Study of Thermal Characteristics Augmentation of the Aluminium Oxide Nano Fluid with Different Base Fluids

Nanofluids are binary mixtures of a base fluid with metallic particles (10 nm - 100 nm in size). The inclusion of nano-sized metal particles colloquially referred to as nanoparticles have been found to enhance the thermal of the fluid, thus increasing the heat transfer phenomena. However, the degree to which nanoparticles absorb heat may be dependent on their volume concentration. Nanoparticles may improve heat transmission up to a specific point in their volume concentration range and may reduce it beyond that point. This range of optimum nanoparticle volume concentration levels may also be dependent on the concentration of the base fluid and the source's temperature. In aggregate, it becomes a highly complicated issue, and more research is necessary to fully comprehend this phenomenon.

Several significant research has been conducted before to better understand the improvement of heat transfer through nanofluids [1, 2]. Kamyar et al. [3] used the lattice Boltzmann method to compare a numerical model to experimental data for a nanofluid system. They demonstrated that numerical methods were in close accord with experimental findings. They suggested that rather than modeling the nanofluid as either a single-phase system, a two-phase system is more appropriate. Additionally, they recommended that numerical modeling of nanofluids should include temperature-dependent thermophysical characteristics.

Li and Peterson [4] studied the buoyancy-based convection in an aluminium oxide nano fluid. Effect of nano-concentration was analysed for 0.5 to 6%. They inferred that with the advance in volume concentration, the heat transmission decreased. They ascribed this degradation to the nanofluid's increased viscosity and the occurrence of Brownian motion. They hypothesized that perhaps the thermophoresis impact delayed the start of natural convection. The findings of this study contradicted earlier findings.

Dagtekin and Oztop [5] investigated the impact of 2 different thermal partitions, their size, and placement inside an enclosure on natural circulation phenomena. Hwang et al. [6] examined a rectangular cavity and performed a buoyancy-driven heat transfer study of water-based (Al₂O₃) nanofluids. The ratio of the heat transfer coefficients of nanofluids to the base fluid falls as the size of the nanoparticles rises. Putra et al. [7] conducted heat transfer tests on a cylindrical device having a bottom and top thermal temperature and nanofluid. There was no indication of stratification of concentration layers. However, there was a reduction in spontaneous convective heat transmission. This decrease was attributable to the nanoparticles' concentration and the cylinder's aspect ratio. Goktepe et al. [8] compared single-phase and two-phase models for nanofluid convection at the entrance of an evenly heated tube. Numerous experts have done further study in nanofluids [9, 10]. Nguyen et al. [11] investigated the impact of nanoparticle size on a water aluminum oxide nanofluid. They tested the viscosity of two distinct particle sizes at various temperatures experimentally. Yazdi et al. [12] investigated the impact of Brownian motion upon this temperature increase of a nanofluid in a cavity. They examined Brownian motion's impact on a hollow loaded with water and Al₂O₃ nanoparticles. Buongiorno [13], Pak and Cho [14] investigated the impact of the nanofluid in a circular tube on oxide dual metallic nano atoms of alumina (Al₂O₃) & titanium oxide (TiO₂). They studied the heat transport behavior of a circular pipe and calculated the turbulent friction. Finally, Ahadi et al. [15] investigated the Soret effect's impact on the heat transmission of nanofluids.

In earlier research, the heat enhancement phenomena in nanofluids were analyzed using a comparison of pure water and pure Ethylene glycol as a primary fluid. Several pieces of research have also examined the heat enhancement capabilities of a combination of water and ethylene glycol in different quantities. However, no study discusses the variation in heat transfer behavior caused by the progressive transition from distilled water to a water-Ethylene glycol combination to a 100% Ethylene glycol mixture. The current article presents a numerical model like any 8 cm square enclosing loaded by Al₂O₃ nanofluid. The present study is unique in that it investigates and reports on the impact of progressive changes in the mixture of the different composite fluids.

The current study assumes that the flow is incompressible. Assuming that the nano-particles are readily humidified in the base fluid, the nanofluid is regarded as a single system. The primary objective of this study is to explore the temperature enhancement (or rate of heat transmission) and circulation behaviour of nano-fluids. Henceforth, any impact caused by an external force (for example, a magnetic field) is ignored. The model's boundary conditions are depicted in Figure 1 and are as follows:

$\begin{array}{ll}u=v=0, T=T_{h} & \text { at } x=0, \& \ 0 \leq y \leq 8 \\ u=v=0, T=T_{c} & \text { at } x=8, \& \  0 \leq y \leq 8 \\ u=v=0, \frac{\partial T}{\partial y}=0 & \text { at } y=0,8 \ \& \  0 \leq x \leq 8 \\ & \text { (All values in cm) }\end{array}$

(The origin is assumed to be at the cavity's south-west corner.)

Based on experimental observations, Khanafer et al. [16] have assessed and suggested the following values for the following characteristics of nanofluids: mass density ($\rho_{\text {nano fluid }}$), Absolute viscosity ( $\mu_{\text {nano fluid }}$), thermal conductivity ( $k_{\text {nano fluid }}$), thermal expansion coefficient ( $\beta_{\text {nano }} fluid)$, and specific heat capacity $\left(C_{p}\right.$ nano fluid $)$. The values for these properties are shown below:

Mass Density, $(\rho_{\text {nano fluid}})$:

$\rho_{\text {nano fluid }}=\varphi \rho_{n p}+(1-\varphi) \rho_{\text {base fluid }}$      (1)

Absolute Viscosity, $(\left.\mu_{\text {nano fluid}}\right)$:

$\mu_{\text {nano fluid }}=\frac{\mu_{\text {base fluid }}}{(1-\varphi)^{2.5}}$      (2)

Thermal conductivity, $(k_{\text {nano fluid}})$:

$\frac{k_{\text {nano fluid }}}{k_{\text {base fluid }}}=\frac{k_{n p}+2 k_{\text {base fluid }}\quad +\quad2\left(k_{n p}-k_{\text {base f;uid}} \quad \right)\quad\varphi}{k_{n p}+2 k_{\text {base fluid }}\quad-\quad 2\left(k_{n p}-k_{\text {base fluid}} \quad \right)\quad \varphi}$       (3)

Thermal volume expansion, $\left(\beta_{n f}\right)$:

$(\rho \beta)_{\text {nano }}$ fluid $=\varphi \rho_{n p} \beta_{n p}+(1-\varphi) \rho_{\text {base }}$ fluid $\beta_{\text {base }} fluid$     (4)

Specific heat capacity, $\left(C_{p_{\text {nano }} \text { fluid }}\right)$:

$\left(\rho c_{p}\right)_{n a n o f l u i d}=\varphi \rho_{n p} c_{p_{n p}}+(1-\varphi) \rho_{\text {base fluid }} c_{p_{\text {base }} \text { fluid }}$            (5)

Table 1. Properties of the base solution and Al₂O₃

Three different baseline liquids (Water, Ethylene glycol (EG), and Water-EG) are examined and compared in this study at varied Al₂O₃ nanoparticle concentrations (= 1%, 2%, and 3%). The water-EG combination is tested at with varying compositions: 0.2-0.8, 0.4-0.6, 0.6-0.4, and 0.8-0.2 concentrations. The thermal fluid characteristics of common basic fluids are shown in Table 1. The low temperature side is maintained at 300 K, while the temperature of the heated isothermal wall is studied at three different temperature levels are 306 K, 312 K, 318 K, & 324 K. As a result, three factors are examined (one at a time): (a) the percent volume concentration of Al₂O₃ nanoparticles; (b) the composition of the base fluid; and (c) the temperature. Table 1 shows the properties of the base solution and Al₂O₃ nanoparticles concerning each other.

The density value is estimated numerically using the Boussinesq approximation since its value varies proportionally with temperature in the momentum equation's buoyancy component. During the numerical simulation, the other characteristics are considered to stay constant. With the above in mind, the incompressible flow's dominant continuity, momentum, as well as energy equations are as follows:

Continuity Equation:

$\frac{\partial u}{\partial x}+\frac{\partial v}{\partial y}=0$      (6)

Momentum Equation:

$u \frac{\partial u}{\partial x}+v \frac{\partial u}{\partial y}=\frac{1}{\rho_{n f}}\left[-\frac{\partial P}{\partial x}+\mu_{n f}\left(\frac{\partial^{2} u}{\partial x^{2}}+\frac{\partial^{2} u}{\partial y^{2}}\right)\right]$      (7)

$\begin{aligned}

u \frac{\partial v}{\partial x}+v \frac{\partial v}{\partial y}=\frac{1}{\rho_{n f}} &\left[-\frac{\partial P}{\partial y}+\mu_{n f}\left(\frac{\partial^{2} v}{\partial x^{2}}+\frac{\partial^{2} v}{\partial y^{2}}\right)\right] \\

&+\left\{g(\rho \beta)_{n f}\left(T-T_{c}\right)\right\}

\end{aligned}$      (8)

Energy Equation:

$u \frac{\partial T}{\partial x}+v \frac{\partial T}{\partial y}=\alpha_{n f}\left(\frac{\partial^{2} T}{\partial x^{2}}+\frac{\partial^{2} T}{\partial y^{2}}\right)$      (9)

Figure 5 (a) and (b) represents the temperature contours of aluminium oxide based water and ethylene glycol nano fluid. The percent volume concentration of Al₂O₃ nanoparticles is adjusted to 3 percent in both square cavities, and the hot wall edge is maintained at 324 K. With regard to Al₂O₃-water nanofluid and also Al₂O₃-EG nanofluids enclosures, the respective RAYLEIGH values are 15.6 (107) and 4.38 (107) (for each). The greater the Rayleigh number, the stronger the flow, which intensifies natural convection. As a result, the isotherms demonstrate that the temperature gradient at the hot and cold walls is more severe in the context of Al₂O₃-water nanofluids.

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Figure 5. Comparison of temperature contour for 3% concentration

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Figure 6. Comparison of Nusselt number for different nanoparticle volume fractions with respect to fraction of water in water/EG solution

Plot of Nusselt number change with base fluid composition from clean EG to water-EG combination and back to pure water is shown in Figure 6. With the hot wall at 312 K and three different %vol nanoparticle concentrations, the analysis is completed. When shown in Figure 6, the Nusselt number rises as the baseline fluid composition shifts from EG to water, regardless of the percent vol concentration. Although the rise is almost linear, the figure flattens out when the composition becomes mostly water-based. For an 80/20 water-EG combination and a pure water base fluid, the Nusselt value is almost the same.

The velocity curves shown in Figure 7 are displayed to examine the impact of the hot heated wall on heat transfer rate. A rise in the Rayleigh number correlates with an increase in the flow strength due to the increased temperature of the wall. This increases the amplitude and activity of the velocity, as shown in Figure 7. The increase in Nusselt number driven by an increase in amplitude and activity of velocity is shown in Figure 8.

Figures 9 and 10 show the heat convection ratio of Al₂O₃-water nanoparticles and Al₂O₃-EG nanocomposites at different nanoparticles concentrations (hnfhbf/) to improve the understanding on the impact of nanoparticle volumetric fraction on heat augmentation. The maximum heat enhancement occurs at a value of=3% and increases to 4.5 percent.

7.png

Figure 7. Comparison of velocity contour for 0.3 volume fractioned Al₂O₃-EG nanofluid (at different wall temperatures)

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Figure 8. Comparison of Nusselt number vs wall temperature difference (for different nano particle volume fractions)

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Figure 9. Comparison of heat enhancement ratio of water nanofluid vs temperature difference for different nanoparticles concentration

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Figure 10. Comparison of heat enhancement ratio of ethylene glycol nanofluid vs temperature difference for different nanoparticles concentration