Investigation of Thermophysical Properties of Nanofluids and Effects of MHD

Heat transfer through a fluid; It is an important parameter in many engineering fields such as heat exchangers, solar collectors, refrigerators, automobiles, cooling of electronic devices, power plants. The increasing demand for energy has made it necessary to use energy more efficiently. For this purpose, it is necessary to design compact, low-cost systems with high thermal conductivity and high-performance heat transfer fluids. Researchers for the use of nanofluids as advanced heat transfer fluid compared to conventional fluids used in heat transfer applications have been aimed at improving the thermophysical properties of nanofluids on magneto fields. Therefore, many parameters such as the size, concentration, shape, base fluid, pH effect and operating temperature of the nano particles used were examined. In this study, information is given about the studies in the literature related to magneto hydrodynamic and the effects of thermophysical properties of the nanofluids on heat and flow characteristics are exemplified by a numerical study.


Parameters Effecting the Gains obtained From Nanofluids 3.1.1. Particle Volume Ratio
The effect of the experimental particle volume ratio of Al2O3-water nanofluid on the thermal conductivity coefficient is shown in Fig. 2.

. Particle Shape
In studies with nanofluids, two types of particle shape are generally studied. These; spherical and cylindrical particles. The particle shape effect of SiC-ethylene glycol and TiO2-water nanofluids is presented in Fig. 6. Figure 6. SiC-ethylene glycol (left), TiO2-water (right) particle shape effect 3.1.6. The Effect of Temperature In conventional suspensions of solid particles (sizes in millimeters or micrometers), while the thermal conductivity of the mixture depends on temperature, this temperature also depends on the temperature of the base fluid and the solid particles. This has a great effect on the thermal conductivity changes of temperature and nanofluids.

Thermophysical Properties of Nanofluids 4.1. Density
The density of nanofluids can be calculated by the Pak and Cho equation, which is derived from the physics principle. ϕ is volumetric ratios of solid particles, while the subindices nf, f and p represent nanofluids, base fluid and solid particles, respectively. Pak and Cho (1998) have demonstrated the accuracy of this equation experimentally. Xuan and Roetzel (2000) equations are used in the calculation of the specific heat of nanofluids

Viscosity
Viscosity of nanofluid is an important parameter in practical applications and directly affects the pressure drop in forced transport. In order to make the nanofluids usable in practical applications, the extent of viscosity increase of nanofluids compared to pure fluids should be well investigated. Studies on viscosity of nanofluids are limited in the literature.

Studies on Viscosity
The viscosity of nanofluids depends on many parameters: particle volume ratio, particle size, temperature. The viscosity increases as the particle volume ratio increases and this is demonstrated in many studies (

Thermal Conductivity
Many studies on thermal conductivity are available in the literature. Thermal conductivity indicates the heat conducting capacity of a substance and depends on many factors.

Studies on Thermal Conductivity
Numerous experimental equations have been developed to estimate the thermal conductivity of nanofluids (Maxwell, Hamilton, Mushed and Yu.).Some thermal conductivity correlations obtained as a result of the studies are presented in Tab. 4.

Coefficient of Thermal Expansion
The thermal expansion coefficient of nanofluids can be written in terms of the volume ratio of the nanoparticles. As a result of the studies, some correlations obtained at different temperature and volume concentration ranges and for different particles are presented in Tab. 5.

Numerical Study
A numerical study is presented in this section. Ogut and Dilki (2018) investigated numerically the fully developed turbulent flow and heat transfer behaviors of the water-based nanofluid in the corrugated trapezoidal plate heat exchanger .In the analysis, the effects of SiO2 nanoparticles with different volume fractions (ϕ = 0%-4%), different numbers of Re (6000-20000) and diameter d = 20nm were examined under constant heat flux (6kW / m 2 ). Viscosity was obtained by Corcione [3] and thermal conductivity was obtained by Koo and Kleinstreuer correlation [9]. Viscosity; Figure 8. Effect of base fluid water and SiO2-water nanofluid with different Reynolds numbers on the average Nusselt number (left) and the pressure drops (right) volume fraction ϕ = 0.04. Fig. 9 shows the different number of Re and nanofluid in different volume ratios on the left and the number of Nusselt changes in the right and pressure drop on the right. Accordingly, both the average Nusselt number and the pressure drop increase with increasing Reynolds number and solid volume ratio.

Conclusions
Although a generalization has not been made, the comments made on nanofluids so far can be summarized as follows: 1. The effective viscosity of nanofluids increases with increasing volume ratio and decreases with increasing temperature. 2. Effective thermal conductivity of nanofluids increases with increasing temperature and volume ratio and decreases with increasing particle diameter. 3. Classical models can be used to calculate the thermal conductivity and viscosity of nanofluids at room temperature, low volume ratios. However, at other temperatures, these models are not suitable for the calculation of thermal conductivity. 4. The viscosity of nanofluids plays a key role in determining the heat transfer characteristics. 5. Many researchers have developed their thermal conductivity modeling on the effects of Brownian motion of nanoparticles. The main argument here is associated with large collisions that occur between the particles during random movements. This enables heat transfer between the colliding particles. In the Brownian movement, it is also believed that the nano-sized fluid produces micro-transport. As the random movement with small-sized nanoparticles increases and the micro-convection effect will become dominant, thermal conductivity will increase. Brownian speed increases with increasing temperature and shrinking particle size. 6. As the thickness of the nano layer between the nanoparticles and the fluid increases, the thermal conductivity also increases. 7. While some clustering increases the thermal conductivity gain, excessive clustering has an adverse effect. Therefore, the optimum level of clustering should be determined for maximum thermal conductivity gain.