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# Nano Fluid

## Influence of Nano Fluid on Heat Exchanger Efficiency

There are many ways to improve the thermal properties of a heat exchanger. These include creating plates to increase heat transfer surface, vibration, and the use of microchannel. Thermal efficiency can also be increased by increasing the thermal conductivity of the working fluids. Fluids commonly used in industry, such as water, ethylene glycol, motor oil, etc., often have lower conductivity than solids, which is why the solids can be used to improve performance in the form of solid particles (nanoparticles) added into the fluid. On the other hand, these particles can also cause scavenging or blockage of the channels or their corrosion, which itself has some disadvantages and the potential to increase the conductivity coefficient in order to increase efficiency.

Many materials can be used as nanoparticles. Since the thermal conductivity of materials, whether in the metal or non-metallic state as Al2O3, CuO, TiO2, SiC, TiC, Ag, Au, Cu, and Fe are generally several times higher, even at low concentration, they have an effective influence on the thermal transfer coefficient.

Nano-scale solid particles with dimensional scales in the range of 1–100 nm have been observed with high thermal conductivity which can significantly increase the effective conductivity of the main fluid as well as its heat transfer coefficient. Most of these particles are spherical. However, other forms, such as tubular, elongated, disc-shaped, are also considered.

## Nano Fluid Thermal Conductivity

Numerous methods have been proposed to calculate and quantify the enhancement and improvement of the thermal properties of Nano fluids, which range from experimental to analytical methods.

### 1. Classic models:

In 1837, Maxwell proposed a relation for calculating the effective conductivity of Nano fluids with spherical particles as follows:

In this equation, the p, f, and nf subgroups represent the particle, fluid, and Nano fluid respectively in the state of the spherical particles. As is evident in this equation, no effect of other particle shapes has been applied. The following equation was proposed by Hamilton and Crosser to improve this model.

In this equation, n is the form factor. PSI is also the degree of spherically of a particle, which represents the ratio of the surface area of a sphere to the spherical particle with equal volume.

### 2. Brownian Motion of Nanoparticles:

The Brownian motions is derived from the random motion of the particles in the fluid, which transfers the energy into the fluid. In order to calculate this type of property that affects the Nano fluid conductivity, the conduction coefficient is divided into two static and Brownian parts, the static part of which is stated in the preceding section and the Brownian part is as follows:

According to the experimental equation of Dos et al the value of “f” for CuO is as follows (for other particles 1 can be taken into account due to lack of experiments):

And the following equation is used to calculate the corresponding values of BETA_beta:

### 3. Clustering of nanoparticles:

Clustering can have the rapid effect of heat transfer over relatively long distances due to the stronger thermal properties of the solid rather than fluid in the following equation:

### 4- The fluid layer around the nanoparticles:

Fluid form a layered structure around the particle, in which case the properties of these parts of the fluid become closer to the solid. In this case, the thermal conductivity of this section becomes a relative increase, as shown by the experiments of Yu and Choi.

where

In this equation, kl is the thermal conductivity of the nanoparticles. Beta_L is also defined as follows:

In this equation, “t” is the thickness of the mentioned layer and NA is also the Avogadro constant. As is well known, a relatively large calculation is needed to obtain Kl, which can be assumed k_l=k_p in the maximum case.

## Nano Fluid & Convection Heat Transfer

In the convection heat transfer analysis of Nano fluid, accurate estimation of properties is of particular importance. The following table estimates the Nano fluid parameters:

Finally, the relationships shown in the following table for specific particle fluids in specific experiments are experimentally expressed as those previously mentioned for viscosity.

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