Numerical Investigation of the Use of Boron Nitride/Water and Conventional Nanofluids in a Microchannel Heat Sink

Abstract

The purpose of this paper is to study the effects of the use of boron nitride (BN) and other conventional nanoparticles (Al₂O₃, CuO and TiO₂) on pressure drop and heat transfer in a microchannel. The governing equations for forced fluid flow and heat transfer were worked out by using fluent computational fluid dynamics (CFD) code. Computational results collected from fluent CFD code for Al₂O₃ as the nano-particle were compared with numerical values used in the literature for validation. The basis of a water-cooled (pure water, Al₂O₃/Water, CuO/Water, TiO₂/Water and BN/Water) smooth microchannel was outlined, and then the corresponding laminar flow and heat transfer were evaluated numerically. The results from the numerical tests (NT) express good agreement with the values found in the literature. These results also indicate, through the comparison which was performed by taking the heat transfer and pressure loss parameters between BN and other widely used conventional nanoparticles (Al₂O₃, CuO and TiO₂) into consideration, that BN is the more favorable nanoparticle. In comparison to other common nanoparticles (Al₂O₃, CuO and TiO₂), BN enhances heat transfer and slightly raised pressure losses owing to its high thermal conductivity and high velocity profile because of low density. It is also chemically stable at the highest temperature relative to most solid materials. Thus, it has a structure that can be used in cooling systems for a long time without causing a problem of agglomeration.

1. Introduction

The high-power density and compactness characteristic of modern electronic devices require the use of efficient and compact cooling components for these devices. The primary task of these components is to maintain this high power and therefore heat generating electronics packages within their designed operating temperature range [1,2]. To ensure the reliability of electronics, many heat dissipation methods have been suggested, which include microchannel heat sink, jet impingement, heat pipe, and thin film boiling, etc. In contrast to conventional heat sinks, which require a large surface area to increase heat dissipation rates, microchannel heat sinks seem applicable for this purpose since they are small and effective.

A microchannel heat sink comprises small diameter passages for a liquid coolant. Creating a large area for the heat transfer between the cooler and the device to be cooled is achieved using these small diameter passages.

Microchannels are fluid flow channels with small hydraulic diameters. Following the classification by Kandlikar and Grande [3], channels with a minimum cross-sectional dimension between 200 µm and 3 mm are classified as minichannels and those between 1 µm and 200 µm are classified as microchannels. The flow in microchannels has been the subject of increased research interest over the past few years. It can be seen in many important applications, such as miniature heat exchangers, microscale process units, nuclear reactors, material processing and thin film deposition technology, and biotechnology system, as well as potentially in space applications [4]. A great deal of research has been carried out to improve the thermal performance of micro systems, according to the literature [5,6,7,8,9].

Zunaid et al. [10] studied the heat transfer and pressure drop characteristics of a straight, rectangular and semi-cylindrical projection microchannel heat sink. They stated that heat transfer increases with the use of semi-cylindrical projection microchannel heat sink.

It is difficult to cool a heated system with traditional liquids, owing to the high-power and high-integration demand, so researchers have concentrated on nanofluids.

A nanofluid is a fluid containing nanometer-sized particles [11]. These particles are metals or metal-oxides [12]. Water is used as the main fluid in nanofluids due to its thermal performance properties.

Abdolahi et al. [13] investigated the fluid flow and heat transfer characteristics of laminar nanofluid flow in microchannel heat sink (MCHS) with V-Type inlet/outlet arrangement, and showed that nanofluid can improve the performance of MCHS with V-shaped inlet/outlet arrangement.

Coskun and Cetkin [14] showed that overall thermal conductance in a rectangular microchannel heat sink can be maximized with the combination of nanofluids and micro pin fins. They showed the effect of micro pin fins and nanofluids both separately and simultaneously, in order to show their effect on the thermal conductance (i.e., thermal resistance). Both nanofluids and micro pin fins decrease the overall thermal resistance due to the increase in the average thermal conductivity of the flow system.

Sabaghan et al. [15] researched a comprehensive numerical procedure which is based on the two-phase approach to simulate a rectangular microchannel consisting of six longitudinal vortex generators (LVGs), and stated that using the mixture of EG:W (60:40 ethylene glycol and water) instead of pure water as a base-fluid leads to the increase of heat transfer in the microchannel. Finally, the maximum normalized efficiency of the LVG-enhanced microchannel, compared to the plain channel, is around 14%. Furthermore, using nanofluid can improve the normalized efficiency by 27%.

Belhadj et al. [16] used a numerical study to show that laminar forced the convective flow of nanofluid-based water/Al₂O₃ in a two-dimensional horizontal microchannel heat sink. They stated that their study contributes to improving cooling systems by integrating the nanofluids in the next generation of microchannel heat sinks.

Shi et al. [17] created a new simulation method, which is described in their paper, to consider whether the thermophysical properties of nanofluids are non-uniform and dynamic in the channels. It was validated by the classical experimental data. The effects of the concentration of nanoparticles, the Reynolds number and the axial thermal conduction effect on the flow and heat transfer characteristics of nanofluids in microchannels are analyzed. They concluded that the proposed numerical simulation method can simulate the forced flow and heat transfer of nanofluids in the microchannel more accurately than the traditional single-phase model.

A numerical study was performed by Kahani [18] to investigate the heat performance of Al₂O₃/water as a nanofluid in a microchannel. He used a modified dispersion model to take the effect of the nanoparticle into account, and recommended this model to predict the thermal performance effects well. Moreover, he stated that the best thermal performance is obtained at a 0.526 aspect ratio of the microchannel.

Gonçalves et al. [19] studied forced convective heat transfer by using different geometrical parameters of a microchannel in a single-phase flow of the fluid. They stated that the higher heat performance of the microchannel comprised a rectangular collector with eight microchannels and vertical placement of the inlet and outlet.

Zainon et al. [20] studied the thermo-physical properties of TiO₂-SiO₂ hybrid nanofluids at volume concentrations between 0.5 and 1.5%. They stated that the thermophysical properties of TiO₂-SiO₂ hybrid nanofluids are temperature-dependent. Both thermal conductivity and specific heat are seen to increase with temperature. In contrast, the viscosity and density decreased when the temperature increase. Based on these findings, the TiO₂-SiO₂ hybrid nanofluids at the recommended volume concentration of 1.5% can be used to replace conventional heat transfer fluids.

Researchers have made great efforts to improve thermal performance in cooling systems by developing or using different nanofluids in different methods.

Saba et al. [21] investigated the three-dimensional compression flow of the hybrid nanofluid (CNT-SiO₂/H₂O). They used an improved Hamilton-Crosser model (RHCM) to explain the effective thermal conductivity of nanofluid based on CNTs. Expressions for the local Nusselt number and skin friction coefficient were also obtained, and their effective behavior was briefly discussed.

Researchers are daily proposing new nanofluids as an alternative to traditional nanofluids.

Rashid et al. [22] investigated the shape effects of graphene-water nanofluid flow on the Marangoni boundary layer and heat transfer over a porous medium under the effects of the suction parameter. They compared the thermal performance by suspending nanoparticles in various shapes.

Studies on the effects of boron minerals as nanofluids are very limited in quantity in the literature, in spite of the fact that these minerals are significant for cooling systems. Furthermore, the presence of new nanofluids helps considerably in solving the problems of cooling systems.

Han et al. [23] created boron nitride nanospheres without requiring modification or the addition of surfactants. Thus, they expressed that BN nanospheres have great potential for improving the thermal conductivity of water-based fluids.

Hou et al. [24] showed a new nanofluid called boron nitride nanosheets with regard to its thermal performance.

Velmurugan et al. [25] studied the effect of boron nitride as nanoparticle. They recommended it as a nanoparticle in nanofluid systems because, due to its high thermal conductivity, appropriate thermal expansion coefficient, high electrical insulation and high mechanical strength, it is a promising addition to traditional heat exchange fluids.

Boron nitride is a ceramic material that has been studied as a nanoparticle due to its high thermal performance properties. In addition, it is also chemically stable with respect to most solid materials, even at most high temperatures. Recently, these particles have become the focus of attention of researchers and industry due to their superior properties.

Kumar and Tiwari [26] evaluated the thermal performance of a U-tube evacuated tube solar collector using water-based and different concentrations of boron nitride. They analyzed the thermal performance of the collector at different mass flow rates and obtained approximately maximum energy efficiency (72.14% at 1.5% volume and 0.051 kg/s). This corresponds to 84% higher efficiency than pure water fluid under the same flow conditions.

Zu et al. [27] studied the application of TiN-modified h-BN nanolayers in solar collectors. They stated that their work is important for new strategies to use the full spectrum of solar energy and to control the photothermal properties of nanofluids.

Mat et al. [28] reported the results of a numerical simulation by CFD on the liquid flow of Triton TX-100 surfactant containing boron nitride nanotubes (BNN) in distilled water (base liquid) at 30 and 50 °C.

Due to the rapid advances in cooling systems and the high thermal performance requirement in these systems, intensive studies are carried out on nanofluids. These studies are about obtaining new and high-performance nanofluids as an alternative to existing nanofluids. In this context, nano-sized solid particles used in nanofluid content should have superior properties in terms of heat transfer and pressure drop. Recently, studies on obtaining nanofluids using BN nanoparticles and using them in cooling systems have increased due to their high thermal capacity, stability at high temperatures and low-density properties.

For this reason, in this study, to acquire the effect of the use of boron nitride (BN) and other conventional nanoparticles (Al₂O₃, CuO and TiO₂) in a microchannel on pressure drop and heat transfer, the 3-D numerical simulations by using the fluent CFD code were evaluated. The geometrical dimensions studied in this paper are demonstrated in Shi et al. [17]. Boron nitride (BN) and other conventional nanoparticles (Al₂O₃, CuO and TiO₂) are used with water as a base fluid by changing the inlet Reynolds number and the volume fraction ratio. It was calculated which of these four nanoparticles have better properties in terms of pressure drop and heat transfer characteristics.

2. Materials and Methods

2.1. Governing and Additional Equations

Governing equations for incompressible, steady state, laminar flow and heat transfer in a microchannel were calculated numerically using fluent CFD code.

The steady-state conservation of mass, momentum and energy equations can be shown in the following compact form:

$$\nabla ·(\rho \overrightarrow{U)}=0$$

(1)

$$\nabla (\rho \overrightarrow{U}\overrightarrow{U})=-\nabla P+\nabla ·(\mu \nabla \overrightarrow{U})+S_m$$

(2)

$$\nabla (\rho \overrightarrow{U}{c}_{p}T)=-\nabla ·(k\nabla T)+S_e$$

(3)

where S_m and S_e are the source terms and represent the momentum and energy transfer between the continuous phase and the discrete phase, respectively [17].

$$S_m={\displaystyle \sum n_p\frac{m_p}{\delta U}\frac{d{U}_p}{dt}}$$

(4)

$$S_e={\displaystyle \sum n_p\frac{m_p}{\delta U}{C}_p\frac{d{T}_p}{dt}}$$

(5)

n_p is the number of nanoparticles in a computational cell.

$$\frac{d{U}_p}{d{t}_p^{}}=\frac{18{\mu }_c}{{\rho }_p{d}_p^2}\frac{C_D{\mathrm{Re}}_p}{24}\left(U_c-U_p\right)+\frac{g\left({\rho }_p-{\rho }_c\right)}{{\rho }_c}+F_{other}$$

(6)

where C_D is the drag coefficient.

$$C_D=\frac{24}{{\mathrm{Re}}_p}$$

(7)

The relative Reynolds number of nanoparticles Re_p is

$${\mathrm{Re}}_p=\frac{\rho d_p\left|u-u_p\right|}{\mu }$$

(8)

Moving nanoparticles from the high temperature region to the low temperature region:

$$F_{tp}=-3\pi {\mu }^2{d}_p{K}_{tp}\frac{\nabla T}{{\rho }_{f}T}$$

(9)

where K_tp is a function of the thermal conductivities of both the fluid and the solid particle [29].

The force resulting from the collisions between the particles and randomly moving molecules of the base fluid leads to the Brownian motion of the nanoparticles.

$$F_{Br}=\frac{m_p}{\pi }\overrightarrow{R}\sqrt{\frac{2k_{B}T}{3\pi \mu d_p{\left(\mathrm{\Delta }t\right)}^3}}$$

(10)

where R is a random vector and Δt is the integration time [29].

Heat transfer coefficient h is calculated using the Ranz and Marshall correction [30].

$$Nu=\frac{h·d_p}{k_{}}=2+0.6·{\mathrm{Re}}_p^{1/2}·{\mathrm{Pr}}^{1/3}$$

(11)

where Pr is the Prandtl number.

For the simulations, a uniform heat flux of 200,000 W/cm² was applied on the bottom surface of the substrate. The top wall surface of the channels and the outer surfaces of the microchannel were assumed to be insulated. For the flow field, the velocity applied at the inlet was assumed to be uniform and a pressure condition was applied at the outlet. Thermal radiation and natural convection heat transfer between the outer wall surface and the environment were ignored.

2.2. Numerical Procedure

The microchannel used in the numerical tests had an overall length of 44.8 mm and the hydraulic diameter of 341 μm, as can be seen in Figure 1.

The numerical computation was carried out with a numerical grid, as shown in Figure 2, where the white color shows the regions of very dense mesh.

Different grades of grid refinement were tested. The grid refinement research demonstrated that a total number of about 3,399,973 elements was sufficient to acquire a grid-independent solution.

The single-phase model and Lagrangian approach were simulated using the control volume method (FVM).

In numerical tests, the forces such as drag, thermophoretic, and Brownian etc., which arose as a result of the interaction between the base fluid and the nanoparticles, were taken into account under the Lagrangian solution approach. These forces were included in the source term in the momentum equation.

The SIMPLE algorithm was employed for pressure–velocity coupling. The second order upwind discretization method was adopted to test the stability of solution convergence. The DPM as the two-way coupling method was used to track nanoparticle trajectories. In this study, the convergence criteria for continuity, momentum and energy equations were set to 10⁻⁶, 10⁻⁶ and 10⁻⁹, respectively.

2.3. Nanofluid Properties

Some properties of BN, Al₂O₃, TiO₂, CuO and pure water, such as density, specific heat and thermal conductivity at 303.15 K, are given in

Table 1. Thermophysical properties of Nanoparticles and Pure Water at 303.15 K.

Property	Water	Al2O3	TiO2	CuO	BN
Density (kg/m3)	998.2	3970	4050	6500	2300
Specific heat (J/kg.K)	4182	765	697	536	1150
Thermal conductivity (W/m.K)	−0.93314 + 0.00853 · T −0.000011259 · T2 [17]	25	11.8	20	52
Viscosity (kg/m.s)	0.01723−9.25951e−5·T+ 1.2681e−7·T2 [17]	-	-	-	-

.

Some properties of nanofluids such as thermal conductivity (k), dynamic viscosity (µ), specific heat (c) and density (ρ) can be shown with the following equations [31]:

$$k_{nf}=\left[\frac{k_p+(n-1)k_{bf}-(n-1)\varphi (k_{bf}-k_p)}{k_p+(n-1)k_{bf}+\varphi (k_{bf}-k_p)}\right]k_{bf}$$

(12)

$$\frac{{\mu }_{nf}}{{\mu }_{bf}}=1+2.5\varphi$$

(13)

$$c_{nf}=(1-\varphi )c_{bf}+\varphi c_p$$

(14)

$${\rho }_{nf}=(1-\varphi ){\rho }_{bf}+\varphi {\rho }_p$$

(15)

where nf, bf and p are the properties of the nanofluid, pure water and solid particle, ϕ is the volume fraction rate, and n is the shape factor of the solid particle.

Figure 3 shows specific heat, thermal conductivity, viscosity and density for coolants of Al₂O₃/Water, TiO₂/Water, CuO/Water and BN/water at volume fraction ratio of 3% and of pure water. 3% volume fraction was chosen in the figure because the thermal conductivity, viscosity, density increase as the particle concentration increase, but the specific heat decreased with the increase of particle concentrations.

As can be seen from this figure, the properties of the coolant change in different mixtures. In the transition from base fluid water to nanofluid, thermal conductivity, viscosity and density values increase while specific heat decreases.

3. Results and Discussion

In this paper, to obtain the effect of the use of boron nitride (BN) and other conventional nanoparticles (Al₂O₃, CuO and TiO₂) in a microchannel on pressure drop and heat transfer, the 3-D numerical simulations using fluent CFD code were assessed, as well as the microchannels for different volume fraction of nanofluids. Boron nitride and other conventional nanoparticles (Al₂O₃, CuO and TiO₂) were used with water as a base fluid by changing the inlet Reynolds numbers. An evaluation was carried out to establish which of these four nanoparticles were considered to have superior properties in terms of pressure drop and heat transfer characteristics.

3.1. Numerical Validation

Firstly, the numerical technique was verified with the results given in Shi et al. [17]. The inlet temperature of fluid had a constant value of 303.15 K for different Reynolds numbers. A uniform heat flux, q = 200,000 W/cm², was applied to the bottom surface of the microchannel.

Figure 4 shows the comparison of the pressure drop values for different Reynolds numbers with water and water/Al₂O₃ fluids obtained using the numerical tests with the results given in Shi et al. [17].

As can be seen from Figure 4, the pressure drop increases with the increasing Reynolds numbers, so it can be seen clearly that the consumption of pumping power directly increases. Moreover, the pressure drop also increases owing to the increase of the mixture density and viscosity with the addition of 1% and 3% Al₂O₃ as nano-particles. Results obtained from the numerical tests show good agreement with results given in Shi et al. [17].

Figure 5 gives the comparison of the heat transfer coefficients values for different Reynolds numbers with water and water/Al₂O₃ fluids obtained using the numerical tests with the results given in Shi et al. [17].

As can be seen from Figure 5, the heat transfer coefficient increases with the increasing Reynolds number, so it is clear that the thermal performance directly increases. Moreover, the thermal performance also increases due to the improvement of the thermal properties such as the thermal conductivity coefficient with the addition of 1% and 3% Al₂O₃ as nanoparticles. Results obtained using the numerical tests demonstrate good agreement with results given in Shi et al. [17].

After the numerical technique was verified, the maximum temperature differences obtained for different Re and pure water in the microchannel and their contours were obtained in Figure 6 and Figure 7. It can be seen that the maximum temperature decreases with the increasing Reynolds numbers since the thermal resistance decreases as the Reynolds numbers increases. This nonlinear trend is in agreement with already published papers [32]. Figure 8 gives the results of the friction factor values obtained using numerical tests for different Reynolds numbers and pure water.

The friction coefficient decreased with the increasing Reynolds numbers, and it was almost constant with high Reynolds numbers (Figure 8). The reason is that at low Reynolds numbers, viscous effects and friction coefficient of the fluid flow are high. Viscous effects decrease with the increasing Reynolds numbers, therefore decreasing the effects of surface friction. The friction coefficient then finally becomes almost constant.

3.2. Analysis of Performance Characteristics of Nanofluids

The effect of the use of boron nitride and other conventional nanoparticles (Al₂O₃, CuO and TiO₂) in a microchannel on pressure drop and heat transfer were studied in detail.

As can be seen from the above validation results, the heat transfer coefficient and pressure drop increased by adding nanoparticles to pure water. At the same time, when the volume fraction ratio was increased from 1% to 3%, the heat transfer coefficient increased due to the thermal conductivity of the nanofluid increases.

A comparison of the longitudinal development of heat transfer coefficient values along the microchannel for Al₂O₃/Water, TiO₂/Water, CuO/Water and BN/water at a volume fraction of 3%, obtained using numerical tests, is given in Figure 9.

As can be seen from Figure 9, the heat transfer coefficient of BN is some higher compared with other conventional nanoparticles (Al₂O₃, CuO and TiO₂) for the same Reynolds numbers, because it is clear that BN, when compared with Al₂O₃, CuO and TiO₂ nanoparticles, has high thermal properties.

A comparison of the longitudinal development of pressure drop values along the microchannel for Al₂O₃/Water, TiO₂/Water, CuO/Water and BN/water at the volume fraction = 3%, obtained using numerical tests, is given in Figure 10.

As can be seen from Figure 10, the pressure drop values of BN is slightly higher compared with other nanoparticles for the same Reynolds numbers, as it is clear that BN has the high velocity profiles due to its low density.

In cooling systems, it is desirable for the heat transfer properties to be high, but for the pressure losses to be minimal. The changing of geometric parameters to increase the heat transfer properties and reduce the pressure loss yields no results because the configurations which are made to improve heat transfer lead to too high an increase in pressure loss. In this case, the best thing to do is to add nanoparticles to the fluid to obtain a new fluid called nanofluid. When the relevant literature is taken into account, it is seen that Al₂O₃/water is the most commonly used nanofluid.

In the comparison between BN and the widely used Al₂O₃, considering the heat transfer parameters, it is seen that BN is the more suitable nanoparticle with a very small increase in pressure losses. TiO₂ and CuO, which are also studied in numerical tests, are not suitable compared to BN and Al₂O₃ in terms of heat transfer with very small pressure differences.

4. Conclusions

In this paper, to obtain the effect of the use of boron nitride and other conventional nanoparticles (Al₂O₃, CuO and TiO₂) in a microchannel on pressure drop and heat transfer, the 3-D numerical simulations were assessed using the fluent CFD code of the microchannels. Al₂O₃, TiO₂, CuO and BN nanoparticles were used with water as a base fluid by changing the inlet Reynolds number and the volume fraction ratio. An evaluation was carried out to establish which of these four nanoparticles have superior properties in terms of pressure drop and heat transfer characteristics.

The pressure drop increased with the increasing Reynolds number, so it is clear that the consumption of pumping power directly increases. Moreover, the pressure drop also increased due to the increase of viscosity with the addition of 1% and 3% nanoparticles.

The heat transfer coefficient increased with the increasing Reynolds number, so it is clear that the thermal performance directly increases. Moreover, the thermal performance also increased due to the improvement of the thermal properties with the addition of 1% and 3% nanoparticles.

The maximum temperature decreases with the increasing Reynolds numbers because the thermal resistance decreases as the Reynolds numbers increases.

The properties of the fluid pair significantly affect heat transfer and pressure drop. It can be concluded that the improvement of the heat transfer and pressure drop in the microchannel relates to the properties of fluid pattern.

Compared to other conventional nanoparticles (Al₂O₃, CuO and TiO₂), BN improves heat transfer and slightly increases pressure drop due to its high thermal conductivity and high velocity profile due to low density. It is also chemically stable at the highest temperature relative to most solid materials. Thus, it has a structure that can be used in cooling systems for a long time without causing a problem of agglomeration.

The friction coefficient decreased with the increasing Reynolds numbers, and it was almost constant at high Reynolds numbers. The reason is that at low Reynolds numbers, viscous effects and the friction coefficient of the fluid flow are high. Viscous effects decreased with the increasing Reynolds numbers, therefore decreasing the effects of surface friction. The friction coefficient finally becomes almost constant.