Comparative study between metal oxide nanopowders on thermal characteristics of nanofluid flow through helical coils

Powder Technology 246 (2013) 82–92

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Comparative study between metal oxide nanopowders on thermal characteristics of nanofluid flow through helical coils M. Kahani, S. Zeinali Heris ⁎, S.M. Mousavi Chemical Engineering Department, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad, Iran

a r t i c l e

i n f o

Article history: Received 13 December 2012 Received in revised form 23 February 2013 Accepted 4 May 2013 Available online 10 May 2013 Keywords: Metal oxide nanopowders Nanofluid Helical coils Thermal performance

a b s t r a c t Nanofluids and helical coils are two different techniques to enhance thermal performance of highly efficient heat exchangers. By combining these techniques together, energy efficiency of equipments could be increased dramatically. The present study is an experimental comparison of heat transfer behavior between metal oxide nanofluid flows through helical coiled tube with uniform heat flux boundary condition. Nanofluids with required volume concentration of 0.25–1.0% were prepared by dispersing specified amounts of Al2O3 (35 nm) and TiO2 (50 nm) nanoparticles and appropriate amount of surfactants in distilled water. The experiments covered a range of Reynolds number from 500 to 4500. Experimental results indicated that a considerable heat transfer enhancement is achieved by both nanofluids. In addition, because of greater thermal conductivity and smaller size of Al2O3 nanoparticles compared to TiO2 nanoparticles, Al2O3/water nanofluid showed better heat transfer augmentation. Moreover, due to the curvature of the tube when fluid flows inside helical coiled tube instead of straight one, convective heat transfer coefficient and the pressure drop of both nanofluids grew dramatically. Besides, experiments indicated that the effect of coil pitch spacing is to some extent weaker than the curvature ratio effect on the heat transfer rate. Finally, it was studied that the experimental and predicted results of Nusselt number and pressure drop held reasonable agreement. © 2013 Elsevier B.V. All rights reserved.

1. Introduction With the increasing heat transfer rate of the heat exchange equipment, a conventional process fluid with low thermal conductivity can no longer meet the requirements of high-intensity heat transfer. The low thermal property of the heat transfer fluid is a primary limitation to the development of high compactness and effectiveness of heat exchangers. Nanofluid is defined as a conventional fluid with suspended particles at nanometer size (normally up to 100 nm). In the last two decades a lot of researchers reported about this new engineered fluid and most of the published papers emphasized that adding a small amount of nanoparticles to a normal thermal fluid (water, oil, ethylene glycol,…etc.) can increase thermal conductivity and heat transfer properties [1]. On the one hand, nanofluids can be considered to be the next generation heat transfer fluids as they offer exciting new possibilities to enhance heat transfer performance compared to pure liquids. Addition of nanoparticles into heat transfer fluids could have the potential for heat transfer enhancement in pipe flow without paying the penalty of increasing pumping power [2]. Compared to conventional solid/liquid suspensions for heat transfer intensifications, nanofluids Abbreviation: HCT, helical coiled tube. ⁎ Corresponding author. Tel.: +98 511 8816840; fax: +98 511 8805108. E-mail address: [email protected] (S. Zeinali Heris). 0032-5910/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.powtec.2013.05.010

possess the following advantages: (a) high specific surface area and therefore more heat transfer surface between particles and fluids; (b) high dispersion stability with predominant Brownian motion of particles; (c) reduced pumping power as compared to pure liquid to achieve equivalent heat transfer intensification; (d) reduced particle clogging as compared to conventional slurries, thus promoting system miniaturization [3]. Preparation and application of nanoparticles and also the effects of particle size, particle volume fraction, temperature dependence, properties of base liquid and particle phase on effective thermal conductivity of nanofluid have been emphasized by several researchers [4–14]. Also, the importance of actual agglomerated particle size in the nanofluid and its effect on the fluid properties have been considered by Yang et al. [15]. Rea et al. [16] have studied laminar convective heat transfer and viscous pressure loss for Al2O3/water and zirconia/water nanofluids flowing in a vertical heated tube which showed that the heat transfer coefficient was increased by the nanofluids. Also the measured pressure loss for the nanofluids was much higher than pure water and the pressure loss of the 6.0 vol.% alumina nanofluid was approximately 7.2 times higher than that of water. Duangthongsuk and Wongwises [17] have investigated experimentally the forced convective heat transfer and flow characteristics of a nanofluid consisting of water and 0.2 vol.% TiO2 nanoparticles. Their results indicated that use of a nanofluid had hardly any penalty in pressure drop. Also, considerable enhancement

M. Kahani et al. / Powder Technology 246 (2013) 82–92

Nomenclature A b Cp d D De f h He k L _ m N Nu Pr Re R 2adj. T U

inner surface of tube (m 2) pitch of coil (m) specific heat (J kg −1 K −1) inside diameter of tube (m) diameter of coil (m) Dean number Fanning friction factor e heat transfer coefficient (W m −2 K −1) Helical coil number thermal conductivity (W m −1 K −1) length of tube (m) mass flow rate (kg s −1) number of coil turns average Nusselt number Prandtl number Reynolds number adjusted correlation coefficient temperature (K) average velocity (m s −1)

Greek letters ΔP axial pressure drop (Pa) η thermal performance factor ρ density (kg m −3) μ dynamic viscosity (Pa s) λ curvature ratio (=D/d) φ nanoparticle volume fraction (%)

Subscripts b bulk C coiled tube f base fluid nf nanofluid p particle S straight tube w wall

for both the convective heat transfer coefficient and the Nusselt number of the TiO2/water nanofluid through a cylindrical mini channel under laminar flow and constant wall heat flux conditions have been reported by Murshed et al. [18]. Zeinali Heris et al. [19,20] have considered the convective heat transfer of Al2O3/water and CuO/water nanofluids in circular tubes and observed that the heat transfer coefficient enhances by increasing the concentration of nanoparticles in the nanofluids. It was obtained from the experimental investigation of Nassan et al. [21] on the heat transfer characteristics of Al2O3/water and CuO/water nanofluids through a square cross-section duct that CuO/water nanofluid gives better enhancement in heat transfer than Al2O3/water nanofluid. Hamed Mosavian et al. [22] have employed aqueous solutions of metallic and oxide nanoparticles to study the forced convective heat transfer under constant wall temperature. Their result revealed that nanofluids that contain metal nanoparticles (Cu/water) show more enhancements compared to oxide nanofluids (Al2O3/water and CuO/ water). Also, they emphasized that there is an optimum concentration for each nanofluid in which more enhancements are available that is related to viscosity by increasing particle concentration. For Al2O3/water nanofluid with volume fraction of 7.5% of nanoparticles, 45% increment in the average wall heat transfer coefficient has been

83

achieved by Palm et al. [23] for the same Reynolds numbers. Conversely, Pak and Cho [24] have expressed that the convective heat transfer coefficient of Al2O3/water and TiO2/water nanofluids with concentration of 3.0 vol.% was 12.0% smaller than that of pure water. On the other hand, curved tubes have been used as one of the most effective heat transfer enhancement techniques and are the most widely used tubes in several heat transfer applications [25]. The facts concerning the working principle of curved tubes and reasons for its enhanced performance are well established as mentioned [26]: (a) generation of secondary flow due to unbalanced centrifugal forces; (b) enhanced cross-sectional mixing; (c) reduction in axial dispersion; (d) improved heat transfer coefficient; (e) improved mass transfer coefficient. Dean [27] has done an earlier theoretical work on fluid motion in a curved pipe using a perturbation technique. He predicted the characteristics of the twin-vortex secondary flow and pointed out that the dynamic similarity of such a flow depends on a dimensionless parameter, De, called the Dean number, which is defined by De = Re (d / D) 1/2. The Dean number characterizes the intensity of the cross stream flow driven by an imbalance between centrifugal and radial pressure gradient induced forces. Flow in curved tube is higher than that for straight tube at the same flow rate and tube length. Many researchers have been conducted regarding fluid flow in helical coiled tubes with circular cross-sections. The use of both active and passive techniques to enhance the heat transfer rate was reported by Cengiz et al. [28]. They have studied the effect of rotation of helical pipes on the heat transfer rates and pressure drop for various air-flow rates. Their results showed that although the rotation caused an increase in pressure drop, the heat transfer rates were augmented. Jamshidi et al. [29] have highlighted the significant effects of coil diameter and coil pitch on thermal performance of nanofluid in helical coils. Akhavan-Behabadi et al. [30] have emphasized that utilizing vertical helical coiled tubes instead of straight ones enhances the heat transfer rate remarkably. Besides, nanofluid flows showed much higher Nusselt numbers compared to the base fluid flow. They used multiwall carbon nanotube in heat transfer oil to run their experiments and reported that the Nusselt numbers acquired for the heat transfer oil inside tested helical coils were 3 to 7 times higher than the values evaluated for the base fluid inside straight tubes with a similar length of the coils. Hashemi et al. [31] have argued that applying helical tubes instead of the straight tubes is a more effective way to enhance the convective heat transfer coefficient compared to using nanofluids instead of the pure liquid. Last but not the least, Mukesh Kumar et al. [32] have reported 55% and 26% enhancement in Nusselt number and friction factor, respectively for Al2O3/water nanofluid turbulent flow in helical coiled tube. Due to the advantages of accommodating large heat transfer area within a small space, high heat transfer coefficient and small residence time distribution, tube coils are extensively used in industries as heat exchangers and reactors. Moreover, nanofludics is an excellent way to enhance the heat transfer rate. So by combining these techniques together, remarkable efficiency enhancement of heat transfer equipments can be obtained. In addition, oxide nanopowders are the most commonly used particles because of their low prices and special properties. In the present investigation, by designing the experimental setup with constant heat flux boundary condition, the heat transfer performance and pressure loss of two metal oxide (Al2O3 and TiO2) nanofluids through helical coiled tubes in various concentrations and in the ranges of flow rates that the flow remains laminar are investigated and the increase of pure water heat transfer and pressure drop which resulted from the adding of nanoparticles is evaluated. 2. Preparation and property of nanofluids In this study, the water-based nanofluids of different nanoparticles including Al2O3 and TiO2 have been employed. Thermophysical

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characterizations of nanopowders and also equations which are used to evaluate the physical properties of distilled water are shown in Table 1. The purity of nanopowders which are used in this study was 99.0% and the exact content of nanopowders is shown in Table 2. These 1.0% impurities can decrease the thermal conductivity of nanoparticles in comparison of 100% purified nanopowders considerably. The nanofluid in 0.25, 0.5, 0.75 and 1.0 vol.% concentrations was prepared. Fig. 1 shows that the TEM (transmission electron microscopy) images of nanoparticles dispersed in distilled water and reveal that both kinds of nanoparticles have a spherical shape. There are several procedures to produce stable nanofluid. Among them, using a stabilizer, a dispersant, a surface activator and an ultrasonic vibrator can be cited. Within these methods, surface modification attracts more attention because of its versatility, low cost and technological advantages [34]. Without using suitable surfactants, the tested nanofluids could be stabled for a maximum of 45 min while surfactant can improve stability of nanofluids dramatically. In this study, Cetyltrimethyl Ammonium Bromide (CTAB) and Triton X-100 were used as surfactant for TiO2 and Al2O3 nanoparticles, respectively. The required amounts of nanoparticles and optimum amounts of their related surfactant were mixed with distilled water by a high-speed stirrer. Then, sonication was done continuously by ultrasonic processor (Hielscher, UP400S) for at least thirty minutes to obtain a more stable and evenly dispersed nanoparticle suspension. No settlement of nanoparticles was observed after 45 days for TiO2/ water and after 48 h for Al2O3/water nanofluids. The settlement period difference between Al2O3/water and TiO2/water is due to larger surface area per mass of alumina than Titan oxide nanopowders. Al2O3 nanopowders have very large surface areas relative to their mass (160 m2/g), which result in strong inter-particle interactions and induce strong tendency of agglomeration, rapid sedimentation and consequently limited mobility of nanoparticles in the aquatic environment than TiO2 nanopowders [35]. Besides, the larger surface area to mass requires more surfactant to cover all parts of the surface which can increase the sedimentation rate of nanopowders. The thermophysical properties of the prepared nanofluids were calculated from water and nanoparticle characteristics at bulk temperature using the following equations for density, specific heat and viscosity [36–38]. ρnf ¼ φ : ρs þ ð1−φÞ:ρw

Cpnf ¼

μ nf ¼

ð1Þ



 φ : ρp : Cpp þ ð1−φÞ : ρf : Cpf

ð2Þ

ρnf μf

ð3Þ

ð1−φÞ2:5

A detailed summary of all classical models for the prediction of the thermal conductivity of nanofluids has been provided by Murshed et al.

Table 2 Certificate of analysis (contents of elements) of nanopowders. Al2O3

Ca

V

Cl

Na

Mn

Co

99%

25 ppm

7 ppm

315 ppm

70 ppm

3 ppm

2 ppm

TiO2

Al

Mg

Si

Ca

S

Nb

99%

17 ppm

65 ppm

120 ppm

75 ppm

130 ppm

80 ppm

[39]. Among existing models, the Wasp model is more suitable to predict the thermal conductivity of spherical particles [40].
 knf kp þ 2kf −2 kf −kp : φ
 ¼ kf kp þ 2kf þ kf −kp : φ

ð4Þ

3. Experimental setup and procedure The experimental setup (Fig. 2) consists of test sections, cooling unit, pump, manometer, dampener, flow rate measuring unit and a fluid reservoir. As shown in Table 3, three copper helical coiled tubes (HCT) with different geometries and a straight tube were used in the test sections. In fabricating the coil, the straight tube was first filled with shock-compacted fine-grain sand to minimize distortion of the circular cross section. Winding was done manually over special cylindrical modules (Fig. 3) to form helical coils with desired geometries. Tubes were equipped with straight entry and exit hydrodynamic lengths made of flexible plastic (nonconductive) pipes of the same inner diameter as the tubes. The entry length, about 30 tube diameters, was used as a hydrodynamic development length, while the exit length was about 15 tube diameters. Both lengths were attached tangentially to the tubes. To obtain a constant heat flux boundary condition, the electric resistance was utilized around the heat transfer section. The heat flux was set by adjusting the electrical voltage with the help of an autotransformer and the constant heat flux was allowed to continue till the steady state is obtained. Also, in order to minimize heat loss to the surroundings, all heat transfer sections were isolated by two thick layers of rock wool and fiberglass sheets as well. Two (PT100-type) thermocouples were inserted into the calming and mixing chambers of the flow at inlet and outlet of each test section for measuring the bulk temperatures of working fluids and other thermocouples from the same type were inserted through the little soldered tubes on the surface of the each test section at different points over the tubes. The accuracy of the all thermocouples was ± 0.1% of full scale. A differential U-tube manometer was fitted across the test sections to measure the pressure drop along the tubes. Moreover, to minimize the vibration of fluid flow, a flow dampener was also located before the test section. Besides, flow rate is measured directly from the time required to fill a glass vessel.

Table 1 Thermophysical characterizations of nanopowders and base fluid. Particle/base fluid

Average diameter (nm)

Al2O3 (γ) TiO2 (rutile) Distilled water⁎

35 99 3690 >160 50 99 3900 40 2 2.5 −5 3 T ρ = 999.7968 + 0.0683 T − 0.01074 T + 0.0008214 T − 2.30309 × 10 Cp = 4.2174 − 0.005618 T + 0.001299 T1.5 − 0.0001153 T2 + 4.14964 × 10−6 T2.5

Purity (%)

1 μ ¼ 557:8248þ19:4084 Tþ0:13604 T 2 −3:1160810−4

Actual density (kg/m3)

Surface area to mass (m2/g)

T3

k = 0.56502 + 0.002636 T − 0.0001251 T1.5 − 1.51549 × 10-6 T2 − 0.00094129 T0.5 ⁎ All temperatures in degrees Celsius [33].

CP (J/kg·K)

k (W/m·K)

780 710

30.5 13.7

M. Kahani et al. / Powder Technology 246 (2013) 82–92

85

Fig. 1. TEM images of nanoparticles.

After filling the reservoir tank with nanofluid, the pump and the cooling heat exchanger were switched on. Then electric resistance was turned on and the temperature of the test section started to increase. Using bypass line the flow rate was adjusted. After the fluid passing the heated test section flowed through the cooling unit, it finally collects in the reservoir. Experiments were conducted for straight tube and subsequently for helical coils at different flow rates and volume concentrations of nanofluids. Through initial tests it has been found that the system needs 30–35 min to reach the steady state condition and after that the readings could be taken. Each measurement was repeated at least two times. The essential parameters that were measured include electric power inputs, flow rate, bulk temperatures (inlet and outlet), outer wall temperatures and pressure drops of working fluid along the coils.

4. Data processing Considering fluid passing through a tube with constant heat flux, the convective heat transfer coefficient and Nusselt number resulting from heat balance are as follows:

h ð expÞ ¼


 _ : Cp : T b −T b m 1 2

Nu ð expÞ ¼

A : ðT w −T b ÞM h ð expÞ : d k

ð5Þ

ð6Þ

in which (Tw − Tb)M is the logarithmic mean temperature difference.

Fig. 2. The schematic of experimental apparatus.

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M. Kahani et al. / Powder Technology 246 (2013) 82–92 −1=4

Table 3 Physical dimensions of helical coils and straight tube. Tube

d (mm)

t (mm)

L (mm)

D (mm)

λ

b (mm)

N

HCT-I HCT-II HCT-III Straight tube

7

0.5

1318.8

140 70 70 –

20 10 10

24 42 24

3 6 6

f S;Turbulent ¼ 0:079Re

ð14Þ

fC 1=4 ¼ 0:47136De fS

ð15Þ

Also, three important dimension parameters in the nanofluid flow through helical coils, including Reynolds number (Re), Prandtl number (Pr) and Helical number (He) are defined as follows:

Also, the criterion for transition from laminar to turbulent flow in curved pipes was established experimentally by Kubair et al. [46] and can be represented by Rcri. = 12,730 / λ 0.32. HCTs in this study have curvature ratios λ = 10 and 20, therefore the related critical Reynolds numbers are 6092 and 4880, respectively. So, in order to take a laminar flow inside the coils, all tests were done at Re b 4500.

Re ¼ ρ : U : d=μ

ð7Þ

5. Experimental uncertainty

Pr ¼ μ : C P =k

ð8Þ

   1=2 b 2 He ¼ De 1 þ 2πD

ð9Þ

where U is the average velocity in the coiled tube. The theoretical equations for predicting the Nusselt number of laminar flow through straight tube and HCT have been presented by Seider and Tate [41] and Manlapaz and Churchill [42] in the following forms:     d 1=3 μ 0:14 NuS ¼ 1:86 Re:Pr: L μw 82 9 33 " #3=2 >1=3 > < 48 = 51=11 7 He 6 NuC ¼ 4 þ
2 5 þ 1:86 1:15 > > 1 þ Pr : 11 ; 1 þ 1342

ð10Þ

ð11Þ

where μw in Eq. (3) is the viscosity of fluid at wall temperature. Moreover, the pressure drop in the axial direction of straight tube can be obtained from the following equation [43]: ΔP S ¼

L d

ρU

2

ð12Þ

2

where fS is the Fanning friction factor for straight tube. After replacing the fS by fC and also L by LC (length of the coiled portion of the coil), Eq. (12) also can be used to evaluate the pressure drop of fluid flow through HCT. To predict the Fanning friction factor of straight and helical coils the following correlations can be applied [44,45]. f S;Laminar ¼ 16=Re

U Pi ¼

X i ∂P U P ∂X i X i

ð16Þ

in which Xi is the measurable parameter, P is the calculated quantity from measurable parameter, UXi is the measuring error and UPi is the maximum error of a parameter. The effect of all errors in calculation of goal function can be summarized as follows [48]: " 2  2  2 #0:5 X 1 ∂P X 2 ∂P X i ∂P U1 þ U2 þ … þ U Xi : P ∂X 1 P ∂X 2 P ∂X i

MaxU P ¼ 

ð17Þ

Pr:He2

4f S

Eq. (16) is a general relation for prediction of experimental errors [47]:

ð13Þ

The uncertainty of the experimental data may have resulted from measuring errors of parameters such as mass flow rate, inlet and outlet temperature difference, the logarithmic mean temperature difference between surface and fluid and also thermal conductivity and specific heat of nanofluid. It can be calculated using Eq. (17) for the Nusselt number:  0:5
2
2
2 2 2 MaxU Nu ¼  ðU m_ Þ þ U Cp þ U ðT b1 −T b2 Þ þ −U ðT w −T b ÞM þ ð−U k Þ :

ð18Þ Flow rates were measured directly from the time taken to fill a glass vessel of known volume with 4.0% uncertainty in measurement. Also, the uncertainty of the temperature difference is calculated at 0.74%. Wasp and Einstein relations (Eqs. (4) and (2)) that are used in this study to predict thermal conductivity and specific heat of nanofluid have the appropriate agreement with experimental studies of spherical particles. By assuming 4.0% and 2.0% uncertainties for thermal conductivity and specific heat of nanofluids respectively, the maximum uncertainty of the Nusselt number calculated taking into account the above considerations is obtained at 6.09%. 6. Results and discussion 6.1. Validation check

Fig. 3. Helical coils with their special modules.

In order to validate and estimate the accuracy of the experimental results, values of Nusselt number for distilled water are compared with exiting correlations for straight tube and HCTs. Fig. 4 shows the variation of theoretical values (Eqs. (10) and (11)) with experimental values for Nusselt number. As it is seen from this figure, the deviation of the experimental data from the theoretical one is within −19% and +32%. Moreover, to verify the validity of measured pressure drop through the tubes, a comparison between theoretical and empirical pressure drops has been done. Fig. 5 depicts the variety of the theoretical values for pressure drop (Eqs. (12)–(15)) along the test section versus measured pressure drop. As it can be seen from Fig. 5, the deviation of the

M. Kahani et al. / Powder Technology 246 (2013) 82–92

45

Table 4 The effects of surfactants on Nusselt number for 0.25 vol.% concentration of nanofluid flows through HCT-II.

HCT No.1

40

+32%

HCT No.2

35

Particle

Theoritical Nu

HCT No.3

30

87

Re

Nu

-19%

Straight tube

25

Al2O3

20

TiO2

4265 905 3915 862

15

With surfactant

Without surfactant

Deviation (%)

47.3 21.3 46.2 21.1

48.1 21.9 46.7 21.3

−1.69 −2.82 −1.08 −0.95

10 5 0 0

5

10

15

20

25

30

35

40

45

Experimental Nu Fig. 4. The comparison between theoretical and experimental Nusselt numbers of distilled water flow inside tubes.

experimental data from the theoretical one is within −27% and +19%. Accordingly, for both Nusselt number and pressure drop the experimental results show reasonable agreement with the theoretical correlations which confirms the reliability and accuracy of the experimental procedure. The experiments were performed for a wide range of (500–4500) Reynolds number and for various concentrations of Al2O3 and TiO2 nanopowders (0.25–1.0 vol.% concentration) inside helical coiled tubes with different geometries and straight one. As shown in Table 4, since the amount of surfactants which are used in the experiments is not considerable, there are no noticeable effects on heat transfer rate.

6.2. Heat transfer study Fig. 6 demonstrates the heat transfer coefficient for nanofluids through HCT-I versus Reynolds number for different concentrations. The results clearly show the enhancement of heat transfer coefficient for both nanofluids with nanoparticle concentrations as well as Reynolds number which is due to superior thermal conductivity of nanofluid compared to water and also Brownian motion of nanoparticles, particle migration and reduction of boundary layer thickness as reported in previous literatures [49–51]. In addition, at high flow rates, the dispersion effects and chaotic movement of the nanoparticles intensify the mixing fluctuations, change the temperature profile to a flatter profile similar to turbulent flow and cause increase in heat transfer coefficient.

Moreover, the variation of Nusselt number of nanofluid flows through HCT-III as a function of Reynolds number at different concentrations is shown in Fig. 7. It can be understood from this figure that the Nusselt number of each nanofluid is greater than distilled water and is intensified by increasing Reynolds number as well as the volume fraction of nanoparticles. Diffusion and relative movement of nanoparticles near tube wall lead to rapid heat transfer from wall to nanofluid. It means that increasing the concentration of nanoparticles amplifies the mechanisms responsible for enhanced heat transfer. Therefore, in general, nanofluids with higher volume concentrations have generally higher convective heat transfer coefficients. It is worth mentioning that when particle concentration increases, the viscosity of nanofluids intensifies, so the pressure drop through HCTs increases too [52]. In another word, when volume concentration of tested nanofluids is more than 1.0%, dramatic pressure losses will occur through the tubes. So application of nanofluids in high concentration is not recommended and all experiments have been done for nanofluids with volume concentration of less than 1.0%. Another evidence to confirm these results is presented in Fig. 8 which illustrates the ratio of heat transfer coefficient of nanofluids to that of distilled water inside HCT-II as a function of Reynolds number. Al2O3/water nanofluid causes more enhancement of water heat transfer compared to TiO2/water. The maximum enhancement ratio is observed for 1.0% Al2O3/water and TiO2/water nanofluid flows at the lowest Reynolds number which is equal to 45% and 27%, respectively. With increasing nanoparticle contents and Reynolds number, physical properties of nanofluids (Prandtl number) change too. Since in this figure the ratio of heat transfer is depicted only versus Reynolds number, some nonlinearity and non-uniform trends are observed over experimental data which is due to lack of considering Prandtl number in this figure. In the last section of this article the effect of Prandtl number on heat transfer rate will be considered. For low Reynolds number the heat transfer coefficient is mainly proportional to the fluid thermal conductivity. The other main effects 3500

7

HCT-I

HCT-I

+19% HCT-III

5

h ( Wm-2K-1 )

Theoritical ΔP (kpa)

3000

HCT-II

6

-27%

4 3

2500 Distilled water 0.25% TiO2 0.25% Al2O3 0.5% TiO2 0.5% Al2O3 0.75% TiO2 0.75% Al2O3 1.0% TiO2 1.0% Al2O3

2000 1500

2 1000

1 0 0

1

2

3

4

5

6

7

Experimental ΔP (kpa) Fig. 5. The comparison between theoretical and experimental pressure drops of distilled water flow inside helical coiled tubes.

500 0

500

1000

1500

2000

2500

3000

3500

4000

4500

Re Fig. 6. Heat transfer coefficient versus Reynolds number and volume concentration for Al2O3/water and TiO2/water nanofluid flows inside HCT-I.

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M. Kahani et al. / Powder Technology 246 (2013) 82–92

55

HCT-III 50 45

Nu

40 35 Distillated water 0.25% TiO2 0.25% Al2O3 0.5% TiO2 0.5% Al2O3 0.75% TiO2 0.75% Al2O3 1.0% TiO2 1.0% Al2O3

30 25 20 15 10 0

500

1000 1500 2000 2500 3000 3500 4000 4500

Re Fig. 7. Nusselt number versus Reynolds number and volume concentration for Al2O3/ water and TiO2/water nanofluid flows inside HCT-III.

of the nanopowders inside the fluid ‘considering the Brownian motion and fluctuation of the nanoparticles’ change the flow structure of the fluid to a semi turbulent regime with a flattened transverse temperature gradient in the bulk of the fluid [53], which leads to enhance the nanofluid convective heat transfer. But at a higher Reynolds or Helical numbers this mechanism is not dominant. In other words, at higher flow rate, the heat transfer coefficient has no considerable dependency to the thermal conductivity of the fluid. Therefore, the effect of thermal conductivity becomes less pronounced. Since, in the presence of nanopowders, the aforementioned heat transfer enhancement ratio (Fig. 8) decreases for a higher Reynolds number [54]. In order to investigate the effects of geometrical parameters (curvature ratio and pitch spacing) of helical coils on heat transfer rate, Nusselt numbers of both nanofluids at 0.25–1.0 vol.% concentration versus Reynolds numbers through helical coiled tubes are shown in Fig. 9(a–d). As it can be seen from these figures, the highest Nusselt numbers are observed for flow inside HCT-II which has the biggest pitch spacing and smallest curvature ratio among other helical coiled tubes. It means that the heat transfer rate marginally increases as the curvature ratio decreases and pitch spacing increases. For instance, at 0.25 vol.% fraction of Al2O3/water nanofluid while Reynolds number varies between 500 and 4000 the Nusselt number increases from 13.9 to 46.9 for HCT-III and from 14.9 to 47.3 for HCT-II and from 12.5 to 36.4 for HCT-I. The smaller curvature ratio leads to the more powerful centrifugal forces which in turn causes more severe secondary flow motions. 1.5

0.25% Al2O3 0.25% TiO2 0.5% Al2O3 0.5% TiO2 0.75% Al2O3 0.75% TiO2 1.0% Al2O3 1.0% TiO2

HCT-II

1.45

h (nf) / h (water)

1.4 1.35 1.3 1.25 1.2

Since the experimental data for all tested nanofluid flows through HCT-II and HCT-III (same curvature ratio) are closer together in comparison of HCT-I and HCT-III (same pitch spacing), it can be concluded that the pitch spacing effect on the heat transfer rate is to some extent weaker than the curvature ratio effect. For example, for 0.5% TiO2/ water nanofluid the enhancement of Nusselt number between HCT-II and HCT-III is 3.4% while this increment is 42.0% between HCT-III and HCT-I at Re = 1400. Also, the maximum achievable Nusselt numbers are 52.5 and 49.8 for 1.0% Al2O3/water and 1.0% TiO2/water nanofluid, respectively at highest Reynolds number. Considering Figs. 6, 7, 8 and 9(a–d), it is clear that Al2O3 nanoparticles with 35 nm particle size present better enhancement of heat transfer rate in comparison with TiO2 (50 nm)/water nanofluids at the same concentration and Reynolds number. For example, as shown in Fig. 7 at 0.75 vol.% fraction of nanofluid flow through HCT-III while Reynolds number varies from 530 to 3410 and the Nusselt number increases from 15.6 to 49.5 for Al2O3/water nanofluid and from 13.9 to 47.4 for TiO2/water nanofluid when Reynolds number changes from 530 to 3500. Two major reasons to support this kind of trend are hidden in the thermal conductivity and average size of nanoparticles. Since Al2O3 nanoparticles have higher thermal conductivity compared to TiO2 nanoparticles, low enhancement of heat transfer rate for TiO2/water nanofluid is obtained in comparison with Al2O3/ water nanofluids. In addition, the smaller size of Al2O3 nanoparticles can intensify the Brownian motion of particles which led to more enhancements on Nusselt number. In brief, the greater enhancement shown by Al2O3/water nanofluid compared to TiO2/water nanofluid is because of the combined effect of greater surface to volume ratio and thermal conductivity of Al2O3 nanoparticles compared to TiO2 particles. The same mechanism has been presented by Suresh et al. [55], Zeinali Heris et al. [56] and Nassan et al. [21] for CuO/water and Al2O3/Water nanofluid flow in a straight circular duct with helical screw tape, straight circular tube and square cross-section duct, respectively. 6.3. Pressure drop results Pressure drop along HCT-II versus Reynolds number for distilled water and both nanofluids is shown in Fig. 10. Both nanofluids indicate a higher pressure drop compared with distilled water. The larger size of TiO2 nanoparticles leads to more increments of pressure drop in comparison with Al2O3/water nanofluid. For instance, by adding 1.0 vol.% fraction of Al2O3 and TiO2 nanoparticles into water at Re = 2600, pressure drop in comparison to water can be increased up to 89.4% and 97.7%, respectively. Also, from Fig. 10 it is found that the pressure drop increases over particle volume concentration due to the rise of working fluid viscosity and density as well as Reynolds number. As mentioned in Eqs. (12)–(15), the larger the value of viscosity, the more growth in axial pressure drop. In the interim, Brownian motion, dispersion, and fluctuation of nanoparticles especially near the wall of tubes lead to amplify the momentum exchange rates between the particles. This momentum exchange can considerably increase axial pressure drop. The results compare well with other investigations [16,57]. The maximum pressure drop is 17.43 and 17.25 kPa for TiO2/water and Al2O3/water, respectively at the highest Reynolds number and volume concentration. 6.4. Thermal performance evaluation

1.15 1.1 1.05 0

500

1000

1500

2000

2500

3000

3500

4000

4500

The thermal performance factor (η) can be defined as the ratio of the heat transfer coefficient (or Nusselt number) ratio to the friction factor (or pressure drop) ratio at the same pumping power:

Re Fig. 8. The ratio of nanofluid heat transfer coefficient to that of distilled water versus Reynolds number inside HCT-II.

η¼


h =hSt;f n f  =f St;f

ð19Þ

M. Kahani et al. / Powder Technology 246 (2013) 82–92

50

50

(a) 0.25%

(b) 0.5%

45

45

40

40

35

35

30

Nu

Nu

89

Al2O3, HCT-I TiO2, HCT-I

25

30

Al2O3, HCT-I TiO2, HCT-I

25

Al2O3, HCT-II

20

TiO2, HCT-II

15

Al2O3, HCT-III

Al2O3, HCT-II

20

10

10 500

1000

1500

2000

2500

3000

3500

4000

Al2O3, HCT-III TiO2, HCT-III

TiO2, HCT-III

0

TiO2, HCT-II

15

0

4500

500

1000

1500

Re

2500

3000

3500

4000

4500

Re 55

55

(c) 0.75%

50

(d) 1.0%

50

45

45

40

40

35

Nu

Nu

2000

Al2O3, HCT-I

30

TiO2, HCT-I

35 Al2O3, HCT-I

30

TiO2, HCT-I

25

Al2O3, HCT-II

25

Al2O3, HCT-II

20

TiO2, HCT-II

20

TiO2, HCT-II

Al2O3, HCT-III

15

Al2O3, HCT-III

15

TiO2, HCT-III

TiO2, HCT-III

10

10 0

500

1000

1500

2000

2500

3000

3500

4000

4500

0

500

1000

1500

Re

2000

2500

3000

3500

4000

4500

Re

Fig. 9. Nusselt number results versus Reynolds number of helical coils at (a) 0.25, (b) 0.5, (c) 0.75, and (d) 1.0 vol.% concentrations of both nanofluids.

where n is the value index. h⁎ and f⁎ represent the Nusselt number and pressure drop of the flow resulted by applying enhanced heat transfer techniques, respectively. The larger the values of the thermal performance factor, the more suitable the enhancement heat transfer technique. The value index (n) has experienced different values in previous literatures. Usui et al. [58] and Suresh et al. [55] have considered n = 0.1666 for laminar flow while Hashemi et al. [31] have taken n = 1.0. Wongcharee et al. [59] have used thermal performance factor with n = 1/3 for turbulent flow and the same value of n has been used by Abbasian Arani and Amani [60] in their experiments. 18 Distiiled water

16

0.25% TiO2 0.25% Al2O3

14

0.5% TiO2

ΔP (kPa)

12

0.5% Al2O3 0.75% TiO2

10

0.75% Al2O3 1.0% TiO2

8

1.0% Al2O3

6 4 2

HCT-II

0 0

500

1000

1500

2000

2500

3000

3500

4000

4500

Re Fig. 10. Experimental pressure drop of nanofluid flows through HCT-II versus Reynolds number.

In order to investigate the influence of both coiled tubes and nanofluid techniques on thermal performance of the equipments, the following equation was used in this study: η¼


NuC;nf =NuSt;f 0:1666 ΔpC;nf =ΔpSt;f

ð20Þ

where NuC,nf and NuSt,f are the Nusselt number for nanofluid flow in helical tubes and for distilled water flow in straight tube, respectively. Besides, ΔpC,nf and ΔpSt,f represent the pressure drop for nanofluid flows in helical coils and for distilled water flow in straight tube, respectively. The variation of thermal performance factor with Reynolds number for 1.0 vol.% concentration of Al2O3/water and TiO2/water nanofluids through helical coiled tubes is illustrated in Fig. 11. The thermal performance factor for all helical coils is greater than unity. It means that using both of the heat transfer enhancement techniques studied in this investigation is a good choice in practical application. Also, HCT-II shows the best thermal performance among other helical tubes. For example, at the lowest Reynolds number the thermal performance factor for Al2O3/water nanofluids through HCT-II is 11.7% and 25.3% greater than the flows inside HCT-III and HCT-I, respectively. As mentioned before, small curvature ratio and large pitch spacing of HCT-II intensify centrifugal forces and secondary flow which lead to more enhancement of thermal performance. In addition, Al2O3/water nanofluid through helical coils shows better performance than TiO2/water nanofluids. For instance, thermal performance factor of Al2O3/water nanofluid flow in HCT-I changes

90

M. Kahani et al. / Powder Technology 246 (2013) 82–92

4

Using the present empirical data, the following correlations are derived to predict the Nusselt number of nanofluid flows inside the helical coils using least square method of regression analysis. For TiO2/water nanofluid:

1.0% Vol. Nanofluid

3.5

3

R2adj: ¼ 95:0%:

ð21Þ

η

NuC ¼ 0:5He0:522 Pr 0:613 φ0:0815 Al2O3, HCT-III TiO2 , HCT-III Al2O3, HCT-II TiO2 , HCT-II Al2O3, HCT-I TiO2 , HCT-I

2

For Al2O3/water nanofluid: NuC ¼ 0:7068He0:514 Pr 0:563 φ0:112

1.5 0

500

1000

1500

2000

2500

3000

3500

4000

Re Fig. 11. Variation of thermal performance factor with Reynolds number for 1.0 vol.% concentration of nanofluid flows inside helical tubes.

between 2.11 and 3.09 while this variation for TiO2/water nanofluids is between 1.71 and 2.88. Besides, the maximum thermal performance factor is 3.82 and obtained for 1.0 vol.% concentration of Al2O3/water nanofluid through HCT-II at Re = 1865.

6.5. Estimation of Nusselt number and pressure drop Fig. 12 depicts the ratio of the experimental Nusselt number to the results obtained from Manlapaz–Churchill equation versus Reynolds number for nanofluid flows through HCT-I. From this figure it can be noticed that Manlapaz–Churchill equation fails to predict the Nusselt number of Al2O3/water and TiO2/water nanofluids. Other mechanisms besides thermal conductivity increase such as Brownian motion and particle migration can be responsible for heat transfer enhancement too and these two main factors are not considered in the common theoretical equations. In order to incorporate the effect of pitch in the empirical correlation for the Nusselt number and pressure drop through helical coils, Helical number is employed instead of the Reynolds number. When Reynolds number varies from 500 to 4500, the Helical number changes between 157 and 1420 for HCT-II and III and also varies from 111 to 1005 for HCT-I.

R2adj: ¼ 96:4%

ð22Þ

the applicable ranges are (i) 0.25% ≤ φ ≤ 1.0%, (ii) 5.89 ≤ Pr ≤ 8.95 and (iii) 115.3 ≤ He ≤ 1311.4. As shown in Fig. 13(a,b), the deviation between the predicted Nusselt number and experimental Nusselt number is found to be in the range of between + 15% to − 15% for TiO2/water and + 18% to − 25% for Al2O3/water nanofluid. Besides, a correlation is developed by using least square method of regression analysis to predict pressure drop through helical coiled tubes as follows: ΔpC ¼ 5:584He1:36 φ0:446 dp 0:163

2

R adj: ¼ 95:8%

ð23Þ

this correlation is valid for metal oxide (spherical shape nanoparticles)/ water nanofluid flows in helical coils with volume concentrations less than 1.0% in the laminar flow regime with 115.3 ≤ He ≤ 1311.4 and 35 ≤ dp ≤ 50 nm. 60

(a) +15%

50

Predicted Nu

2.5

40

-15%

30 20 10 0 0

10

20

30

40

50

60

Experimental Nu 1.4 60

HCT-I

(b)

1.3

+18%

Predicted Nu

Nu (exp) / Nu (th)

50 1.2 1.1 1 0.9 0.25% TiO2 0.5% TiO2 0.75% TiO2 1.0% TiO2

0.8

0.25% Al2O3 0.5% Al2O3 0.75% Al2O3 1.0% Al2O3

0.7 0

1000

2000

3000

4000

Re Fig. 12. The ratio of experimental Nusselt number to Manlapaz–Churchill equation for Al2O3/water and TiO2/water nanofluids versus Reynolds number through HCT-I.

40

-25%

30 20 10 0 0

10

20

30

40

50

60

Experimental Nu Fig. 13. Deviation between the predicted Nusselt number and experimental Nusselt number for (a) TiO2/water and (b) Al2O3/water nanofluids.

M. Kahani et al. / Powder Technology 246 (2013) 82–92

7. Conclusion The comparative study on thermal performance and pressure drop for Al2O3 (35 nm)/water and TiO2 (50 nm)/water nanofluid flows through helical coils was done. The experiments were carried out for the laminar flow regime under constant heat flux boundary condition with different concentrations of nanofluids, which vary from 0.25% to 1.0%. The conclusions based on the experimental results are as follows: 1) For nanofluids, heat transfer rate and also pressure drop enhance with increasing nanoparticle concentrations as well as Reynolds number. Although, because of the larger thermal conductivity and smaller size of nanoparticles, Al2O3/water nanofluids show more enhancement compared with TiO2/water. 2) All the helical coils have thermal performance factor greater than unity. It means that using nanofluids inside helical coils is a suitable choice in practical application. 3) The maximum thermal performance factor is found to be 3.82 for 1.0 vol.% concentration of Al2O3/water nanofluid through HCT-II at Re = 1865. 4) According to the empirical data, HCT-II which has the smallest curvature ratio and the largest pitch spacing shows the best performance among other helical coils. 5) The pitch spacing effect of helical coils is to some extent weaker than the curvature ratio effect on the heat transfer rate. 6) Three experimental correlations are proposed to bring out the effects of Helical number, Prandtl number, volume concentration and particle size on Nusselt number and pressure drops of both nanofluids. Acknowledgment The authors wish to thank the Iran Nanotechnology Initiative Council (INIC) and the Ferdowsi University of Mashhad for financial support of this research. References [1] Y. Li, J. Zhou, S. Tung, E. Schneider, Sh. Xi, A review on development of nanofluid preparation and characterization, Powder Technology 196 (2009) 89. [2] Y. Yang, A. Oztekin, S. Neti, S. Mohapatra, Characterization and convective heat transfer with nanofluids, ASME/JSME 8th Thermal Engineering Joint Conference (2011) Honolulu, USA, 2011. [3] S.U.S. Choi, D.A. Singer, H.P. Wang, Development and application of non-Newtonian flows, vol. FED 231, ASME, New York, 1995, p. 99. [4] M.H. Chang, H.S. Liu, C.Y. Tai, Preparation of copper oxide nanoparticles and its application in nanofluid, Powder Technology 207 (2011) 378. [5] J. Koo, C. Kleinstreuer, A new thermal conductivity model for nanofluids, Journal of Nanoparticle Research 6 (2004) 577. [6] P. Sharmaa, I. Baeka, T. Cho, S. Park, K.B. Leed, Enhancement of thermal conductivity of ethylene glycol based silver nanofluids, Powder Technology 208 (2011) 7. [7] S.S. Mallick, A. Mishra, L. Kundan, An investigation into modeling thermal conductivity for alumina–water nanofluids, Powder Technology 233 (2013) 234. [8] S.M.S. Murshed, K.C. Leong, C. Yang, Enhanced thermal conductivity of TiO2–water based nanofluids, International Journal of Thermal Sciences 44 (2005) 367–373. [9] L. Yang, K. Du, Y.H. Ding, B. Cheng, Y.J. Li, Viscosity-prediction models of ammonia water nanofluids based on various dispersion types, Powder Technology 215 (2012) 210. [10] M.P. Beck, Y. Yuan, P. Warrier, A.S. Teja, The thermal conductivity of alumina nanofluids in water, ethylene glycol, and ethylene glycol + water mixtures, Journal of Nanoparticle Research 12 (2010) 1469. [11] S. Chakraborty, S.K. Saha, J.C. Pandey, S. Das, Experimental characterization of concentration of nanofluid by ultrasonic technique, Powder Technology 210 (2011) 304. [12] C. Kleinstreuer, Y. Feng, Experimental and theoretical studies of nanofluid thermal conductivity enhancement: a review, Nanoscale Research Letters 6 (2011) 229. [13] W. Yu, H. Xie, L. Chen, Y. Li, Investigation on the thermal transport properties of ethylene glycol-based nanofluids containing copper nanoparticles, Powder Technology 197 (2010) 218. [14] E. Tamjida, B.H. Guentherb, Rheology and colloidal structure of silver nanoparticles dispersed in diethylene glycol, Powder Technology 197 (2010) 49. [15] Y. Yang, A. Oztekin, S. Neti, S. Mohapatra, Particle agglomeration and properties of nanofluids, Journal of Nanoparticle Research 1 (4) (2012) 852.

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