[ASME ASME 2009 Second International Conference on Micro/Nanoscale Heat and Mass Transfer - Shanghai, China (December 18–21, 2009)] ASME 2009 Second International Conference on Micro/Nanoscale

1 Copyright © 2009 by ASME

Proceedings of MNHMT2009 ASME 2009 2nd Micro/Nanoscale Heat & Mass Transfer International Conference

December 18-22, 2009, Shanghai, China

MNHMT2009-18553

HEAT TRANSFER OF FALLING FILM FLOWING AROUND A HORIZONTAL TUBE WITH NANOFLUIDS

Binglu RUAN 1, 2, Anthony M JACOBI 2, Liansheng LI 1 1National Engineering Research Center of Fluid Machinery and Compressor, School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an, PR of China, 710049

2Mechanical Science and Engineering, University of Illinois, Urbana, IL, USA, 61801

ABSTRACT Due to its high heat transfer coefficient and low working

fluid inventory, the horizontal-tube, falling-film heat exchanger finds wide application as an absorber, condenser and evaporator. Recent advances in nanotechnology suggest the use of nanofluids in heat exchangers. Some researchers find an enhanced heat transfer with nanofluids, while others report no enhancement or a deleterious effect on heat transfer when applying nanoparticles in the working fluids. In the current work, the thermal conductivity and kinematic viscosity of aqueous alumina nanofluids are measured at concentrations of 0 vol%, 0.05 vol%, 0.5 vol%, 1 vol% (with and without sodium dodecylbenzene sulfonate, SDBS), and 2 vol%. For these nanofluids, the impact of nanoparticles on thermal conductivity and viscosity is small (less than 5% for thermal conductivity and 13% for viscosity). The heat transfer characteristics of these nanofluids are measured and compared to predictions from the literature for conventional fluids. The falling-film heat transfer for these nanofluids is in good agreement with predictions, and no unusual heat transfer enhancement is observed in the present studies. Although the findings with water-alumina nanofluids are not encouraging with respect to heat transfer, the results extend nanofluid data to a new type of flow and may help improve our understanding of nanofluid behavior. Moreover, this work provides a basis for further work on falling-film nanofluids.

Keywords: falling film, heat transfer, nanofluids, thermal conductivity, kinematic viscosity

NOMENCLATURE

Ar Archimedes number based on tube diameter =d3g/ν2 cp constant-pressure specific heat

d tube diameter g gravitational acceleration h heat transfer coefficient k thermal conductivity Nu Nusselt number =(ν2/g)1/3h/k Pr Prandtl number =cpμ/k q heat flux Re film Reynolds number =2Γ/μ s tube spacing (see Hu and Jacobi [1] for detail) T temperature z axial coordinate Γ liquid mass flow rate per unit length of tube θ angular coordinate λ falling film departure site spacing μ dynamic viscosity ν kinematic viscosity ρ mass density σ surface tension at liquid/gas interface φ nanoparticle concentration Subscripts exp experiment f fluid nf nanofluid np nanoparticle o at outside of the tube pred prediction w water 1. INTRODUCTION

Falling-film, horizontal-tube heat exchangers, including

evaporators, condensers, and absorbers have been widely used in chemical, refrigeration, petroleum refining, desalination and food industries. These heat exchangers provide higher heat

Proceedings of the ASME 2009 2nd Micro/Nanoscale Heat & Mass Transfer International Conference MNHMT2009

December 18-21, 2009, Shanghai, China

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transfer coefficients and operate with smaller liquid inventories than flooded heat exchangers. They also mitigate fouling, non-condensable-gas effects and some other heat exchanger problems.

Since 1888, when the first patent of a falling-film horizontal-tube evaporator was registered, studies of falling film heat exchangers have been carried out by many investigators seeking performance improvements. The effects of heat flux [2, 3], liquid flow rate [4, 5], tube diameter [2, 3], tube spacing [3, 4, 6], liquid distributor configuration [7-9], liquid distributor height [4, 10, 11], enhanced surfaces [5, 12] and a vapor flow [3, 6] on intertube falling-film heat transfer behavior were investigated and some predictive correlations were developed for falling-film heat exchanger design.

Mitrovic [4] studied the tube spacing and flow rate effects on the intertube falling-film heat transfer and gave a correlation for water with 160 < Re < 560:

0.1582 0.349 0.5

3 1.32

(1 / )1.374(10 ) Re Pr1 exp 3.2(10 ) Re

s dNu −

−

+=

⎡ ⎤+ −⎣ ⎦ (1)

Hu and Jacobi [3] investigated the falling film mode effects on heat transfer, and based on 291 heat transfer experiments with Re<1900 developed correlations for the sheet mode,

0.28 0.14 -0.20 0.07=2.194Re Pr Ar ( / )Nu s d (2)

jet mode,

0.42 0.26 -0.23 0.08=1.378Re Pr Ar ( / )Nu s d (3)

and for the droplet mode,

0.85 0.85 -0.27 0.04=0.113Re Pr Ar ( / )Nu s d (4)

Recently, colloid suspensions of nanometer-sized particles, referred to as nanofluids, have been of interest for heat transfer applications, because of their potentially enhanced thermal conductivity [13]. Nanofluids have been shown to exhibit a significant thermal conductivity, with the experimental work of Xuan and Li [14], Choi et al. [15], Eastman et al. [16] and others showing thermal conductivity enhancements beyond the predictions of classical heterogeneous mixed media models, such as Maxwell-Garnett [17] and Hamilton and Crosser [18]. There is ongoing research directed at exploring the potential of nanofluid convective heat transfer enhancement.

Many investigators have reported an enhanced Nu in single-phase convective heat transfer using nanofluids. Wen and Ding [19] investigated the heat transfer of aqueous-alumina nanofluids with sodium dodecylbenzene sulfonate (SDBS) in a laminar flow through a horizontal tube and found that the nanofluids significantly enhanced the convective heat transfer, especially in the entrance region. Yang et al. [20] studied the convective heat transfer performance of the graphite nanofluids in the same flow and observed that the dispersed nanoparticles increase the heat transfer coefficient, but the increase was much less than expected. Ding et al. [21] observed a very large heat transfer enhancement for aqueous suspensions of multi-walled carbon nanotubes (MWCNT) flowing through a horizontal

tube. The maximum enhancement reached over 350% for nanofluids containing 0.5 wt % (0.048 vol %) MWCNT. Heris et al. [22] employed aqueous Al2O3 and CuO in different concentrations in their heat transfer experiments of a laminar flow through a circular tube and they observed that the heat transfer enhancement is beyond what is predicted by the homogenous model. Xuan and Li [23] also obtained a 35% Nu enhancement for a turbulent flow through a horizontal tube with a nanofluid of 2 vol % copper dispersed in water at 9800< Re <23600. Most of these heat transfer increase are beyond what would be expected from thermal conductivity enhancement.

However, some researchers reported a deleterious effect on Nu or no heat transfer enhancement in their convective heat transfer experiments involving nanofluids. Putra et al. [24] applied the aqueous Al2O3 and CuO nanofluids in a horizontal-cylinder natural convection application and obtained a reduced Nu. Wen and Ding [25] applied HNO3/NaOH treated TiO2 nanofluids in a vertical-cylinder natural convection application and received a deleterious effect on Nu. Rea. et al. [26] investigated the laminar convective heat transfer in a flow loop with a vertical heated tube using aqueous alumina and zirconia nanofluids at a maximum concentration of 6 vol % and they observed no abnormal heat transfer enhancement.

Nanofluid studies have been carried out for several heat transfer applications, and it seems that the heat transfer behavior is quite different for different flows; however, until very recently there had been no nanofluid research with falling films. Kang et al. [27] studied falling film absorption process of binary nanofluids with Fe and carbon nanotube (CNT) nanoparticles at concentration of 0, 0.01, 0.1 wt %. They observed no significant heat transfer enhancement but a significant mass transfer enhancement without explanation. However, their nanoparticle concentration is very low compared to those used in internal flow, and this might be a reason that no heat transfer enhancement was observed. Meanwhile, their data are limited to four mass flow rates and three nanoparticle concentrations. Up to now, no systematic falling-film heat transfer and corresponding mode-transition studies involving nanofluids have been reported in the open literature. In this paper, a comprehensive investigation of falling-film horizontal-tube heat transfer behavior of nanofluids will be provided. Understanding of falling-film heat transfer and mode-transition behavior involving nanofluids will provide a basis for applying nanofluids in this type of application including evaporators, condensers and absorbers. Hopefully it may also help an improvement of limited understanding of nanofluid heat transfer enhancement.

2. EXPERIMENT 2.1 Experimental Apparatus

The schematic diagram of the experimental apparatus is shown in Fig. 1. It consisted of a pump, a flow meter, two needle valves and a test chamber. The speed adjustable pump



delivered the test liquid from the bottom of the test chamber, which is also a liquid collector, through a flow meter, two

Fig.1 Schematic diagram of the experimental apparatus.

(a)

(b)

Fig.2 Falling film liquid distributor.

needle valves and then back to the test chamber. In the test chamber, the liquid flow was divided into two parts and fed in the feeding tube from two opposite directions. A uniform liquid axial distribution was realized by a feeding system with double distributions (see Fig.2, (b) is a partial, schematic, cross-section A-A view of (a)). The first distribution was complicated by a PVC tube with 61 holes, 3 mm in diameter, 5 mm apart (center to center) on the bottom. The secondary distribution was achieved by a plexiglas box with 60 holes, 1 mm in diameter, 5 mm apart (center to center) on the bottom. The positions of the secondary distribution holes were adjusted carefully to be aligned with the center of the two first distribution holes. When liquid flow went into the PVC tube from opposite directions, it passed through the first distribution holes into the plexiglas box, and established a liquid level within it (or even filled it if the flow rate was large) to reach a uniform liquid distribution.

After being distributed by the feeding system, the liquid flowed around a stabilizing tube, then impinged on the test tube, and then collected in the liquid collector. The gap between the bottom of the plexiglas box and the top of the stabilizing tube was 1mm. 2.2 Instrumentation

The liquid mass flow rates were measured using a Coriolis-effect flowmeter (with an uncertainty of ± 0.1%). The fluid inlet temperatures were measured by a T-type thermocouple placed in the gap between the bottom of the feeding plexiglas box and the top of the stabilizing tube.

A copper tube with an outside diameter of 19.05mm and a wall thickness of 1.65mm was employed in the experiments. On the test tube, eight 30-gauged copper-constantan thermocouples were embedded in axial grooves (1mm deep×1.2 mm wide×101.60mm length) at 45 degree circumferential increments to measure the test tube surface temperature, as shown in Fig.3. Each thermocouple junction was carefully fixed to the end of an axial groove by using a thermally

Fig.3 Thermocouple placement on the test specimen tube. conductive epoxy (with a thermal conductivity of 1.3 W/(m·K)). After making sure that all thermocouple junctions were in contact with the test tube surface at the end of the axial grooves, the thermocouple wires were placed inside of the grooves and the same epoxy was used to fill those grooves. After the epoxies cured, the test tube was first polished by a fine emery cloth (320/P400), and then an even finer emery cloth (400/P800) to remove the excess epoxy and smooth the test tube surface. All the thermocouple beads and wires were barely visible after the polish. An electric-resistance heater was pressed into the test tube after applying a thermal grease. Bakelite supports were fastened at two ends of the test tube along with the heater to minimize the heat conduction end-losses. An AC voltage transformer was used to transfer the 110 V power source to a desired power to the heater. The heater input (voltage×current) was measured by a multimeter (with an uncertainty of ±1.5% for voltage and ±3% for current), and these data were used to infer the inside surface heat flux to the test tube.

Before embedding thermocouples into the test tube, all the thermocouples including those used to measure the fluid inlet temperature were calibrated using a thermostatic bath (NESLAB RTE-210) and a standard RTD thermometer (ASL, Precision Thermometer F200) to ensure accurate surface



temperature measurements within ±0.1ºC over the entire experimental range. During the experiments, each thermocouple was sampled every 2 seconds at steady state for 2 minutes by a SCXI data acquisition system (DAQ), and the readings were averaged.

2.3 Nanofluid Preparation

The nanofluids in the experiments were made by dispersing aluminum oxide nanoparticles into distilled water. The nanoparticles used in this work were purchased from Alfa Aesar Co. with a nominal average size of 47nm. The reason to choose alumina nanoparticles was that they are relatively inexpensive and the dispersion in industrial applications may be attainable. Five concentrations of nanofluids, 0 vol%, 0.05 vol% (0.20 wt%), 0.5 vol% (1.96 wt%), 1 vol% (3.86 wt%) and 2 vol% (7.51 wt%) were made for investigating the effects of the nanofluid concentration on falling film heat transfer behavior. An even high concentration of nanofluids may cause problems in application. Additionally, a 1 vol% (3.86 wt%) aqueous alumina nanofluid with sodium dodecylbenzene sulfonate (SDBS) was also made to understand the surfactant effects on nanofluid properties and heat transfer behavior. When preparing the nanofluids, first, nanoparticles were dispersed into a glass breaker containing 500ml of distilled water. After nanoparticles were immerged in the water, an ultrasonic homogenizer (Omni-Ruptor 400) was employed to break the aggregation of the nanofluid in the glass breaker. The nanofluids were sonicated under the sonicator at a setting of 200W, pulse 60~70, frequency 20 kHz for 2 hours. The sonicator probe could handle a maximum volume of 500 ml of fluid. Then, the highly concentrated nanofluids were diluted 10 times to the desired concentrations and the volume of these nanofluids was necessary to meet the minimum liquid inventory (5 Liter) for running the liquid loop of the experimental system. In order to obtain a better dispersed nanofluid, the diluted nanofluids were sent back under the sonicator for another 1 hour. Then the diluted, sonicated nanofluids at different concentrations were placed still in the lab for more than one week. No obvious sediment was found for those nanofluids and the transmission electron microscopy (TEM) photos of the nanofluids at 0.5% and 2% was shown in Fig. 4. Comparison of Fig. 4(a) and Fig. 4(b) reveals that some aggregation might occurs in 2% nanofluids. However, the aggregation we observed could also be introduced by the TEM specimen-making processes. More investigation should be carried out on nanofluids dispersion. For the current experiments, no further effort was made to break the aggregation since the nanofluids are stable enough for the experiments. In order to compare to the results with Wen and Ding [19], the 1% nanofluids with SDBS was dispersed in a same way reported by Wen and Ding [19]. The SDBS with one tenth of mass of nanoparticles was first mixed with 5 Liter distilled water, and then nanoparticles were dispersed inside. After being stirred with a paint mixer, the nanofluid was sonicated using the same setting as earlier for 2 hours. Then,

the 5L nanofluid was poured into ten 500ml glass breakers, each of which was sonicated for another 2 hours.

2.4 Fluid Properties Measurement

In order to compare results with the existing literature, fluid properties used in the experiments are obtained based on the fluid inlet temperatures. Fluid properties needed to calculate the falling film heat transfer coefficients and Nusselt numbers in the experiments including thermal conductivity k, kinematic viscosity ν, density ρ and specific heat cp.

(a)

(b)

Fig.4 TEM images of dispersed aluminum oxide nanofluid: (a) 0.5%;(b) 2%.

Thermal conductivity was measured using a KD2-pro

thermal property meter (Decagon Devices) which is based on the well-known hot wire method and calibrated by the manufacturer. The KD2 pro thermal property meter has a probe of 60mm in length and 1.3mm in diameter, which integrates a heating element and a thermometer. Both the heat output and the temperature rise of the probe are sent to a microprocessor for conducting measurements and calculating thermal properties of a fluid. Since the falling film heat transfer coefficient is insensitive to fluid inlet temperature [28], and because of the limited fluid inlet temperature range in the experiments (20~40ºC, with an expected thermal conductivity variation of only 5% [29]), thermal conductivity was recorded at room temperature (around 20 ºC) at different concentrations. A 500 ml standard glass breaker was used to hold the test sample for an overnight test, and the ‘Auto Mode’ was used to take the measurement every 30 minutes. The manufacturer indicates the uncertainty in thermal conductivity is ±5% for the KD2-pro; however, in these experiments differences in thermal conductivity are most relevant. By recording at least 20



repeated measurements and averaging the results, it was found that the maximum deviation from the average was always less than ±3%; thus, the repeatability, which is relevant in measuring differences in thermal conductivity, is ±3%.

The viscosity of test fluids was measured using a factory calibrated glass capillary viscometer (Cannon CFRC 9721-B50, size 25) from 15 ºC to 60 ºC at 5 ºC intervals, with an uncertainty of ±0.25%. The viscometer was placed in a transparent plexiglas chamber with a constant temperature circulating water supplied by a thermostatic bath. The fluid densities were also measured by the Coriolis-effect flowmeter with an uncertainty of ±0.5 kg/m3 during the experiments. According to the observation of Yang et al. [20] and Namburu et al.[30], dispersing a small amount of nanoparticles does not have significant effect on the specific heat of nanofluids. Hence, the heat capacities of nanofluids were calculated using conventional mixing theory: (ρcp)nf = (1-φ) (ρcp)f +φ(ρcp)np (5) 2.5 Experimental Scope and Procedure

The falling film heat transfer coefficient and Nu could depend on the liquid flow rate, liquid temperature, surface heat flux, tube diameter, tube spacing and the test fluid properties. The experimental ranges of these parameters are summarized in Table 1.

Table 1 Experimental range of the relevant physical variable

Physical Parameter, Symbol Experimental Range UnitsMass flow rate per unit length, Γ 0.02 to 0.37 kg/m·s

Fluid kinematic viscosity, ν 7.0(10−7) to 10.5(10−7) m2/s Mass density of the liquid, ρ 998.8 to 1058 kg/m3

Fluid thermal conductivity, k 0.587 to 0.614 W/m·KFluid specific heat, cp 3800 to 4180 J/kg·K

Tube spacing, s 10(10−3) m Tube diameter, d 19.05(10−3) m

Heat flux, q up to about 2.9(104) W/m2

Fluid inlet temperature, Tf 20 to 40 ºC

Nanoparticle concentration, φ 0%, 0.05%,0.5%,1%,2%

Before conducting a heat transfer experiment, the system

was charged with the prepared nanofluid and circulated for at least an hour at sheet mode until both the stabilizing tube and the test tube were fully wetted. Then, the liquid flow rate was decreased until stable jet mode appeared to ensure that those jets fell from the same sites without any shifting. Then the heater inside the test tube was powered on. The surface temperature of the test tube and the liquid inlet temperature were recorded after they reach the steady states. Fluid flow rate, density, the voltage and the current powered to the heater were also recorded during the measurements. This procedure was repeated for wide-range flow conditions to include each possible mode for each test liquid.

Since the wide circumferential distribution of the local convective heat transfer coefficient for a falling-film jet mode [3], local test tube surface temperatures were measured evenly

at 6 positions in half a departure site spacing λ (around 2mm apart), and the average of the 48 local heat transfer coefficient (6 positions ×8 angles) was taken and averaged as the overall tube surface heat transfer coefficient.

2.6 Data Reduction

In order to compare the results with the existing literature, four dimensionless parameters, the film Reynolds number, the Archimedes number, the Prandtl number and the dimensionless tube spacing were determined for the experimental conditions, allowing Nu to be calculated from correlations such as those in Eqs (1)-(4). The experimental Nusselt number was inferred from the local surface temperature measurements. In order to determine the Nusselt number, it was necessary to calculate the local heat transfer coefficient h(θ ,z) as:

( , )( , )

( , )o

o f

q zh z

T z Tθ

θθ

=−

(6)

where qo (θ ,z) is the local outer-tube surface heat flux, To(θ ,z) is the local outer-tube surface temperature, Tf is the fluid inlet temperature. Since the test tube wall thickness was small (1.6mm), circumferential heat conduction in the test tube due to the local surface temperature differences was neglected, and the heat flux at the tube outer surface was considered uniform. Hence, ( , )oq zθ is calculated directly by the measured voltage, current and the test tube surface area exposed to the flow. The local Nusselt number ( , )Nu zθ is determined using [3]:

1 / 32( , )( , ) h zNu zk g

θ νθ⎛ ⎞

= ⎜ ⎟⎝ ⎠

(7)

which is consistent with and easy to compare to predictions from Eqs (1)-(4). Both the overall heat transfer coefficients h and the overall Nusselt number Nu were obtained by averaging the local heat transfer coefficients and the local Nusselt numbers under the same operating condition.

The experimental range and estimated uncertainty for the dimensionless parameters are summarized in Table 2. The uncertainties of both the local and average heat transfer coefficient and Nusselt number not only depend on the experimental operating conditions but also the angle and spatial location of interest. However, it was estimated that the uncertainty of the heat transfer coefficient was typically ±6% and that of Nusselt number was typically ±8%.

Table 2 Relevant dimensionless parameters, the experimental range

and estimated uncertainty Dimensionless

Parameter Experimental Range Estimated Uncertainty

Ar=d3g/ν2 6.14(107) to 1.36(108) ±0.9% Pr=cpμ/k 4.85 to 7.14 ±6.0% Re=2 Γ/ μ 65 to 950 ±1.5%

s/d 0.53 ±1.1%



3 RESULTS AND DISCUSSION 3.1 Fluid Property Measurements 3.1.1 Thermal conductivity

Thermal conductivity of the distilled water was measured and compared with Kays and Crawford [31], before the measurements of nanofluids. Excellent agreement was found and the thermal conductivities of nanofluids were then obtained and are presented in Fig.5. It is observed that the present experimental data for nanofluids and the data from the literature are in good agreement. Increasing the concentration of nanoparticles to 2% could result in a thermal conductivity enhancement of 4.6%. It can be seen that at 1% and 2% nanopartical concentrations, the measured increases reflected by our data are slightly lower than those of Lee et al. [32] and Das et al. [33], which might be due to the different nanoparticle size they used. Both Lee et al. [32] and Das et al. [33] measured their data at room temperature; however, the mean diameter of their nanoparticles was 38.4nm, which is relatively smaller than what was used in the current experiment. It also seems that the surfactant SDBS does not have an obvious effect on the thermal conductivity for the 1% nanofluid in the current study in contrast to Wen and Ding [19] (27~56nm aqueous alumina nanofluid at 22ºC).

0.00 0.01 0.02 0.031.00

1.02

1.04

1.06

1.08

1.10

1.12

1.14

1.16

1.18

1.20 present experiments Hamilton-Crosser model:spheres[18] Lee et al.[32] Das et al.[33] present experiments:with SDBS Wen and Ding (2004):with SDBS[19]

Ther

mal

con

duct

ivity

ratio

k/k

w

Volume concentration

Fig.5 Measured thermal conductivity ratio of alumina nanofluids at different concentrations and the comparison between experimental

data and the literatures.

3.1.2 Kinematic viscosity The viscosity change of nanofluids may also be an

important issue when calculating Nusselt number. The well-known Einstein formula has been used by some researchers [34] to evaluate the effective viscosity of a linearly viscous fluid containing a dilute suspension of small rigid spherical particles. However, Einstein formula has restrictions and the experiment data of kinematic viscosity for nanofluids with a temperature range from 15ºC~60 ºC are quite limited. Hence, experimental investigation on temperature effect on kinematic viscosity of nanofluids was necessary in the current work. The viscosity of distilled water at 15ºC~60 ºC was measured and

compared with Kays and Crawford [31], and the average deviation was 1.3%. Then, the viscosity of nanofluids at different temperatures and concentrations with and without SDBS was measured and the results are shown in Fig. 6 (a). It is clear that the viscosities of both distilled water and nanofluids are quite sensitive to the temperature and decease systematically with a temperature increase. When comparing the data at 30 ºC for different concentrations (see Fig.6 (b)), it seems that the kinematic viscosity increased nonlinearly with the volume concentration of nanofluids. The viscosity of nanofluids increased 12.5% at 2% nanoparticle concentration, which is much higher than the thermal conductivity enhancement at the same concentration. The viscosity increase of nanofluids is more pronounced at a higher concentration and a lower fluid temperature, which suggests challenging heat-transfer-pressure-drop tradeoffs in application.

0 10 20 30 40 50 60 704.0x10-7

5.0x10-7

6.0x10-7

7.0x10-7

8.0x10-7

9.0x10-7

1.0x10-6

1.1x10-6

1.2x10-6

1.3x10-6

1.4x10-6

1.5x10-6

Kin

emat

ic v

isco

sity

_ν(m

2 /s)

Temperature (oC)

distill water 0.05% nanofluid 0.5% nanofluid 1% nanofluid 2% nanofluid 1% nanofluid:with SDBS

(a)

0.000 0.005 0.010 0.015 0.020 0.025 0.0308.0x10-7

8.2x10-7

8.4x10-7

8.6x10-7

8.8x10-7

9.0x10-7

9.2x10-7

9.4x10-7

experimental data experimental data:with SDBS trend line

Kin

emat

ic v

isco

sity

_ν(m

2 /s)

Volume concentration (b)

Fig.6 Measured kinematic viscosity of nanofluids: (a) behavior with

temperature at different concentrations; and (b) behavior with nanofluid volume concentration at 30ºC.

3.2 Heat Transfer Results 3.2.1 Baseline test of experimental system

Before the nanofluid experiments, distilled water was used to conduct baseline experiments and the results were compared with the literature. Fig.8(a) shows the Nu dependence on Re of



baseline data and predictions from the correlation of Hu and Jacobi [3]. Fig. 8(b) shows a comparison between baseline Nu and the predictions by Hu and Jacobi [3]. Heat transfer results at both sheet mode and jet mode agree very well with predictions, corroborating the experimental procedures. However, the heat transfer data of the droplet mode are lower than the prediction from Hu and Jacobi [3] by around 20%. The reason for the discrepancy is unclear. It is notable that the experimental data agree well with Ganic and Roppo [28] (see Fig.8(c)), even though they employed an enhanced tube in their studies. In the following discussion, the heat transfer data for distilled water in present experiments will be considered as the baseline data for comparison to data for nanofluids. 3.2.2 Heat transfer results of nanofluids

Heat transfer data for nanofluids are compared to the predictions of Hu and Jacobi [3] in Figs. 9-11 for three flow regimes at different particle concentrations. In order to see the system differences before and after the nanofluid experiments, experiments for pure water were carried out again after all the nanofluid experiments were finished. As shown in these figures, both the baseline and nanofluid data for sheet mode and jet mode were within about 8% of the predictions, which was the typical uncertainty in the measurements, as discussed earlier. Although the nanofluid data for droplet mode were still lower than Hu and Jacobi’s [3] predictions, the results were consistent with the pure-water data in present work

When comparing the heat transfer data of the 1% nanofluid with and without SDBS (see Fig.12), still no significant heat transfer enhancement was observed. This finding suggests that the nanofluids without the SDBS in present experiments indeed formed stable suspensions; no further surfactant was needed for the preparation of aluminum oxide nanofluids.

The heat flux effects on Nu were also explored and no significant heat transfer enhancement was observed.

These results show that the presence of alumina nanoparticles has no impact on the intertube falling film heat transfer, beyond the experimental uncertainty of this work. Some possible reasons might be as follows:

a. From a macroscope point of view, the properties of a homogenous nanofluid which affect the heat transfer behavior can be viscosity, density, thermal conductivity, and specific heat. In this study, a 12.5% kinematic viscosity increase was observed for 2% nanofluid at 30ºC and a 4.6% thermal conductivity enhancement was recorded at room temperature. The fluid density increased 6% and the calculated specific heat decreased 9% typically at the maximum nanofluid concentration. The relation between Nu and fluid properties can be derived from definition of Nu (Eqn.(7)) as:

Nu∝ν2/3k-1 (8) For the sheet mode, the predicted Nu by Hu and Jacobi [3] (Eqn.(3)~(5)) can easily be derived as:

Nupred∝ν0.28(cpρ/k)0.14 (9)

For the jet mode,

Nupred∝(cpρ/k)0.26 (10)

and for the droplet mode,

Nupred∝ν0.54(cpρ/k)0.85 (11)

By substituting the thermal conductivity enhancement and viscosity, density, specific heat increase obtained in the experiments, we expect a 1.2%, 5.5% and 4.1% Nu increase for the sheet mode, jet mode and droplet mode, respectively. All of these Nu enhancements are within the average uncertainty of the Nu measurements. The simple calculation agrees well with experiment results. However, the effect of fluid properties change might not be the only reason for observing no heat transfer enhancement in the experiments. There might be some other reasons accounting for the heat transfer enhancement observed by other investigators for applications with different flows.

0 100 200 300 400 500 600 700 8000.0

0.1

0.2

0.3

0.4

0.5

0.6

present experiments Hu and Jacobi's prediction[3]

Nu

Re

(a)

0.0 0.1 0.2 0.3 0.4 0.50.0

0.1

0.2

0.3

0.4

0.5

+20%

Droplet Mode Jet mode Sheet mode

Nu_

exp.

Nu_predicted by Hu and Jacobi[3]

-20%

(b)



500 1000 1500 2000 2500 3000 3500500

1000

1500

2000

2500

3000

3500

h_pr

esen

t exp

erim

ents

h_by Ganic and Roppo[28]

(c)

Fig. 8 Falling film heat transfer of pure water: (a) Nusselt number behavior with Re compared with predictions by Hu and Jacobi [3]; (b) Nu comparison between experimental data and

predictions by Hu and Jacobi [3] at three falling film modes; (c) comparison of heat transfer coefficients of droplet mode between

present experiments and Ganic and Roppo[18].

b. In reviewing the literature, it can be seen that researchers who studied the nucleate boiling heat transfer enhancement reported both a reduced heat transfer [35-37] and an enhanced heat transfer [38]. A thin porous nanoparticle layer on the heated surface was attributed to the deleterious effects on heat transfer[39-41]. No such layer was reported for the non-boiling heat transfer studies with nanofluids. However, this layer could also form in the non-boiling flow due to the nanoparticle

0.0 0.1 0.2 0.3 0.4 0.50.0

0.1

0.2

0.3

0.4

0.5

+8%

2% nanofluid 1% nanofluid 0.5% nanofluid 0.05% nanofluid 0%_after nanofluid exp. 0%_before nanofluid exp.

Nu_

exp.


-8%

Fig.9 Nusselt number comparison between experimental data of nanofluids and predictions by Hu and Jacobi [3] for sheet mode.

0.0 0.1 0.2 0.3 0.4 0.50.0

0.1

0.2

0.3

0.4

0.5

+8%-8%


Nu_

exp.


Fig. 10 Nusselt number comparison between experimental data of nanofluids and predictions by Hu and Jacobi [3] for jet mode.

0.0 0.1 0.2 0.3 0.4 0.50.0

0.1

0.2

0.3

0.4

0.5

-20%

+20%


Nu_

exp.


Fig. 11 Nusselt number comparison between experimental data of nanofluids and predictions by Hu and Jacobi [3] for droplet

mode.

aggregation and sediment. This layer could be very thin, modify the heat transfer surface, increase the heat transfer surface area, and finally lead to an enhanced heat transfer. The layer could be relatively thick, bringing an extra thermal resistance between the nanofluid and the heated surface and hence introduce a reduced heat transfer. For the non-boiling heat transfer experiments, though the nanoparticle layer would likely not form in a short time as in the boiling experiments, and it is much easier for nanoparticles to settle on the heated surface when the nanofluid flows inside a horizontal tube than when the fluid flows around the outside tube. In this study, no obvious layer was observed on the test surface. For the researchers who obtained a heat transfer enhancement for nanofluid flow inside a horizontal tube, surface modification might be one of the reasons. Further investigations are needed to verify this effect.



0.0 0.1 0.2 0.3 0.4 0.50.0

0.1

0.2

0.3

0.4

0.5+8%

-8%+20%

-20%

Sheet Jet Droplet Sheet: with SDBS Jet: with SDBS Droplet: with SDBS

Nu_

exp.


Fig.12 Nusselt number comparison between experimental data of 1 vol% nanofluids and predictions by Hu and Jacobi [3] for all falling film modes with and without the surfactant SDBS.

4 CONCLUSIONS

The intertube, falling-film heat transfer characteristics of aluminum oxide nanofluids were investigated, at five particle volume concentrations, 0%, 0.05%, 0.5%, 1%, and 2%, along with a 1% nanofluid with surfactant SDBS. The kinematic viscosity and the thermal conductivity of the nanofluids were measured. Then falling-film heat transfer experiments for nanofluids with different concentrations were conducted and the results were compared with both baseline data (for distilled water) and the predictions by Hu and Jacobi [3]. The results showed that all the Nusselt number increases were within the uncertainty of measurements, and no unusual heat transfer enhancement was observed. There might be two possible reasons for the results. First, the thermal conductivity of these nanofluids did not depart significantly from that of the base fluid, and thermophysical property changes examined in view of their anticipated impact on Nu from prior work suggest that only small heat transfer effects should be anticipated. Second, the interactions between nanoparticles and the surface of the test tube for a falling film flow with heat transfer seem to be such that little if any surface modification occurs. Since fluid property effects and surface modification are the expected mechanisms for heat transfer enhancement and neither was present in this flow with these nanofluids, there was apparently no pathway to an enhancement.

ACKNOWLEDGMENTS The authors thank Dr. Scott J. Robinson and Dr. Leilei Yin

in the BECKMAN institute at the University of Illinois for their assistance in obtaining TEM photos for nanofluids.

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[ASME ASME 2009 Second International Conference on Micro/Nanoscale Heat and Mass Transfer - Shanghai, China (December 18–21, 2009)] ASME 2009 Second International Conference on Micro/Nanoscale