Scale formation and subcooled flow boiling heat transfer of CuO–water nanofluid inside the vertical annulus

Experimental Thermal and Fluid Science 52 (2014) 205–214

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Scale formation and subcooled flow boiling heat transfer of CuO–water nanofluid inside the vertical annulus M.M. Sarafraz ⇑, F. Hormozi 1 Faculty of Chemical, Petroleum and Gas Engineering, Semnan University, Semnan, Iran

a r t i c l e

i n f o

Article history: Received 13 July 2013 Received in revised form 10 September 2013 Accepted 14 September 2013 Available online 20 September 2013 Keywords: Forced convective Subcooled flow boiling Fouling rate CuO nanoparticle Stabilization of nanofluid

a b s t r a c t The forced convective and subcooled flow-boiling heat transfer of CuO/water nanofluid as well as fouling rate of nanofluid are experimentally quantified for different dilute concentrations of CuO nanoparticles in water over a range of mass fluxes (353 kg/m2 s < G < 1059 kg/m2 s). Stabilization of nanofluid was also carried out using pH control method and examined using time-spend experiment. In the best case of stabilization (about 216 h), experimental results demonstrate that two discrete regions of heat transfer are seen namely force convective and nucleate boiling. Results also show that when concentration of nanofluid increases, heat transfer coefficient in both regions significantly decreases in comparison to pure water. Beside, results reveal that increase of heat and mass flux significantly increases the heat transfer coefficient in both heat transfer mechanisms. In the range of these experiments; nanoparticles have an insignificant effect on the flow pressure drop with the CuO/water nanofluid. Beside, Influence of some operating conditions on flow boiling heat transfer coefficient and fouling rate is discussed. Ó 2013 Elsevier Inc. All rights reserved.

1. Introduction Boiling and two phase flow phenomena are used in a variety of industrial processes and applications, such as refrigeration, airconditioning and heat pumping systems, energy conversion system, heat exchange systems, chemical thermal processes, cooling of high-power electronics components, cooling of nuclear reactors, micro-fabricated fluidic systems, thermal processes of aerospace station and bioengineering reactors [1]. In the nuclear power applications, boiling heat transfer plays a key role both in the efficient energy transportation during the normal operation and in the successful decay heat removal for the transient accident condition, due to the large latent heat of water and the bubble-driven convection or turbulence. Specifically, to prevent the core melt down and to mitigate the leakage of radioactivity to the outside of reactor vessel, successful removal of decay heat is necessary [2]. Solid particles of the nominal size 1–100 nm are called nanoparticles, and low-concentration dispersions of such particles in a base fluid are called nanofluids. Nanofluids are known to apply a significant increase in thermal conductivity over that of the base fluid [3–7]. Early studies of application of nanofluids in flow and pool boiling have mainly focused on critical heat flux and surface characteris-

⇑ Corresponding author. Tel.: +98 9166317313; fax: +98 6324231683. E-mail addresses: [email protected] (M.M. Sarafraz), [email protected] (F. Hormozi). 1 Tel.: +98 9123930495. 0894-1777/$ - see front matter Ó 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.expthermflusci.2013.09.012

tics of a heating section as well as thermal conductivity enhancement and the parameters that govern this behavior [8–17]. 2. Literature review Many researchers have conducted experimental studies on the effect of refrigerant based nanofluids on pool and flow boiling heat transfer coefficient and pressure drop due to their importance in industrial cooling cycles and refrigerant systems and some other researchers investigated on the organic based nanofluid (e.g. ethylene, tri-ethylene–glycols, refrigerants, etc.), oils and lubricants, bio-fluids, polymer solutions and other common liquids [18–26]. In fact, employing the nanofluids is a new research frontier related to nanotechnology and has found a wide range of potential applications particularly in cooling systems and two phase heat transfer applications. Following literature review represents the recent works conducted to forced convective and flow boiling heat transfer of nanofluids. An experimental study on the forced convective heat transfer and flow characteristics of TiO2/water nanofluids under turbulent flow conditions has been reported by Duangthongsuk and Wongwises [27]. A horizontal double-tube counter flow heat exchanger is used in their study. They observed a slightly higher (6–11%) heat transfer coefficient for nanofluid compared to pure water. The heat transfer coefficient increases with increasing mass flow rate of the hot water as well as nanofluid. Recently, Sarafraz et al. conducted some experimental investigations on pool boiling heat transfer of nanofluids around the horizontal cylinder [28,29]. Also, among very few studies on flow boiling of nanofluids,

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Nomenclature A b Bo Cp db dh f F h DHv k lth L DL Nu Pe ph Pr Pr P q Re Ra Rf s S T x x_

area, m2 distance, m boiling number heat capacity, J kg1 °C1 bubble departing diameter, m hydraulic diameter, m fanning friction number enhancement factor enthalpy, J kg1 heat of vaporization, J kg1 thermal conductivity, W m1 °C1 heated length, m heater length, m characteristic length in Eq. (15), m Nusselt number Peclet number phase change number reduced pressure Prandtl number pressure, Pa heat, W Reynolds number roughness, m fouling resistance, m2 K/kW distance between thermometer location and heat transfer surface, m suppression factor temperature, K liquid mass or mole fraction vapor mass fraction

Kim et al. [9] represented about 50% enhancement in flow boiling CHF for Al2O3/water nanofluids flowing through a vertical stainless steel tube. Very recently, Henderson et al. [20] studied refrigerantbased SiO2 and CuO-nanofluids in flow boiling experiments in horizontal copper tube. They found that while the boiling heat transfer coefficient (BHTC) of SiO2/R-134a nanofluid decreases up to 55% in comparison to pure R-134a, the BHTC increases more than 100% for CuO-laden nanofluid over base fluid, i.e. mixture of R-134a and poly-olester oil (PO). Despite the recent activity, our current understanding of nanofluids is limited with respect to most two-phase flow conditions, especially those used in vapor compression systems. Previous experiments for single- and two-phase convective heat transfer predominantly use aqueous suspensions of nanoparticles. While water is widely used in heat transfer applications and generally produces stable nanoparticle suspensions, the feasibility of creating refrigerant-based nanofluids as well as characterizing their thermal effects must be explored further if the potential heat transfer enhancements are to be realized in air-conditioning and refrigeration applications [30]. In previous studies and recent studies, most of investigators pay more attention to the CHF and surface characteristics of heating sections. As the evidence, Kim et al. [31] conducted Experiments in order to study the critical heat flux enhancement in forced convective flow boiling of nanofluid on a short heated surface and represent the significant enhancement of critical heat flux, when nanofluid is used as a coolant and ignored the possible influence of nanoparticles on flow boiling heat transfer coefficient and bubble dynamics. They also suggested that suggested that the flow boiling CHF enhancement in nanofluids is mostly caused by the nanoparticles deposition of the heater surface during vigorous boiling of nanofluids and the subsequent wettability enhancements. Kim and Ahn and Kim [32] studied the

Xtt y

Martinelli parameter vapor mass or mole fraction

Subscripts–superscripts b bulk bs base fluid nf nanofluid c critical fb flow boiling in inlet out outlet l liquid m mixture n number of components nb nucleate boiling r reduced Sat saturated th thermometers v vapor w wall Greek symbols a heat transfer coefficient, W m2 K1 q density, kg m3 l viscosity, kg m1 s1 j Boltzmann constant = 1.381  1023, J K1 / volume fraction u particle sphericity

boiling phenomena of Al2O3 nanofluids near the critical heat flux and showed that particle deposition on a heater leads to creation of thicker macro-layer around the heating section which leads the CHF to be enhanced due to the wettability enhancement. In this regards, visualization study on the effects of nanoparticle deposition on a surface was studied by Kim et al. [33]. As can be seen from the above-mentioned literatures, Less attention has been paid to the forced convective and flow boiling heat transfer coefficient of nanofluid due to the deterioration of heat transfer coefficient which is undesirable. The outstanding purpose of this study is to experimentally measure the forced and nucleate flow boiling heat transfer coefficient of CuO/water nanofluid to set collection of experimental data and investigate the influence of different operating conditions such as heat flux, flow rate and dilute volumetric concentrations of test nanofluid on the single phase and two-phase flow-boiling of CuO/water nanofluid. Fouling rate and scale formation is also briefly discussed. In addition to, a rough comparison between experimental data and results obtained by Chen well-known correlation is carried out. 3. Experiments 3.1. Preparation of nanofluids Semnan University has precious heat transfer lab which provides technical facilities to disperse the CuO nanoparticles (50 nm, PlasmaChem GmbH, Germany) uniformly into the base fluid for making a stable nanofluid. In the present work, deionized water is considered as base fluid. The two step method is employed for preparation of nanofluid. Briefly, these processes include:

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I. Weight the mass of CuO with digital electronic balance (A&D EK Series Portable Balances, EK-1200i). II. Initially, the weighted CuO nanoparticle was added into the weighted deionized water while it was agitated in a flask. The magnetic motorized stirrer (Hanna instruments Co.) was employed to agitate the nanoparticle inside the base fluid. III. UP400S ultrasonic Hielscher GmbH (400 W/24 kHz) is used to disperse the nanoparticles into the water uniformly. In the present work, nanofluids with volumetric concentrations of 0.5%, 1% and 1.5% is prepared using the 50 nm (claimed by manufacturer) CuO as nanoparticle and deionized water as based fluid. As can be seen in Fig. 1a, XRD pattern depicts the single-phase CuO with a monoclinic structure which implies on this fact that there is no impurity other than CuO nanoparticles and no significant peaks of impurities are found in XRD pattern. In fact, X-ray diffraction is one of the most important characterization tools, which is widely used in solid state chemistry and powder/particle sciences. This technology is an easy tool to determine the size and the shape of the particles and Phase Identification Quantitative analysis. XRD Diffraction pattern gives information on symmetry size and shape of the particle and purity of particles from Peak Positions. These peaks can be compared to those of obtained for particular particle or powder and shape or impurity as well as nano-size particles can be detected. It also gives information on deviations from a perfect particle; the peaks are broad due to the nano-size Effect. It must be noted that sometimes, Commercial CuO particles involves CuO2 and other impurities and a simple XRD such as Fig. 1a can help the researchers to verify the quality of particles used in their research and ensure them about the absence of any other undesired compounds. The average size of the nanoparticles measured by using Scherrer’s formula [35] was approximately equal to 45–50 nm and the value of 2h and B was determined by the XRD spectra. Fig. 1b also demonstrates the particle size distribution of nanofluid. As can be seen, the dominant size of particles is 50 nm. Fig. 1c depicts the SEM image of CuO nanoparticles. 3.2. Stabilization of nanofluid Preparation of homogeneous suspension remains a technical challenge since the nanoparticles always form aggregates due to very strong van der Waals interactions. To get stable nanofluids, physical or chemical treatment have been conducted such as an addition of surfactant, surface modification of the suspended particles or applying strong force on the clusters of the suspended particles [36,37]. To avoid complications of thermo-physical

Fig. 1b. Results of nanoparticle count.

Fig. 1c. SEM image of CuO nanoparticles [34].

properties of nanofluid due to the presence of dispersant/surfactant, in this study the nanofluids were stabilized considering the variation of pH. Experiments showed us that at pH = 7.7 the best stable nanofluid (for about 216 h) is achievable. Fig. 2 shows the results of sedimentation-time experiment for CuO water based nanofluids. Noticeably, to control the pH of nanofluid, NaOH aqueous solution and HCl was used and also to experimentally measure the pH, the pen type pH meter AZ-8685A (AZ instruments Co) was used. 3.3. Experimental apparatus

Fig. 1a. XRD pattern of CuO nanoparticles.

Schematic of the main components of the close loop experimental facility constructed in the present study is shown in Fig. 3. The working fluid enters the loop from a main tank through the isolated pipes and is continuously circulated by a centrifugal pump (DAB Co.). Duo to the importance of flow rate of fluid in flow boiling heat transfer, a Netflix ultrasonic flow meter is also installed in trajectory line of fluid to measure the flow rate with the least possible uncertainty. Also, a rotameter is installed at the outlet line of condenser to validate the flow rate values measured by ultrasonic device. The fluid temperature was measured by two PT-100 thermometers installed in two thermo-well located just before and

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Fig. 2. Stability of CuO/water nanofluid during 216 h after dispersion.

Fig. 3. A scheme of test loop.

after the annular section. The complete cylinder was made from stainless steel 316a. Thermometer voltages, current and voltage drop from the test heater were all measured and processed with a data acquisition system in conjunction with a PID temperature controller. The test section shown in Fig. 3 consists of an electrically heated cylindrical DC bolt heater (manufactured by Cetal Co.) with a stainless steel surface, which is mounted concentrically within the surrounding pipe. The dimensions of the test section are: diameter of heating rod, 22 mm; annular gap diameter (hydraulic diameter) 30 mm; the length of the Pyrex tube is 400 mm; the length of stainless steel rod, 300 mm; the length of heated section, 140 mm which means that just the first 140 mm of stainless steel is heated uniformly and radially by the heater. The axial heat transfer thorough the rod can be ignored according to the insulation of the both ends of the heater. The heat flux and wall temperature can be as high as 190,000 W m2 and 163 °C, respectively. The local wall temperatures have been measured with four stainless steel sheathed K-type thermocouples which have been installed close to the heat transfer surface. The temperature drop between the thermocouples location and the heat transfer surface can be calculated from:

T w ¼ T th  q_

s kw

ð1Þ

The ratio between the distance of the thermometers from the surface and the thermal conductivity of the tube material (s/kw) was determined for each K-type thermocouple by calibration using Wilson plot technique [38]. The average temperature difference for each test section was the arithmetic average of the four thermometers readings around the rod circumference. The average of 10 voltage readings was used to determine the difference between the wall and bulk temperature for each thermometer. All the Ktype thermocouples were thoroughly calibrated using a constant temperature water bath, and their accuracy has been estimated to ±0.3 K. The local heat transfer coefficient a is then calculated from:

a¼

q_ ðT w  T b Þav e:

ð2Þ

To minimize the thermal contact resistance, high quality silicone paste was injected into the thermocouple wells. To avoid possible heat loss, main tank circumferences were heavily insulated using industrial glass wool. To control the fluctuations due to the alternative current, a regular DC power supply was also employed to supply the needed voltage to central heater. Likewise, to visualize the flow and boiling phenomenon and record the proper images, annulus was made of the Pyrex glass.

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209

As shown in Fig. 3, the temperature shown by the thermocouple (Tth) is not exactly equal but it is slightly higher than the actual temperature of the heat transfer surface (Tw). This temperature difference is due to the conduction resistance of the heater material which is mounted between these two points. These temperatures can be related according to the energy balance under steady state condition:

Since the bulk temperature is constant in each experiment, Reynolds number is proportional to the fluid velocity. Considering this point and unifying all the constants as ‘‘b’’, the following equation will be obtained:

k q ¼ UðT th  T b Þ ¼ aðT w  T b Þ ¼ ðT th  T w Þ s

Eq. (8) shows that the plot of 1/U versus 1/V0.75 for each thermocouple gives the values of s/k as the intercept of the line. Fig. 4a–d shows the calibration plot of the different thermocouples used in the test heater. This data were taken under forced convective heat transfer to water at constant heat flux 8 kW/m2. As demonstrated in Fig. 4, the values of s/k for the thermocouples #1–4 are respectively equal to.2.97  104, 2.96  104, 2.85  104, 3.09  104 m2 K/W. Repeating the experiments at other heat fluxes gives the value of 3  104 m2 K/W as an average value of s/k for all the thermocouples. This value was then used for the calibration of the surface thermocouples using Eq. (4).

ð3Þ

This relation can be simplified as follows:

1 1 s ¼ þ U a k

ð4Þ

If a can be calculated using some characteristics of the system like velocity, estimation would be obtained for s/k using Eq. (4). For this purpose, the below relation is used:

a / f  NRe

ð5Þ

For the plain tubes, friction factor is related to Reynolds number according to Blasius relation as follows:

f /

1 N0:25 Re

ð8Þ

3.4. Uncertainty analysis

ð6Þ

Combination of Eqs. (5) and (6) gives the following relation for heat transfer coefficient:

a / N0:75 Re

1 b s ¼ þ U V 0:75 k

ð7Þ

The uncertainties of the experimental results are analyzed by the procedures proposed by Kline and McClintock [39]. The method is based on careful specifications of the uncertainties in the various primary experimental measurements. The heat transfer coefficient can be obtained using the following equation:

Fig. 4. Numerical values of s/k obtained by Wilson plot technique.

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a¼

qVC pnf ðT out  T in Þ

3.5. Thermo-physical properties of nanofluid

ð9Þ

ðT w  T b Þav :

In this work, it is assumed that CuO nanoparticles are well dispersed within the base fluid due to using the ultrasonic device and magnetic stirrer. The application of this assumption is that the particle concentration can be postulated uniform throughout the system and consequently the thermo-physical properties of the nanofluids at different temperatures and concentrations can be

As seen from Eq. (9), the uncertainty in the measurement of the heat transfer coefficient can be related to the errors in the measurements of volume flow rate, hydraulic diameter, and all the temperatures as follows.

a ¼ f fV; Ah ; ðT out  T in Þ; ðT w  T b Þg

ð10Þ

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  

2  

2  

2  

2 @a @a @a @a  dV þ  dA þ  dðT out  T in Þ þ  dðT w  T b Þ @a ¼ @V @A @ðT out  T in Þ @ðT w  T b Þ

a is flow boiling heat transfer coefficient, V is volume flow rate, A is cross section of annulus (computed using hydraulic diameter, Dh = 4A/P), Tin, Tout are temperature of fluid at inlet and outlet of annulus respectively and Tw is the wall temperature of heating section that can be estimated by arithmetic average of four thermocouples mounted as shown in Fig. 3. d, for each parameter represents its uncertainty. According to the above uncertainty analysis, the uncertainty in the measurement of the heat transfer coefficient is 16.23%. The detailed results from the present uncertainty analysis for the experiments conducted here are summarized in Tables 1 and 2.

estimated using some well-known theoretical formulas as usually used for two phase flow [34,36,40,41]. In this paper, the following correlations are used to calculate the density, viscosity and the specific heat of CuO/water nanofluid as follows in Table 3. 4. Results and discussion 4.1. Deionized water as a verification test To validate the experimental results, pure water is tested for verification test because, the physical properties of distilled water are well known with high accuracy and Forced convective and subcooled flow boiling heat transfer coefficient of distilled water had been investigated by several investigators over a wide range of heat fluxes and system pressures. Gnielinski and Chen [42,43] conducted many experiments to predict the heat transfer coefficient of distillated water. Todays, their well-known correlation are respectively used for convective and flow boiling zones in many investigations. Results of comparisons revealed that 7.83% and 12.6% deviations existed respectively which are acceptable results (Figs. 5a and 5b). Above figures demonstrate that the experimental results show the good agreement with that of obtained by well-known correlations. Therefore, experimental data which are represented as follows are truly reliable and valid.

Table 1 Uncertainty of parameters used in Kline–McClintock method.

a

Parameters

Uncertainty value

Unit

dV dA @ðT out  T in Þ @ðT w  T b Þ

0.5  103 2.5  109a 0.3 0.3

m3 m2 K K

In calculations, this value is considered equal to zero.

Table 2 Summary of the uncertainty analysis related to instruments and devices. Parameter

Uncertainty

Length, width and thickness (m) Temperature (K) Water flow rate (l min1) Voltage (V) Current (A) Cylinder side area (m2) Flow boiling heat transfer coefficient (W/m2 K)

±5  105 0:3 K ±1.5% of readings ±1% of readings ±0.02% of readings ±4  108 ±16.23%

ð11Þ

4.2. CuO/water nanofluid 4.2.1. Effect of operating parameters and nanoparticles on heat transfer coefficient In order to investigate the influence of operating parameters on the forced convective and flow boiling heat transfer coefficient, nanofluids are implemented by the addition of CuO nanoparticles

Table 3 Correlations for predicting the thermophysical properties of nanofluids. Physical properties

Correlation

Ref.

Density

qnf ¼ /qp þ ð1  /Þqbf

[36]

Heat capacity Viscosity

    q q C pnf ¼ ð1  /Þ qbf C pnf þ / q p C pp nf nf 1  lnf ¼ A T  B

[36] [36]

A ¼ 20; 587/2 þ 15; 857/ þ 1078:3, B ¼ 107:12/2 þ 53:548/ þ 2:8715 K þðn1ÞK /ðn1ÞðK K p Þ

Thermal conductivity

bf bf K nf ¼ p K p þðn1ÞK bf þ/ðK bf K p Þ qffiffiffiffiffiffiffiffi j T P ¼ q dp f ðT; /Þ

K bf þ 5  104 b/qbf C pbf  P

p

f ð/; TÞ ¼ 2:8217  102 / þ 3:917  103

  T T0

 3:0669  102 /  3:911  103

For CuO nanoparticle: b ¼ 9:881  ð100/Þ0:9446 n ¼ u3 ; u : Sphericity of nanoparticles [35]

[36]

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Fig. 5a. Comparison of results obtained by Gnielinski correlation and experimental data in forced convective region.

Fig. 5b. Comparison of results obtained by Chen model and experimental data in nucleate boiling region.

into the water at three different nanoparticle concentrations of 0.5, 1 and 1.5 vol.% different liquid mass fluxes of 353, 706 and 1059 kg/m2 s. At first, heat transfer coefficient is measured when different heat fluxes are applied. Obtained results showed that similar to previous works two distinguishable heat transfer regions namely: forced convective and nucleate boiling zone and deterioration of heat transfer coefficient was seen in both of heat transfer regions. According to Fig. 6, with increasing the heat flux at any volumetric concentration of nanofluid, heat transfer coefficient increases. However, for forced convective region, slight increase of heat transfer coefficient is seen while for nucleate boiling heat transfer zone, heat transfer coefficient dramatically increases. Also with increasing the volumetric concentration of nanofluid, heat transfer coefficient significantly decreases. Boiling of nanofluids results in nanoparticle deposition on the boiling surface [10,17]. Such deposition can affect the heat transfer coefficient in two ways: (i) change the number of micro-cavities on the surface and (ii) change the surface wettability. Although the main aim of this article is to represent the experimental data related to the forced convective and flow boiling heat transfer coefficient of dilute CuO nanofluid and the surface characteristic is out of goal of this paper but it is cleared that with increasing the rate of deposition of nanoparticles o the heating section, wettability of surface changes such that bubble interactions near the surface may increase and bubbles as well as nanoparticles cover the heating section which leads the heating

Fig. 6. Forced convective (at heat flux <50 kW/m2) and nucleate flow boiling heat transfer coefficient of CuO/water nanofluids at different volumetric concentration, heat transfer coefficient decreases with increasing the concentration of nanoparticles.

section to be isolated by bubbles and consequently, rate of heat transfer decreases. Fig. 7 represents the influence of mass flux on the flow boiling heat transfer coefficient of nanofluids. Fig. 8 illustrates the comparison between flow boiling heat transfer coefficient of deionized water (hbf) and water based CuO nanofluid (hnf). Deterioration of flow boiling heat transfer coefficient is clearly seen at all volumetric concentrations of nanofluid. Anyhow, in industrial heating systems, deterioration of heat transfer coefficient due to the economic aspects is normally undesirable but in some others such as cosmetic productions and hygiene manufacturers, products are so sensitive to the thermal shock and moderate heat fluxes which leads to changing the chemical properties, decomposition, oxidation, ignition and dimensional change (basically thermal expansion). Therefore, reduction of heat transfer coefficient would be desirable in these types of industries. According to Table 4, subcooling level does not have significant effect on the deterioration of heat transfer coefficient. 4.2.2. Comparison with Chen type model The obtained experimental heat transfer coefficient data for deionized water and CuO nanofluids were compared to those obtained by Chen correlation for flow boiling, which is celebrated for its applicability to a broad range of pure, mixtures and refrigerants. The Chen correlation in its basic form is expressed as [43,46]:

afb ¼ S  anb þ F  afc

ð12Þ

where afc is the convective heat transfer coefficient that may lonely be found for the liquid phase flowing. The parameter F is a multiplier that accounts for the apparent increase in velocity due to the presence of the vapor and is a function of the Martinelli parameter Xtt. anb is the pool boiling heat transfer coefficient at the local wall superheat and can be calculated using any pure liquid pool boiling predicting correlations; The suppression factor, S, accounts for the fact that anb is found from pool boiling correlations which over-predicts nucleate flow boiling. Coiller [30,44,45] fitted the following equations to the graphical relationships for F and S:

F¼

S¼

8 <1

 0:736 : 2:35 1 þ 0:213 X tt 1 1 þ 2:53  106 N1:17 Retp

if

1 X tt

6 0:1

if

1 X tt

P 0:1

ð13Þ

ð14Þ

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mass fraction has to be known. Schroder [47] proposed a calculation procedure for the local vapor mass fraction, which is applicable for subcooled and saturated boiling:

x_ ¼ Nph  Nphn exp



Nph 1 Nphn

 ð17Þ

where Nph is the phase change number and is defined as:

Nph ¼

hv  hl;sat hfg

ð18Þ

That: Nph is the value of the phase change number which is reached once the mean fluid temperature is high enough to permit the existence of vapor bubbles in the bulk of the liquid. Schroder [47] suggested calculating Nphn with a correlation valid for laminar and turbulent flow using the boiling number, Bo and the Peclet number, Pe: Fig. 7. Forced convective (at heat flux <50 kW/m2) and nucleate flow boiling heat transfer coefficient of CuO/water nanofluids at vol.% = 0.5 and different mass flux, heat transfer coefficient dramatically increases with increasing the mass flux of nanofluid.

NBo Nphn ¼ rffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi   455 N Pe

2

ð19Þ

2

þ 0:0065

l

NBo ¼

_ p;nf dh mC q_ N ¼ _  hfg Pe k m

ð20Þ

The length from the beginning of the test section to the point where the phase change number is zero is calculated from Eqs. (22) and (23)as:

DL ¼

Npho  dh 4NBo

Npho ¼

C p;nf ðT sat  T b Þ hfg

ð21Þ

ð22Þ

From Eq. (14) the phase change number at the beginning of the heated section can be calculated which gives the characteristic length DL from Eq. (21). From DL the length coordinate for the actual thermometer position can be calculated:

DLt ¼ DL þ xth

ð23Þ

With this length, the phase change number at the thermometer location is: Fig. 8. Experimental heat transfer coefficient of nanofluid in comparison with deionized water (hnf/hbf), Subcooling level = 363 K.

Table 4 Deterioration of flow boiling heat transfer coefficient at other subcooling levels and different vol.% at mass flux 1059 kg/m2 s, [(1-(hnf/hbf))  100]. Condition

Vol.% = 0.5

Vol.% = 1

Vol.% = 1.5

Subcooling = 323 K Subcooling = 343 K Subcooling = 353 K

5.21% 3.76% 4.77%

11.24% 11.71% 11.96%

24.35% 24.05% 23.89%

That:

!0:5    0:9 lnf 0:1 qbf 1  x_ X tt ¼ x_ qnf lv NRetp ¼

_  xÞd _ h mð1

lnf

F

1:25

ð15Þ

ð16Þ

Subsequently, Bennett and Chen [46] redeveloped the Chen correlation for binary mixtures, by using experimental data obtained for mixtures of water and glycol. To calculate the enhancement and suppression factors according to Eqs. (14)–(17), the local vapor

Nph ¼

4NBo  DLt dh

ð24Þ

To calculate the heat transfer coefficient according to Eq. (8), The Chen correlation requires both forced convective and nucleate boiling heat transfer coefficients. In this research, Gnielinski [42] correlation was used for forced convection and Gorenflo [48] correlation for nucleate pool boiling. As can be seen in Fig. 9, Chen type model represents the fair and acceptable agreement with experimental data with maximum deviation about 30%. Noticeably, in Chen model, thermo-physical properties are replaced with nanofluid physical properties. Likewise, it is important that Chen model has been proposed for pure, mixture, hydrocarbon mixtures in thermo-hydraulic conditions and subsequently, it is expected that this model is not able to predict the reasonable values for heat transfer coefficient of nanofluid. 4.2.3. Influence of operating parameters on the scale formation of CuO nanofluid In the present work, a large number of experiments were performed to measure the fouling resistance of CuO nanoparticles around the vertical stainless steel cylinder inside the annular duct. It is customary to present fouling data in terms of fouling resistance (Rf) which can be calculated on the basis of heat transfer [49]:

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Fig. 9. Comparison of experimental flow boiling heat transfer coefficient with Chen type model.

213

Fig. 11. Influence of mass flux on fouling resistance of CuO nanoparticles; representation of linear function of fouling resistance with time.

the heat transfer surface increases the surface roughness. This leads to an increase in the rate of heat transfer in comparison with clean surface heat transfer rate, thereby portraying the fouling resistance as negative. However, in the present work, no negative value of fouling resistance is reported. Fig. 10 depicts the experimental data related to the experimental fouling resistance as a function of time and at different mass flux. Noticeably, other operating conditions such as temperature and solution concentration remained constant. The experimental data in Fig. 10 demonstrates that with increasing the mass flux of nanofluid fouling resistance increases at constant surface and bulk temperature and constant nanofluid concentration. Also results illustrated that with increasing the heat flux, fouling rate significantly increases. In fact, increasing the wall temperature leads the fouling rate to increase. Fig. 11 also demonstrates that scale formation has a rectilinear change with the time and shows that with increasing the mass flux, sedimentation of nanoparticles significantly increases. 5. Conclusions Fig. 10. Fouling resistance and heat transfer coefficient as a function of time.

Rf ¼

1

aðtÞ



1

aðt ¼ 0Þ

Experimental investigation on subcooled flow boiling heat transfer coefficient of CuO water based nanofluid has been conducted and the following conclusions can be made:

ð25Þ

Fig. 10 shows changes of flow boiling heat transfer coefficient and fouling resistance with time. As can be seen in Fig. 9, subcooled flow boiling heat transfer coefficient decreases with time due to the deposition of CuO nanoparticles on the heat transfer surface. Because, these particles cover the heating surface and slightly change the thermal resistance of surface. On the other hand, according to previous studies, microcavity and wettability of surface change and bubbles cover the heating section too which lead to the heat transfer rate decreases. Experimental results reveal a linear increase of fouling resistance with time which is a result of nanoparticle sedimentation fouling. Walker and Sheikholeslami [50] reported an asymptotic behavior of fouling resistance which may be attributed to additional particulate fouling. Peyghambarzadeh et al. [49] showed that the fouling resistance in the initial stages of the test period decreases even hit the negative value at some points. He expressed that this phenomenon may be due to the fact that during the nucleation stage, the nuclei forming on

(a) According to the experimental results related to process of stabilization of CuO/water nanofluid, for dilute vol.% 0, 1 and 1.5 of nanoparticles at pH = 7.7 the maximum stability (about 216 h) is reported. (b) Experimental data show that two distinguishable heat transfer region was observed namely: forced convective and nucleate boiling heat transfer coefficient. In nucleate boiling zone, heat transfer coefficient values are much higher than those reported in forced convection zone. Because in nucleate boiling region, two phase heat transfer occurs while single phase heat transfer mechanism is the dominant phenomenon in forced convective region. (c) Experimental results showed that increasing the heat flux and mass flux leads to the flow boiling heat transfer coefficient significantly increases. In contrast, with increasing the concentration of nanofluid, deterioration of heat transfer coefficient both in forced convective and nucleate boiling region is seen.

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(d) A rough comparison was made between experimental heat transfer coefficients and those obtained by Chen correlation. Results of comparison showed that the fair agreement was established between experimental data and results calculated by Chen correlation (A.D.D = 30%) (e) Flow boiling around the vertical cylinder leads to the nanoparticles deposit on the heating section. With increasing the concentration of CuO nanofluid, fouling rate significantly increases. Also with increasing the wall temperature of cylinder and applied heat flux, fouling rate significantly increases. (f) It is shown that Fouling rate is a linear function of time, however, in previous works, asymptotic function of fouling rate with time were introduced for some particular dissolved salts.

Acknowledgements Authors of this research tend to dedicate this article to Imam Mahdi and appreciate Semnan State University for their scientific and financial supports. References [1] T. Lee, J.H. Lee, Y.H. Jeong, Flow boiling critical heat flux characteristics of magnetic nanofluid at atmospheric pressure and low mass flux conditions, Int. J. Heat Mass Transfer 56 (2013) 101–106. [2] L. Cheng, L. Liu, Boiling and two-phase flow phenomena of refrigerant-based nanofluids fundamentals, applications and challenges, Int. J. Refrigeration 36 (2013) 421–446. [3] S.U.S. Choi, Z.G. Zhang, W. Yu, F.E. Lockwood, E.A. Grulke, Anomalous thermal conductivity enhancement in nanotube suspensions, Appl. Phys. Lett. 79 (14) (2001) 2252–2254. [4] S.K. Das, N. Putra, W. Roetzel, Pool boiling characteristics of nano-fluids, Int. J. Heat Mass Transfer 46 (5) (2003) 851–862. [5] Y. Ding, H. Alias, D. Wen, R.A. Williams, Heat transfer of aqueous suspensions of carbon nanotubes (CNT nanofluids), Int. J. Heat Mass Transfer 49 (1–2) (2006) 240–250. [6] Y. He, Y. Jin, H. Chen, Y. Ding, D. Cang, H. Lu, Heat transfer and flow behavior of aqueous suspensions of TiO2 nanoparticles (nanofluids) flowing upward through a vertical pipe, Int. J. Heat Mass Transfer 50 (11–12) (2007) 2272– 2281. [7] S.M. You, J.H. Kim, K.H. Kim, Effect of nanoparticles on critical heat flux of water in pool boiling heat transfer, Appl. Phys. Lett. 83 (16) (2003) 3374–3376. [8] D. Wen, Y. Ding, Experimental investigation into the pool boiling heat transfer of aqueous based c-alumina nanofluids, J. Nanopart. Res. 7 (2) (2005) 265–274. [9] H. Kim, J. Kim, M.H. Kim, Effect of nanoparticles on CHF enhancement in pool boiling of nano-fluids, Int. J. Heat Mass Transfer 49 (25–26) (2006) 5070–5074. [10] S.J. Kim, I.C. Bang, J. Buongiorno, L.W. Hu, Effects of nanoparticle deposition on surface wettability influencing boiling heat transfer in nanofluids, Appl. Phys. Lett. 89 (15) (2006) 153107. [11] H.D. Kim, J.B. Kim, M.H. Kim, Experimental studies on CHF characteristics of nano-fluids at pool boiling, Int. J. Multiphase Flow 33 (2007) 691–706. [12] S.J. Kim, I.C. Bang, J. Buongiorno, L.W. Hu, Study of pool boiling and critical heat flux enhancement in nanofluids, Bull. Polish Academy Sci. Tech. Sci. 55, 2007. [13] S.J. Kim, T. McKrell, J. Buongiorno, L.W. Hu, Experimental study of flow critical heat flux in alumina–water, zinc-oxide–water and diamond–water nanofluids, J. Heat Transfer 131 (4) (2009). [14] T.I. Kim, Y.H. Jeong, S.H. Chang, An experimental study on CHF enhancement in flow boiling using Al2O3 nano-fluid, Int. J. Heat Mass Transfer 53 (2010) 1015– 1022. [15] D.C. Groeneveld et al., The1995 Look-up table for critical heat flux in tubes, Nucl. Eng. 163 (1996) 1–23. [16] Y.H. Jeong, M.S. Sarwar, S.H. Chang, Flow boiling CHF enhancement with surfactant solutions under atmospheric pressure, Int. J. Heat Mass Transfer 51 (2008) 1913–1919. [17] Y.H. Jeong, W.J. Chang, S.H. Chang, Wettability of heated surfaces under pool boiling using surfactant solutions and nano-fluids, Int. J. Heat Mass Transfer 51 (2008) 3025–3031. [18] J. Lee, Y.H. Jeong, CHF enhancement in flow boiling system with TSP and boric acid solutions under atmospheric pressure, Nucl. Eng. Des. (2010) 3594–3600. [19] G.P. Celata, K. Mishima, G. Zummo, Critical heat flux prediction for saturated flow boiling of water in vertical tubes, Int. J. Heat Mass Transfer 44 (2001) 4323–4331.

[20] K. Henderson, Y.G. Park, L. Liu, A.M. Jacobi, Flow-boiling heat transfer of R134a based nanofluids in a horizontal tube, Int. J. Heat Mass Trans. 5 (2010) 944–951. [21] E.A.H. Abdel-Hadi, S.H. Taher, A.M. Torki, S.S. Hamad, Heat transfer analysis of vapor compression system using nano CuO/R134a, Int. Conf. Adv. Mater Eng, IPCSIT 15 (2011) 80–84. [22] K. Stephan, Influence of oil on heat transfer of boiling refrigerant 12 and refrigerant 22, in: XI Congress of Refrigeration, vol. 1, 1963, pp. 369–380. [23] K. Mohrlok, K. Spindler, E. Hahne, The influence of low viscosity oil on the pool boiling heat transfer of the refrigerant R507, Int. J. Refrigeration 24 (1) (2001) 25–40. [24] M.A. Kedzierski, A semi-theoretical model for predicting R123/lubricant mixture pool boiling heat transfer, Int. J. Refrigeration 26 (3) (2003) 337–348. [25] K. Bartelt, Y. Park, L. Liu, A.M. Jacobi, Two-phase flow-boiling of R-134a/POE/ CuO nanofluid in a Horizontal Tube, in: 12th International Refrigeration and Air Conditioning Conference at Purdue, July 14–17, West Lafayette, IN, 2008. [26] J.S. Panek, J.C. Chato, J.M.S. Jabardo, A.L. de Souza, J.P. Wattelet, Evaporation Heat Transfer and Pressure Drop in Ozone-Safe Refrigerants and Refrigerant– Oil Mixtures ACRC TR-11, Air Conditioning and Refrigeration Center, University of Illinois at Urbana-Champaign, Urbana, IL, 1992. [27] W. Duangthongsuk, S. Wongwises, Effect of thermo-physical properties models on the predicting of the convective heat transfer coefficient for low concentration nanofluid, Int. Commun. Heat Mass Transfer 35 (2008) 1320– 1326. [28] M.M. Sarafraz, S.M. Peyghambarzadeh, S.A. Alavi Fazel, N. Vaeli, Nucleate pool boiling heat transfer of binary nano mixtures under atmospheric pressure around a smooth horizontal cylinder, Rperiodica Polytech. Chem. Eng. 56 (2) (2012) 1–7. [29] M.M. Sarafraz, S.M. Pyghambarzadeh, Nucleate pool boiling heat transfer to Al2O3–water and TiO2–water nanofluids on horizontal smooth tubes with dissimilar homogeneous materials, Chem. Biochem. Eng. Q 26 (3) (2012) 199– 206. [30] M.M. Sarafraz, S.M. Peyghambarzadeh, Experimental study on subcooled flow boiling heat transfer to water–diethylene glycol mixtures as a coolant inside a vertical annulus, Exp. Therm. Fluid Sci. 50 (2013) 154–162. [31] H.S. Ahn, H. Kim, H. Jo, S.H. Kang, W. Chang, M.H. Kim, Experimental study of critical heat flux enhancement during forced convective flow boiling of nanofluid on a short heated surface, Int. J. Multiphase Flow 36 (2010) 375–384. [32] H.S. Ahn, M.H. Kim, The boiling phenomenon of alumina nanofluid near critical heat flux, Int. J. Heat Mass Transfer 62 (2013) 718–728. [33] H.S. Ahn, S. Kang, H. Jo, H. Kim, M. Kim, Visualization study of the effects of nanoparticles surface deposition on convective flow boiling CHF from a short heated wall, Int. J. Multiphase Flow 37 (2011) 215–228. [34] L. Fedele, L. Colla, S. Bobbo, S. Barison, F. Agresti, Experimental stability analysis of different water-based nanofluids, Nanoscale Res. Letter (2011). [35] B.D. Cullity, S.R. Stock, Text Book of Elements of X-ray Diffraction, third ed., Prentice-Hall Publisher, pp. 170 (Chapter 5), 2001. [36] R. Saidur, K.Y. Leong, H.A. Mohammad, A review on applications and challenges of nanofluids, Renew. Sustain. Energy Rev. 15 (2011) 1646–1668. [37] S.M. Peyghambarzadeh, S.H. Hashemabadi, M. Naraki, Y. Vermahmoudi, Experimental study of overall heat transfer coefficient in the application of dilute nanofluids in the car radiator, Appl. Therm. Eng. 52 (2013) 8–16. [38] J.F. Seara, F.J. Uhia, J. Sieres, Laboratory practices with the Wilson plot method, Exp. Heat Transfer 20 (2007) 123–135. [39] S.J. Kline, F.A. McClintock, Describing uncertainties in single-sample experiments, Mech. Eng. 75 (1) (1953) 3–12. [40] X. Wang, X. Xu, S.U.S. Choi, Thermal conductivity of nanoparticles fluid mixture, J. Thermophys. Heat Transfer 13 (4) (1999) 474–480. [41] Y. Xuan, W. Roetzel, Conceptions for heat transfer correlation of nanofluids, Int. J. Heat Mass Transfer 43 (2000) 3701–3708. [42] V. Gnielinski, Wärmeübertragung in Rohren VDI Wärme atlas, fifth ed., VDIVerlag, Düsseldorf, 1986. [43] J.C. Chen, A correlation for boiling heat transfer to saturated fluids in convective flow, Ind. Eng. Chem. Process Design Dev. 5 (3) (1966) 322–329. [44] W.M. Rohsenow, Chapter in Heat Transfer, University of Michigan Press, Ann Arbor, IL, 1953. [45] J.G. Coiller, Boiling within vertical tubes, Heat Exchanger Design Handbook, Fluid mechanics and Heat Transfer, vol. 2, Hemisphere, Washington DC, 1984. [46] D.L. Bennett, J.C. Chen, Forced convective boiling in vertical tubes for saturated pure components and binary mixtures, AIChE J. 21 (1980) 454–461. [47] J.J. Schroder, Heat Transfer During Sub-Cooled Boiling, fifth ed., VDI-Warme atlas, 1988. [48] D. Gorenflo, Pool Boiling, VDI heat Atlas, Dusseldorf, Germany, 1993 (Chapter Ha). [49] S.M. Peyghambarzadeh, A. Vatani, M. Jamialahmadi, Application of asymptotic model for the prediction of fouling rate of calcium sulfate under subcooled flow boiling, Appl. Therm. Eng. 39 (2012) 105–113. [50] P. Walker, R. Sheikholeslami, Assessment of the effect of velocity and residence time in CaSO4 precipitating flow reaction, Chem. Eng. Sci. 58 (2003) 3807– 3816.