Experimental Investigation of Convective Heat Transfer Using

Article pubs.acs.org/IECR

Experimental Investigation of Convective Heat Transfer Using Graphene Nanoplatelet Based Nanofluids under Turbulent Flow Conditions Emad Sadeghinezhad,† Mohammad Mehrali,*,‡ Sara Tahan Latibari,‡ Mehdi Mehrali,‡ S. N. Kazi,*,† Cheen Sean Oon,†,§ and Hendrik Simon Cornelis Metselaar‡ †

Department of Mechanical Engineering and ‡Department of Mechanical Engineering and Advanced Material Research Centre, University of Malaya, 50603 Kuala Lumpur, Malaysia § School of Built Environment, Liverpool John Moores University, Byron Street, Liverpool, L3 3AF, United Kingdom S Supporting Information *

ABSTRACT: An experimental investigation was performed to evaluate the heat transfer characteristics and the pressure drop of a graphene nanoplatelet (GNP) nanofluid in a horizontal stainless steel tube that was subjected to a uniform heat flux at its outer surface. The thermal conductivity and viscosity of the GNP nanofluids at concentrations of 0.025, 0.05, 0.075, and 0.1 wt % were measured prior to the heat transfer experiments. The heat transfer and the pressure drop within the flowing base fluid (distilled water) were measured and compared with the corresponding data from the correlations. The data were satisfied within a 5% error and a 95% confidence level. The effects of the nanoparticle concentration and the heat flux on the enhancement of the heat transfer turbulent flow condition are presented. The convective heat transfer coefficient of the GNP nanofluid is higher than that of the base fluid by approximately 13−160%. Further, the heat transfer coefficient of the GNP nanofluid increased as the flow rate and the heat flux increased. However, the increase in the pressure drop ranged from 0.4% to 14.6%. Finally, an analysis of the thermal performance factor reveals that the GNP nanofluids at concentrations of 0.075 and 0.1 wt % could function as a good and alternative conventional working fluid in heat transfer applications.

1. INTRODUCTION Energy transport is an integral part of a wide range of fields, including oil and gas, nuclear energy, and electrical energy.1,2 Water, oil, and ethylene glycol (EG) are used as heat transfer fluids. However, the development of heat transfer fluids with an improved thermal conductivity3 has become increasingly critical to the performance of energy systems.4 Choi and Eastman5 have introduced the term nanofluids, which refer to fluids that contain dispersed nanosized particles that have a higher thermal conductivity. Nanofluids improve thermo-physical properties,6 such as the thermal diffusivity and the thermal conductivity,7 provide excellent stability and convective heat transfer coefficients, and only slightly increase the pressure drop and required pumping power.8 Many studies have been conducted to enhance the thermal properties of heat transfer fluids by adding highly thermally conductive nanoparticles.9,10 Recently, a significant number of studies have been performed on carbonbased nanostructures,3 including carbon fiber,11 carbon black,12 carbon nanotubes (CNTs),13 graphite,14 graphene oxide (GO),15 graphene,16 and graphite flakes.17 An experimental investigation of the convective heat transfer coefficient for nanofluids flowing through different types of tubes has been conducted in several studies, and these have considered different types of nanoparticles, including oxides, nitrides, metals, diamond, and carbon-based nanoparticles.18,19 Early experiments with TiO2, Al2O3, and SiO2 nanofluids were undertaken by different researchers to determine the effect of the nanofluid concentration on the thermo-physical properties and the heat transfer coefficient.20 They observed an increase in © 2014 American Chemical Society

the convective heat transfer coefficients at various concentrations of the nanofluid under laminar and turbulent flow conditions from 20% to 350%. They concluded that the influence of the nanofluid concentration on the heat transfer coefficient is significant in the turbulent region versus the laminar region.21,22 However, only limited research has been performed on convective heat transfer when using carbonbased nanofluids as the heat transfer liquid compared with many results for the thermo-physical properties of nanofluids.21 This work is concerned with the convective heat transfer of GNP nanofluids. The reasons for choosing this topic are as follows: (a) no previous research has been performed on the convective heat transfer of GNP nanofluids and (b) the high thermal conductivity of GNP nanoparticles23 (as high as 3000 to 5000 W/m·K)4 may allow significant improvement in heat transfer.24 For this reason, additional studies and investigations on convective heat transfer are required to apply nanofluids in heat transfer systems. In the present work, aqueous suspensions of stable homogeneous GNP nanofluids were prepared by high-power ultrasonication. The stability and the thermo-physical properties of the GNPs have been reported previously by Mehrali, Sadeghinezhad, Latibari, Kazi, Mehrali, Zubir, and Metselaar.4 The objective of the present investigation is to experimentally Received: Revised: Accepted: Published: 12455

May 13, 2014 July 17, 2014 July 17, 2014 July 17, 2014 dx.doi.org/10.1021/ie501947u | Ind. Eng. Chem. Res. 2014, 53, 12455−12465

Industrial & Engineering Chemistry Research

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Figure 1. Experimental setup for the measurement of the convective heat transfer coefficient.

Figure 2. Sectional view of the experimental test sections.

Calibration Instruments, Denmark). The thermocouples were connected to the Graphtec (midi logger gl220), and the RTDs were connected to the Scada system for the continuous monitoring and recording of the temperature data by a personal computer. To minimize the heat loss to the surroundings, a thick glass wool wrapping was used. This insulation’s heat loss temperature was measured by three type-K thermocouples that were located on the outer surface of the insulation. The specifications and the accuracy of the measuring equipment used in the present experimental setup are presented in Table S1. 2.2. Data Processing. An investigation of the heat transfer behavior of the nanofluids was performed by evaluating the Nusselt number and the heat transfer coefficient. The measurements were performed in the bulk velocity range of 0.3 to 1.3 m/s for the distilled water and the GNP nanofluids, which caused the Re number to vary from 5000 to 22 000. Data were compared for a variety of flow rates with nanofluid concentrations of up to 0.1 wt %. The heat transfer coefficients were calculated based on the measured values for the inlet, outlet, and inner wall temperatures and the flow rate. The pressure drop over the tube was measured, and from these results, the friction factor was calculated. Comparisons of the Nusselt numbers or the heat transfer coefficients at an equal Reynolds number is unreliable and is uninteresting from a practical perspective.25 The comparison of nanofluids at the same Reynolds number is common in the literature for nanofluid fields.26−28 Based on many literatures, comparing the heat transfer at the same flow rates (pumping power) is considered a more appropriate method in a nanofluids study.26,29,30 Additionally, comparing the heat transfer coefficients for two different fluids at the same Reynolds number requires a higher flow rate (pumping power) for the fluid and a higher viscosity. Hence, the higher heat transfer at same Re number is not only because of the nanofluids performance, but

determine the heat transfer coefficient, the Nusselt number, and the friction factor of the turbulent flow for the GNP (specific surface areas of 500 m2/g) nanofluids flowing through a circular stainless steel tube. The effects on the convective heat transfer coefficient that is derived from the different heat fluxes (8231, 10351, 12320 W/m2) of the GNP nanofluid at different concentrations (0.25, 0.05, 0.075, and 0.1 wt %) under different bulk velocities range from 0.3 to 1.3 m/s (Reynolds number varies from 5000 to 22 000).

2. EXPERIMENTAL APPARATUS AND PROCESS 2.1. Experimental System. The experimental setup for this work is shown in Figure 1. It consists of a flow loop (with a bypass), a heating unit, a cooling part, measuring instruments, and a control unit. The flow loop includes a pump, a magnetic flow meter, a reservoir tank, a differential pressure transmitter, and a test section. The nanofluids were pumped from a 14-L capacity stainless steel jacketed tank by a Cole-Parmer magnetic drive pump at a flow rate of 0−10 l/m, and the pump flow was controlled by a Hoffman Muller inverter. The flow rate and the pressure loss were measured using a magnetic flow meter and a differential pressure transmitter, respectively. A straight stainless steel tube with a length of 1400 mm, a 12 ± 0.2 mm outer diameter, and a 10 mm inner diameter was used as the test section. The test section was heated using an ultrahightemperature heating tape (Omega, USA) at a maximum power of 900 W, which was linked to a Variac transformer and a watt/ amp meter. Five type-K thermocouples (Omega, Singapore) were fixed using a high-temperature epoxy glue at equal axial distances on the outer surface of the test tube (Figure 2). To measure the cold and hot nanofluid temperatures, two RTD (PT-100) sensors (Omega, Singapore) were inserted to measure the bulk temperature at the inlet and outlet of the test section. All thermocouples and RTDs were calibrated against an Ametek temperature calibrator (AMETEK Test & 12456

dx.doi.org/10.1021/ie501947u | Ind. Eng. Chem. Res. 2014, 53, 12455−12465


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might be due to the higher flow rate of nanofluids (for measuring at same Re number).26 Due to these reasons, it might be better choose constant velocity instead of constant Re number. Estimations of the heat flux, heat transfer coefficient, Nusselt number, friction factor, and Reynolds number are presented in eqs 1−6. (a) The heat flux is defined by eq 1. P V×I = πDL A

q″ =

(1)

(b) The convective heat transfer coefficient is calculated from the measured temperature data by eq 2.

h=

q″ Tw − Tb

Figure 3. Effects of temperature and concentration on the thermal conductivity of GNP nanofluids. (2)

ment of thermal conductivity for GNPs 500 was between 7.96% and 25%. The viscosity of the GNP nanofluids at a different weight percentage was measured by using an Anton Paar rheometer (Physica MCR 301, Anton Paar GmbH, Graz, Austria) at different temperatures with a 1% error rate. The viscosity of the nanofluids is one of the most critical parameters determining the quality of the heat transfer fluid. Similar to simple fluids, temperature is the main parameter affecting the viscosity of the nanofluids. Figure 4 shows the viscosity at a high shear rate of

The temperature profile between the thermocouple and the fluid inside the circular pipe and the bulk temperature are calculated using the Wilson plot method.29,31 The exact and real wall, the fluid temperatures, and the heat flux are measured to calculate the convective heat transfer coefficient. (c) The Nusselt number is defined by eq 3. Nu =

hD k

(3)

(d) The friction factor is defined by eq 4. f=

ΔP 2

( )( ρ2v ) L D

(e) The Reynolds number is defined by eq 5. 4ṁ Re = πDμ

(4)

(5)

(f) The Prandtl number is defined by eq 6.

Pr =

μCp k

(6) Figure 4. Viscosity of the GNP nanofluids as a function of temperature.

3. MATERIALS AND NANOFLUID PREPARATION To investigate the effect of the nanoparticles on heat transfer, the GNP nanofluid was prepared using a two-step method without any surfactant. As described in our previous work,4 GNPs (Grade C, XG Sciences, Inc., Lansing, MI, USA) were used for the preparation of nanofluids. The specifications of the GNP nanoparticle are shown in Table S2. The GNPs were dispersed in distilled water using a high-powered ultrasonication probe (Sonics Vibra-Cell, VC 750, Sonics & Materials, Inc., USA) that has a 750-W output power and a 20-kHz frequency power supply. The concentrations of the nanofluids were 0.025, 0.05, 0.075, and 0.1 wt %. 3.1. Measurement of the Effective Thermal Conductivity and the Viscosity of the Nanofluids. The thermal conductivity is measured by using a KD2 Pro thermal analyzer (KD2 Pro, Decagon Devices, Inc., Pullman, WA, USA), which works on the principle of a transient hot wire method with 2−4% accuracy. Figure 3 shows the effective thermal conductivity of the GNP nanofluids as a function of the temperature at different concentrations. The effective thermal conductivity increases as the nanofluid temperature increases in each case, and a linear dependence of the thermal conductivity enhancement on the temperature was obtained. The enhance-

500 s−1 for different concentrations as a function of temperature. While the viscosity of the nanofluids and the base fluids is strongly dependent on temperature, the viscosity decreased at higher temperatures, ranging from 9% to 38% compared with distilled water.

4. RESULTS AND DISCUSSION 4.1. Validation Test for Distilled Water. To validate the reliability of the experimental setup for calculating the Nusselt number and the convective heat transfer coefficient and for providing a baseline to compare the GNP nanofluid data, tests were initially conducted for distilled water (DW). The experimental results for DW at constant heat flux conditions were compared with the results from the standard equations, such as the Gnielinski, Petukhov, and Dittus−Boelter equations for turbulent flow.32 The Gnielinski equation for turbulent flow is given in eq 7 12457



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Figure 5. Measured average Nusselt number and the prediction correlations for distilled water versus the velocity at a different heating power: (a) 8231, (b) 10 351, (c) 12 320 W/m2.

validate the accuracy of the experimental setup with an error rate of less than 6%. The data from the experimental friction factor are derived from the measurements of the pressure drop along the length of the test section. To verify the friction factor data, the experimental results for DW are validated by the Blasius equation33 and the power law.29 Figure 6 shows the validation of the friction loss data from the experimental investigation, and the above-mentioned equations have an error rate of less than 10%.

f 8

( )(Re − 1000)Pr Nu = 1 + 12.7( ) (Pr − 1) f 0.5 8

2/3

(7)

which is applied in the range of 0.5 < Pr < 2000 and 3000 < Re < 5 × 106. The friction factor for a fully developed turbulent flow depends on the Re number and is calculated by the Colebrook equation, given in eq 8. f=

1 (1.82log10 Re − 1.64)2

(8)

The Dittus−Boelter equation for turbulent flow is given in eq 9 Nu = 0.023Re 0.8Pr 0.4

(9)

which is applied in the range of Re > 104, 0.6 < Pr < 200. The Petukhov equation for turbulent flow is given in eq 10 f 8

( )RePr Nu = 1.07 + 12.7( ) (Pr f 0.5 8

2/3

− 1)

(10)

Figure 6. Frictional head loss as a function of the velocity for distilled water.

which is applied in the range of 0.5 < Pr < 2000 and 3000 < Re < 5 × 106. Figure 5 shows a comparison between the experimentally average Nusselt number and the data from the abovementioned equations (eqs 7−10). The experimental data and classical correlations agree well. Data from the Petukhov equation and the experimental Nusselt number for distilled water are better than the data from the other equations and

4.2. Uncertainty Analysis of the Test Results. The uncertainty analysis of the measured data along with that of the relevant parameters obtained from the data reduction process is presented in Table 1 and is estimated based on the error propagation method.34,35 12458



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8231, 10 351, and 12 320 W/m2, respectively, at a weight percentage of 0.1 for the GNP nanofluids. Additionally, the Nusselt number (Nu) was increased up to 75%, 79%, and 83% for the heat fluxes of 8231, 10 351, and 12 320 W/m2, respectively. The convective heat transfer coefficient increased along with the fluid velocity and the particle concentration, which may indicate an improvement in the heat transfer potential of the GNP nanofluids compared with distilled water. In addition, the Nusselt number and the convective heat transfer coefficient were largely influenced by the particle’s Brownian motion, the thermo-physical properties (viscosity and thermal conductivity), and the specific surface area of the nanoparticles.36 Therefore, the higher concentration, heat flux, and nanofluid velocity increased the value of the convective heat transfer coefficient. The improved heat convection performance of the GNP nanofluid resulted from the higher

Table 1. Uncertainty Ranges variable name

uncertainty range

Nu, avg Nu, local h, avg h, local f

±6% ±8% ±6% ±9% ±10%

4.3. Convective Heat Transfer Coefficient of the Nanofluids. Figure 7 shows the variations of the Nusselt number (Nu) and convective heat transfer coefficient as well as the variation in the flow rate at different heat fluxes. Figure 8 shows the Nusselt number and the convective heat transfer coefficient at different heat fluxes for the 0.1 wt % GNP nanofluids. The convective heat transfer coefficient was increased up to 131%, 146%, and 160% for the heat fluxes of

Figure 7. Variation of the (a−c) Nusselt numbers and (d−f) convective heat transfer coefficients of the GNP nanofluids as a function of the velocity at different heat fluxes. 12459



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Figure 8. (a) Nusselt number and (b) heat transfer coefficient as a function of the velocity for 0.1 wt % of the GNP nanofluid at different heat fluxes.

Figure 9. Comparison of the local Nusselt number versus the nondimensional axial distance (x/d) at 0.1 wt % of the GNP nanofluid under various heat fluxes: (a) 8231, (b) 10 351, and (c) 12 320 W/m2.

the particles near the wall, particle migration, particle shape and rearrangement, the Brownian motion of the particles, the thermal conductivity enhancement, a reduction of the boundary layer thickness, and a delay in the boundary layer development.37,38 In addition, the thermal entry length for a fully developed flow in the turbulent region should be expressed as x ≥ 10Di.30 According to the experimental findings, there are two reasons for the convective heat transfer enhancement of the nanofluids: delay and disturbance of the thermal boundary layers and the excellent thermal conductivity enhancement of the GNP nanofluid. The chaotic movements created from the Brownian motion and the migration of GNP nanoparticles could affect the development of the thermal boundary layer in the entrance region.37 Figure 9 shows the local Nusselt number versus the axial position for 0.1 wt % of the GNP nanofluids at different velocities with three different heat fluxes. The local Nusselt

thermal conductivity of the nanofluid and the disordered movement of the GNP nanoparticles.36 A significant enhancement in the Nusselt number and the convective heat transfer coefficient up to 0.1 wt % of the GNP nanofluid was due to the improved thermal conductivity and the reduced thermal resistance between the flowing nanofluid and the inner wall surface of the tube. Figure 7f shows the largest enhancement of the convective heat transfer coefficient, which was 18%, 48%, 88%, and 160% for the 0.025, 0.05, 0.075, and 0.1 wt %, respectively, at a heat flux of 12,320 W/m2. This substantial enhancement is obtained by adding a very small amount of GNP nanoparticles to the distilled water. In the present investigation, the highest enhancement of the thermal conductivity was observed at approximately 25% of 0.1 wt % of the GNP nanofluid. Previous studies claimed that the reasons for the heat transfer enhancement of the nanofluids included the mixing effects of 12460



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Figure 10. Variation of (a) friction factor and (b) pressure drop of the GNP nanofluid as a function of the velocity.

number could be calculated from the measured data, including the bulk and wall temperatures and the heat flux of the test section. The results clearly show negligible variations in the Nusselt number data of the GNP nanofluids under the fully developed condition of the turbulent flow region and the local Nusselt number in the thermally developing region because there is a slight enhancement of the local Nusselt number. In the thermally developed region, the surface temperature will also increase linearly in the flow direction because the heat transfer coefficient is constant. Thus, the difference between the local and the bulk mean fluid temperatures are constant and are independent of the axial position. At a short distance from the end of the heated section in the thermal entry region, both the wall and bulk temperatures tend to be the same value, which is dependent on the overall heat balance. The results in Figure 9 also show that the temperature difference of the wall and bulk liquid increases as the heat flux increases. Table S3 summarizes the convective heat transfer results for different nanofluids. The available experimental data from different research groups vary widely, and further investigations are necessary to clarify the results.14,24,39−43 4.4. Pressure Drop of the Nanofluid. To use the nanofluids in practical applications, the flow features of the GNP nanofluids should be determined in addition to the heat transfer measurements. The experimental results show that the pressure drop and the friction factor depend on the GNP concentration and the flow velocity (Figure 10). Table 2 shows the pressure drop increments of the GNP nanofluids for different flow velocity ranges of 0.3−1.3 m/s.

The design of a heat exchanger for efficient heat transfer and minimum pumping power is important in terms of energy savings and could cause considerable errors when assessing the performance of nanofluids (pumping power and heat transfer) in various thermal applications. In the actual case of a fully developed condition and a turbulent region in a circular tube with uniform heat flux at the wall, the expression for the pumping power could be introduced by eq 11.44 0.25 ⎛ Ẇ ⎞ ⎛ μ ⎞ ⎛ ρbf ⎞2 ⎜ ⎟ = ⎜⎜ ⎟⎟ ⎜ ⎟ ⎝ Ẇ bf ⎠ ⎝ μ bf ⎠ ⎝ ρ ⎠

Figure 11 shows that the pumping power increases linearly with the GNP nanoparticle concentration. Compared with

Figure 11. Effect of the GNP nanofluid concentrations on the pumping power.

Table 2. Pressure Drop Increment of the GNP Nanofluids concentration (wt %)

increment (%)

0.025 0.05 0.075 0.1

0.4−9.1 1−10.2 2.8−13.1 3.4−14.6

(11)

distilled water, no significant augmentation in the pressure drop and in the pumping power was required (Figures 10a and 11) for the GNP nanofluids in any of the experimental runs; there was only a minor pumping power penalty due to the enhanced viscosity of the nanofluids. The effect of the GNP nanoparticles is small, and the GNP nanofluids behave similarly to pure fluid. In conclusion, for the heat transfer performance of the GNP nanofluid compared with the base fluid at a constant Reynolds number or at a constant flow rate, the data from a constant flow rate comparison show good results under certain conditions, such as the use of the same pumping power for the nanofluid and the base fluid. The thermal performance factor of the GNP nanofluid can be used to evaluate the usefulness of GNP nanofluids for application in thermal systems. The thermal performance factor is defined by eq 12, and a higher thermal performance factor indicates greater usefulness.45

The increased pressure drop and friction factor appear based on the viscous drag effects of the GNP nanofluids. This expression could be validated from eq 4, wherein the friction factor as a function of the pressure drop was primarily influenced by the density gradient of the GNP nanofluids that resulted from an increase in the GNP nanoparticle concentrations. The GNP nanoparticle density is an important parameter for the increased friction factor and pressure drop of the nanofluids.36 12461



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Figure 12. Variations of the thermal performance factor with the velocity at different heat fluxes: (a) 8231, (b) 10 351, and (c) 12 320 W/m2. 1/3 ⎛ Nu ⎞ ⎛ f ⎞ η=⎜ ⎟ /⎜⎜ ⎟⎟ ⎝ Nubf ⎠ ⎝ fbf ⎠

(12)

Figure 12 shows that the thermal performance factor of the GNP nanofluid at a higher heat flux is higher than at a lower heat flux and increases as the velocity increases. This is a result of the superior efficiency of the fluid disturbance and thus the heat transfer caused by the higher thermal conductivity values at the same pumping power. It also shows that the lowest concentration and the higher velocity of the GNP nanofluid are not as advantageous because the heat transfer enhancement effects are mitigated by the unfavorable effects of the pressure drop augmentation. The highest thermal performance of the GNP nanofluid increased to 1.66, 1.70, and 1.77 for the GNP nanofluid at 8231, 10 351, and 12 320 W/m2, respectively, for a 0.1 wt % concentration. Finally, an analysis of the heat transfer and the pressure drop data via the thermal performance factor reveals that in spite of the pressure drop and the pumping power penalty, the GNP nanofluid at concentrations of 0.075 and 0.1 wt % is a good alternative for conventional working fluids in heat transfer applications. In order to verify the performance of GNP nanofluid at 0.1 wt %, the entropy generation of nanofluid was calculated. The entropy generation analysis of nanofluids is known as a useful application to analyze thermal design optimization through minimizing it, and then better working conditions can be performed for a heat exchangers.1,8,9 Figure 13 shows that the entropy generation of GNP nanofluid at 0.1 wt % and 1.3 m/s was decrease by increasing of heat flux. Entropy generation shows the irreversibility of the system, therefore the reduction in Entropy generation value will make the energy systems more efficient.

Figure 13. Entropy generation of GNP nanofluid versus heat flux at 0.1 wt % and 1.3 m/s.

4.5. Wettability Effects of GNP Nanofluid. Wettability is the ability of a liquid to maintain contact with a solid surface. In heat transfer systems, the wettability effect of the working fluid on the solid surfaces is generally considered. Surface forces (cohesive and adhesive forces) control the wettability of the surface. Wettability studies usually involve the measurement of the contact angles (θ) as the primary data, which indicates the degree of wetting when a solid and liquid interact. As the tendency of a drop to spread out over a solid surface increases, the contact angle decreases, and the deformation of the drop due to gravity was considered to be negligible because of its small surface area. Figure 14 shows the images of the contact angles for the GNP nanofluid when it was spread on a solid surface at 25 °C. The contact angle of the distilled water (DW) on the solid surface was 99.8°, which was decreased to 95.3°, 95.1°, 94.5°, and 93.5° for the GNP nanofluid at 0.025, 0.05, 0.075, and 0.1 wt %, respectively. The contact angle of the GNP nanofluid decreased compared with the base fluid, which 12462



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GNPs was provided using the improved thermal conductivity and the reduced thermal resistance that were offered by the GNP nanofluid on the inner wall surface of the tube. 6. The pressure drop and the friction factor of the nanofluid increased by 0.4% to 14.6% compared to the base fluid. Therefore, the nanofluid results in only a minor penalty in terms of the pumping power, which indicates that it is suitable for practical applications. 7. An increase of the thermal performance could be obtained as 1.66, 1.70, and 1.77 for the GNP nanofluid at 8231, 10 351, and 12 320 W/m2, respectively, for a 0.1 wt % concentration. The GNP nanofluid at concentrations of 0.075 and 0.1 wt % provides a good option for the replacement of the conventional working fluids in heat transfer applications. 8. The contact angle of the GNP nanofluid decreases compared with the base fluid, which improves the wettability of the nanofluids and leads to an enhanced heat transfer coefficient. Additional work is required to investigate the effects of the different GNP nanoparticle concentrations and the different parameters of the convective heat transfer coefficients and flow features of the GNP nanofluids.

Figure 14. Contact angle image of the base fluid and the GNP nanofluid at different concentrations.

improves the wettability of the GNP nanofluids and leads to a reduction of the contact angle. The wettability is an effective parameter for the heat transfer coefficient and the friction factor, especially for heat transfer to two-phase flow, and higher contact angle surfaces tend to decrease the heat transfer coefficient compared with the lower contact angle surfaces.46 The initial equilibrium contact angle of the nanofluids was significantly affected by the nanoparticle sizes and concentrations. Nanofluid molecules tumble along the tube wall, similar to two solid surfaces sliding over one another, when the forces between the nanofluid and the tube wall molecules are not strong enough to overcome the shear forces at the wall. This decoupling of the nanofluid from the wall results in a lower frictional pressure drop. Therefore, the lower contact angle provided more friction drop because of the adhesive force between the nanofluids and the tube wall.46

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ASSOCIATED CONTENT

S Supporting Information *

Test rig specification, the GNP nanoparticles’ specification, and summary of the previous heat transfer work. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail address: [email protected] (M.M.) *E-mail address: [email protected] (S.N.K.). Phone: 0060 3 7967 4582. Fax: 0060 3 7967 5317. Author Contributions

The manuscript was written using the contributions of all the authors. All authors read and approved the final manuscript.

5. CONCLUSIONS The convective heat transfer performance and the flow characteristics of a GNP nanofluid flowing in a horizontal tube with various heat fluxes in a fully developed turbulent region were experimentally investigated. Aqueous GNP nanofluids with various concentrations ranging from 0.025 to 0.1 wt % were prepared using a two-step method without any surfactant. The convective heat transfer characteristics and the pressure drop were measured for the flow through a circular tube. The following conclusions were obtained. 1. Thermal conductivity increases as the nanofluid temperature increases, and the enhancement in thermal conductivity for the GNP nanofluid was between 7.96% and 25%. 2. The GNP nanofluid viscosity was strongly dependent on the temperature. It decreased at higher temperatures, and their increment was 9−38% compared with distilled water. 3. The use of the GNP nanofluid provides significantly higher heat transfer coefficients up to 160%. 4. The convective heat transfer coefficient increases as the flow rate and heat flux increase. 5. A significant enhancement of the convective heat transfer coefficient and the Nusselt number up to 0.1 wt % of the

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research work has been financially supported by the High Impact Research (MOHE-HIR) grant UM.C/625/1/HIR/ MOHE/ENG/21, the UMRG grant RP012D-13AET, and the University of Malaya in Malaysia. The authors wish to thank the Bright Sparks unit (University of Malaya) for additional financial support.

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ABBREVIATIONS Cp = specific heat capacity, J/kg·K D = tube diameter, m DW = distilled water f = friction factor h = convective heat transfer coefficient I = electrical current, A k = thermal conductivity, W/m·K L = tube length, m Nu = Nusselt number P = heater power, W Pe = Péclet number dx.doi.org/10.1021/ie501947u | Ind. Eng. Chem. Res. 2014, 53, 12455−12465


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Pr = Prandtl number q″ = heat flux, W/m2 Re = Reynolds number T = temperature, K V = volts, V v = mean velocity, m/s w = water W = watt x = axial distance Greek

ΔP = pressure drop, Pa wt % = weight percentage ϕ = nanoparticle volumetric fraction μ = viscosity, Pa.s ρ = density, kg/m3 η = thermal performance factor Subscripts

avg = average b = bulk bf = base fluid i = inner in = inlet m = mean nf = nanofluid np = nanoparticle o = outer out = outlet w = wall

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