application like in thermocouple, heat exchangers, and heat engines. Chamkha and Ismael [1] examined the Cu-H2O nanofluid mixed convection in an enclosure with lid wall. Also, Ellahi et al. [2] reported the similar study for nanofluid over permeable wedge in mixed convection. Harikrishnan et al. [3] investigated melting behavior of composite PCM for heating application. Nanofluid melting in a pipe with external fins has been studied by Mat et al. [4]. Manikandan and Rajan [5] utilized hybrid nanofluid for heat transfer augmentation. Koca et al. [6] utilized Ag-H2O nanofluid for natural circulation loops. Shyam and Tiwari [7] investigated the coiled heat exchanger by means of nanofluid. Das [8] reported the radiative flow in existence of melting heat.

Sheremet et al. [9] illustrated the free convective flow of ferrofluid in a rotating enclosure. Wavy duct in existence of Brownian forces has been examined by Shehzad et al. [10]. Sheikholeslami et al. [11] illustrated different uses of nanotechnology in their article paper. Abbas et al. [12] demonstrated the nanofluid flow through a horizontal Riga plate. Chamkha and Rashad [13] reported the nanoparticle migration on porous cone. Ellahi et al. [14] analyzed particle shape effects on Marangoni convection boundary layer flow of a nanofluid. They considered the Lorentz forces impact in governing equations. Malvandi et al. [15] reported nanofluid flow inside a channel in existence of Lorentz forces. Garoosi et al. [16] investigated performance of heat exchanger via nanofluid. They indicated that optimum volume fraction of nanoparticle exists to obtain maximum Nusselt number. Mesoscopic method has been utilized by Sheikholeslami and Ellahi [17] for a three-dimensional problem.

This research intends to present the impact of melting heat transfer on free convection of ferrofluid in the presence of Lorentz forces. CVFEM is selected to find the outputs. Roles of melting parameter, CuO–water volume fraction, and Hartmann and Rayleigh numbers are presented.

2. Problem Statement

Figure 1 depicts the geometry, boundary condition, and sample element. The inner wall is hot wall and the outer one is melting surface . Other walls are adiabatic. Horizontal magnetic field has been applied. The enclosure is field with nanofluid.

Figure 1: (a) Geometry; (b) sample element.

3. Governing Equation and Simulation

3.1. Governing Formulation

2D steady convective nanofluid flow is considered in existence of constant magnetic field. The fluid flow is laminar and incompressible. The flow is steady and Newtonian. The viscous dissipation is negligible in this study. The effects of Brownian force and thermophoretic force are not taken into condition. The flow also follows the Boussinesq assumption. The prevailing equations under these constraints can be written as [20],, , and are calculated as [17, 18], are calculated via KKL model [19]:Properties and needed parameters are provided in Tables 1 and 2 [19].

Table 1: Coefficient values of CuO–H2O [19].
Table 2: Properties of H2O and CuO [19].

Vorticity and stream function should be used to eliminate pressure source terms:Dimensionless quantities are introduced as follows:The final formulae areBoundary conditions areand in melting surface, we havewhere dimensionless and constants parameters are illustrated asIt should be mentioned thatis related to Stefan numbers.

Local and average Nusselt over the cold wall can be calculated as follows:

3.2. Numerical Procedure

CVFEM uses both benefits of two common CFD methods. This method uses triangular element (see Figure 1(b)). Upwind approach is utilized for advection term. Gauss-Seidel approach is applied to solve the algebraic equations. Further notes can be found in [21].

4. Grid Independency and Validation

Outputs should not rely on mesh size. Therefore, several grids should be tested. For example, as shown in Table 3, a grid size of can be selected. The correctness of CVFEM code for nanofluid natural convective heat transfer is demonstrated in Figure 2 ([18]). This CVFEM code has good accuracy for magnetohydrodynamic flow as depicted in Table 4 [20].

Table 3: Mesh independency analysis when , , , and .
Table 4: for various Gr and Ha at Pr = 0.733.
Figure 2: Validation of present code (Khanafer et al. [18]) when , , and (Cu–water).

5. Results and Discussion

Nanofluid flow in a half sinusoidal annulus due to magnetic field in presence of melting surface is examined. , of CuO–water nanofluid are estimated by means of KKL model. Graphs and tables are depicted for different amounts of CuO–H2O volume fraction ( to ), melting parameter ( to ), Rayleigh number ( to ), and Hartmann number ( to ).

Impact of adding CuO nanoparticles in water on velocity and temperature contours is depicted in Figure 3. Temperature gradient decreases with augment of . augments with adding nanoparticles because of increment in the solid movements. In presence of melting heat transfer and magnetic field, effect of adding nanoparticles on isotherms becomes negligible.

Figure 3: Impact of adding CuO in water on streamlines and isotherms (nanofluid () (—) and pure fluid () (- - -)) when and .

Figures 4 and 5 depict the impact of Rayleigh and Hartmann numbers in absence of melting heat transfer. There is only one eddy in streamline. In low Rayleigh number, conduction mechanism is dominant. As increases, the distortion of isotherms is enhanced close to the hot wall. Adding magnetic field makes isotherms become parallel. In presence of melting heat transfer the primary eddy diminishes and increasing Lorentz forces generates three layers for streamline. Increasing melting parameter augments the bottom eddy.

Figure 4: Isotherms and streamlines for various Ha, Ra when and .
Figure 5: Isotherms and streamlines for various Ha, Ra when and .

Figure 6 illustrates the impact of , , and on . The formula for corresponding to active parameters iswhere and . As melting parameter augments, temperature gradient is enhanced and in turn Nusselt number is enhanced. Increasing buoyancy forces leads the thermal boundary layer thickness to reduce. So Nusselt number increases with enhancement of. As Hartmann number augments, isotherms become parallel. Therefore Nusselt number has opposite relationship with Ha.

Figure 6: Impacts of , Ha, and Ra on .

6. Conclusions

Nanofluid free convection due to Lorentz force in existence of melting surface is reported. Combination of FEM and FVM is utilized to solve the PDEs. KKL model is considered for nanofluid. Roles of Hartmann number, CuO–water volume fraction, Rayleigh number, and melting parameter are presented. Outputs depict that temperature gradient improves with augment of melting parameter and Rayleigh number. Adding magnetic field makes the temperature gradient reduce due to domination of conduction mechanism in high Hartmann number.

Nomenclature

Magnetic field
Fluid temperature
Nusselt number
Ra:Rayleigh number
:Gravitational acceleration vector
Ha:Hartmann number.
Greek Symbols
Dimensionless temperature
Thermal diffusivity
and :Dimensionless vorticity and stream function
Melting parameter
Thermal expansion coefficient
Electrical conductivity
Dynamic viscosity.
Subscripts
Base fluid
Local
Nanofluid.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

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