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Experimental Investigation of Effective Viscosity and Density of Nanofluids
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ScienceDirect Materials Today: Proceedings 16 (2019) 504–515
www.materialstoday.com/proceedings
ICAMMAS17
Experimental Investigation of Effective Viscosity and Density of Nanofluids. Durgeshkumar Chavana, Dr. Ashok Piseb. b
aHead of Department, Mechanical Engg. Government Polytechnic, Ambad Dist. Jalna- 431204 Professor, Mechanical Engg. Government College of Engineering, KaradDistSatara, India – 415110
Abstract In the present research work, the effect of nanoparticles volume concentration and the temperature on the effective viscosity and the density of nanofluids were investigated. The stable nanofluids using different base fluids and nanoparticles with varying nanoparticles concentration were prepared. The Rheometer and density meter (Anton Parr Make) were used for the measurement of viscosity and density of nanofluids. The experimental results clearly shows that the viscosity of nanofluid, increase with increase in particle volume concentration and decreases with increase in temperature of nanofluids. The increment in viscosity differs with different base fluids. The classical formulas for viscosity under predict the viscosity enhancement. Experimental data for density of nanofluids shows increase in density with increase in nanoparticles concentration. The temperature has negligible effect on the density of nanofluid. The mixture formula shows good agreement to predict the density of nanofluid. ©2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Advances in Materials, Manufacturing and Applied Sciences. Keywords: Effective viscosity, density, nanofluid, base fluid, rheometer
1.
Introduction Heating or cooling fluids such as water, engine oil and ethylene glycol plays a crucial role in thermal
management of high-tech industries but they have poor thermal characteristics, in particular thermal conductivity. Despite considerable efforts to improve the rate of heat transfer by usage of extended surfaces, mini-channels and micro-channels, further enhancement in heating and cooling rate is always in demand. With ever increasing thermal loads due to high power output and smaller features of microelectronics devices, improvement to make heat transfer equipment more energy efficient become most important technical issue. The thermal management of many applications like transportation, manufacturing and micro-electronics is very important, to maintain their desired performance and durability.
* Corresponding author. Tel.:+91-9970700780; fax:+91-2483275010 E-mailaddress:[email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Advances in Materials, Manufacturing and Applied Sciences
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The improvement to make heat transfer equipment more energy efficient can be made by focus on reduces the size on one hand and huge increase in heat flux on the other. Heat transfer fluids such as water, mineral oil and ethylene glycol are used in many industrial processes. The poor heat transfer properties of these common fluids compared to most solids is a primary obstacle to the high compactness and effectiveness of heat exchangers. As the thermal conductivity of a fluid plays a vital role in the development of energy efficient heat transfer equipment, there is need to find new heat transfer fluid with has higher thermal properties and an advanced cooling techniques. With enhancement in nanotechnology, manufacturing solid particles down to the nanometer scale becomes easier, a new class of heat transfer fluid called Nanofluids can be developed. Nanofluid is heat transfer fluid in which nanometer sized solid particles are dispersed in traditional heat transfer fluid. These fluids have their potential benefits like higher heat conduction, large relative surface area, excellent stability and minimal clogging Along with thermal conductivity, viscosity is important property of the heat transfer fluid that needs to be investigated as pumping power required for circulation of working fluid and pressure drop across the thermal system are directly related to viscosity. The viscosity of nanofluid depends on nano-particle loading and the temperature. Some researchers reported that viscosity of nanofluid is temperature independent. With dilute volume concentration, nanofluids show Newtonian behavior. Very limited literature is available on the effect of temperature on viscosity of nanofluids. Density plays very important role in heat transfer especially in natural convection. As natural convection affected by the buoyancy force and density gradient, accurate determination of the density of nanofluids is very important in the heat transfer applications using nanofluids. 2. Experimental and Theoretical Studies Review In the design of thermal systems, viscosity and the density of the working fluid plays the vital role. In comparison with the study of thermal conductivity of nanofluids, very few studies were reported on the effective viscosity and the density of the nanofluids. The experimental and theoretical models developed for effective viscosity and density are discussed as below. Wang et al. [1]used mechanical blending technique for nanofluid preparation and measure effective viscosity of Al2O3 (28 nm)/ DI water nanofluid. They reported about 86% increment in the effective viscosity for a 5 vol.%of nanoparticles and an increase of 40 % in viscosity of Al2O3/ethylene glycol base nanofluid at a volumetric loading of 3.5%. Masuda et al. [2]recorded 60% increase in the viscosity of water at a volumetric loading of 4.3 vol. % loading of TiO2(27 nm) nanoparticles. Pak and Cho [3]observed several times increment in the viscosity of water with 10 vol.% addition of Al2O3 (13 nm) and TiO2 (27 nm) nanoparticles. They concluded that the large increment in viscosity may be due to differences in dispersion techniques and size of the particles. They apply an electronic repulsion technique and adjusted pH values, and found that viscosity of nanofluids depends on the methods used to disperse and stabilize the nanoparticles suspension. The experimental obtained were significantly larger than the prediction from classical model of Einstein [4]. The effect of shear rate on the viscosity of Al2O3/water and CuO/water-based nanofluids was studied by Das et al. [5] and Putra et al. [6]andreported Newtonian behavior of the nanofluids for a range of volume percentage between 1% and 4%. Das et al.[5] also observed an increase in viscosity with an increase of particle volume fraction
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for Al2O3/water based nanofluids. Ding et al. [7] experimented effect of particle loading and temperature on viscosity of nanofluid at a given shear rate and observe increase in viscosity of nanofluids with increase in CNT concentration and decreasing temperature. They also observed clear shear thinning at all concentrations of CNT, which indicates nanofluids can offer better fluid flow performance due to the higher shear rate at the wall resulted in low viscosity. Prasher et al. [8]measured viscosity of Al2O3/water based nanofluid and reportedNewtonian behavior of the nanofluid. Their experimental data conform that viscosity increases withincreasing particle volume fraction. However they found contrary result that viscosity is independent of temperature. Wen and Ding [9] reported 20 % increase in the effective viscosity for TiO2 (34 nm) / water based nanofluid with 2.4 weight % particle loading and recorded much higher viscosity increase under low shear rate condition of 25- 100 1/S. Murshed et al.[10] reported nearly 82% increase in the viscosity of Al2O3(80 nm) and TiO2 (27nm)/Di water based nanofluid for the 5 % maximum volumetric loading. Similar increment (86%) of the effective viscosity was observed by Wang at al.[1] for same nanofluid. They also measured viscosity of TiO2 (27nm) / DI water based nanofluid, reported higher viscosity than those of Masuda et al. [2] who recorded 60% increase in the viscosity of water at a volumetric loading of 4.3 %. Kang et al. [11] measured viscosity of different nanofluids like ultra dispersed diamond/EG, silver/water and silica /water and reported 50%, 30% and 20% increment in the viscosity for UDD/EG, silver/water and silica/water nanofluids with the particle concentration of 1%, 2% and 3 % respectively. Nguyen et al. [12] studied the effect of temperature and particle volume concentration on the dynamic viscosity of Al2O3/water nanofluid. They concluded that dynamic viscosity of the nanofluid is function of particle loading and temperature. They criticize the use of nanofluid as a heat transfer fluid as beyond critical temperature, the properties of particle suspension seem to be varied. Xie et al. [13]compared the increment in viscosity of Al2O3 /EG and Al2O3 /Water nanofluid and showed that increment in the viscosity of EG based nanofluids is smaller than those of water based nanofluids which shows the effect of base fluid properties on the nanofluids. They also examined the effect of pH value on the viscosity of nanofluid and found increment in the viscosity due to coagulation of nanoparticles when pH value is close to IEP. Riehl [14] carried out an experimental work to measure density of Nikel-water nanofluid. He observed an increasing the density near 3.2% and 4.7% for particle concentration increasing from 3.5% to 5%. Shelton et al. [15]used molecular dynamic simulation to investigate the local density of surrounding xenon base fluid with platinum nanoparticles. They considered lognormal size distribution and agglomeration of nanoparticles over the range of nanoparticles diameters (25 – 150nm).The radial distribution function showed an increase in the local fluid density. This increase in local density was shown to be caused by the formation of liquid layers that surround the nanoparticle. There are a few theoretical models reported in the published literature to approximate nanofluid viscosities. All these relations based on the original work of Einstein [4], which is based on the assumption of a linearly viscous fluid containing a dilute, suspension of spherical particles. Einstein calculated the energy dissipated by the fluid flow around a single particle and from the work required for moving a particle relatively to the surrounding fluid, he found that, _ = _
/ _
= 1 + 2.5∅
(1)
This relation is found to be applicable for relatively low particle volume fraction,∅ < 2%, beyond this it underestimates the effective viscosity. For moderate particle concentration, Brinkman [16] proposed the relation for relative viscosity as :
Durgeshkumar Chavan and Ashok Pise / Materials Today: Proceedings 16 (2019) 504–515
_
= 1/〖(1 − ∅)〗^2.5
/ _
507
(2)
The formula proposed by the Frankel and Acrivos [17] for the relative viscosity as: _
/ _
= 9/8 [(∅ ⁄ ∅_
)^(1 ⁄ 3)/(1 − (∅ ⁄ ∅_
)^(1 ⁄ 3) )]
(3)
where∅ is the experimental value for the maximum particle volume fraction. Lundgren [18] use Taylor series in to estimate effective viscosity as: _
/ _
= 1 + 2.5∅ + 25/4 ∅^2 + 0(∅^3 )
(4)
Clearly, when higher terms of higher power of are neglected, it reduces to Einstein equation. By considering the effect due to the Brownian motion of particles on the bulk stress of an approximately isotropic suspension of rigid and spherical particles, Batchelor [19] proposed the following formula: _
/ _
= 1 + 2.5∅ + 6.5 ∅^2
(5)
Nguyen et al [12] found that the conditional formulas as discussed above underestimate the relative viscosity even at low particle volume concentration and for Al2O3 /water nanofluid suggested two correlations as: _
/ _
_
= 0.904 ^0.4835 (for 47 nm Al2O3)
/ _
= 1 + 0.025∅ + 0.015 ∅^2 (for 36 nm Al2O3)
(6) (7)
Other than the particle volume fraction, temperature is another important factor which influences the viscosity of nanofluids. There are limited researches about the dependence of viscosity on temperature. Ghadimi et al. [20] suggested two formulas for relative viscosity of Al2O3/water and Cuo/Water nanofluids as: _ _
/ _ / _
= 1.1250 − 0.0007 × = 2.1275 − 0.0215 ×
(8) + 0.0002 × ^2
(9)
Using mixture formula, the density of the nanofluid can be estimated as: _
= (1 − ∅) _ + ∅ _
(10)
3. Nanofluid Preparation Nanofluids are prepared by selecting three types of nanoparticles and two types of base fluids. The quality of the nanoparticles is very important for obtaining the stable nanofluid by dispersing it into a base fluid. The nanoparticles were examined using (i) Scanning electron microscope and (ii) X – ray diffraction machine. The Scanning electron microscopy gives information of particle size distribution, which is normally represented in terms of a mean diameter and a standard deviation. X – ray diffraction (XRD) technique is used to determine the phase composition and phase purity. The SEM images and XRD pattern of Al2O3 nanoparticlesis shown in Fig.01. The SEM image of selected nanoparticles confirms that nano-particles are of reported size and present without agglomeration before disperse in the base fluid. The XRD of the selected nanoparticles were compared with the standard XRD patterns to find the phase composition and purity, impurities present. For comparison, the Xperthighscore software is used.
The comparison between XRD of selected nanoparticles and standard XRD provided by Xperthighscore
software shows that intensity peak matches with standard XRD peak. Therefore nanoparticles used for nanofluid preparation have purity more than 90 %.
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For preparation of the nanofluids, various equipments such as magnetic stirrer, ultrasonic bath Sonicator and pH meter are used. The two step method is used for nanofluid preparation. The clustering of the nanoparticles is avoided to get a stable nanofluid. This is done by inducing surface charge on to the particles by adjusting the pH value of the base fluid. The pH value of the base fluid is adjusted in such a way that pH value is well away from the isoelectic point (IEP) of the nanoparticles. Iso-electic point is pH value at which the particular molecules carries no net electric charge. IEP value of Al2O3, TiO2 and SiO2 is 9.4, 5.8 and 2.3 respectively. Therefore, during preparation of
(2 0 0)
nanofluids using these nanoparticles, pH value is adjusted at about 6.4, 8.6 and 5.3 respectively.
2.4
(2 2 0)
Intensity (a.u.)
2.2 2.0 1.8 1.6 1.4 1.2 1.0 20
(a) SEM images with 20 kx
40
2degree)
60
80
(b) XRD plot Fig. 1. SEM image and XRD plot for Al2O3 nanoparticles
After preparing the stable nanofluid samples of various concentration (vol.% concentration), the dynamic viscosity is measured with rheometer whereas the density is measured with density meter, both are of Anton Parr make. 4. Viscosity Measurement The viscosity of the fluids is measured by viscometers working on different principles. As nanofluids is a fluid with dispersion of nano-sized solid particles in base fluid, rheometer will be the best choice to measure viscosity of nanofluids compared to viscometers.A rheometer is a laboratory device used to measure the way in which a liquid, suspension or slurry flows in response to applied forces. It is used for those fluids which cannot be defined by a single value of viscosity and therefore require more parameters to be set and measured than is the case for a viscometer. It measures the rheology of the fluid. The schematic diagram of Rheometer is as shown in Fig. 02 (a) In the present research work, the dynamic viscosity of different nanofluids is measured using rotational rheometer from Anton Parr. The equipment consisted of MCR 52 viscometer with concentric cylinder measurement system. The liquid is placed within the annulus of one cylinder inside another. One of the cylinders is rotated at a set speed. This determines shear rate inside the annulus. The liquid tends to drag the other cylinder round, and the force it exerts on that cylinder (torque) is measured, which can be converted to a shear stress. The photograph of MCR 52 rheometer is shown in Fig. 02 (b). To determine the dynamic viscosity of nanofluids at different temperatures, the shear rate was set to 500 1/S. The nanofluids temperature varied from 20 to 700C in 10 minutes. The temperature variation is done with the help of automatic temperature controller. The rheometer took 30 measuring points with the interval of 20 seconds. Similarly to
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determine the rheology of the fluid, the shear rate was set to increase from 0 to 500 1/S in the duration of 300 sec. The rheometer took 15 measuring points with the interval of 20 seconds. The fluid was kept constant at 30 0C with automatic temperature control from the rheometer.
(a)
Basic Principle of Rheometer work
(b) Rheometer Model MCR 52 Fig. 2: Rheometer Model MCR 52 from Anton Parr.
5. Density Measurement In the present research work, the density of different nanofluids is measured using density meter (DMA 5000) from Anton Parr. The Measuring range of the DMA 5000 is 0 to 3 gm/cm3 with accuracy of 0.0001 g/cm3. The photograph of Density meter is as shown in Fig. 03. The instrument use the principle of the U shaped vibration tube to measure density of the fluid. The working principle of an oscillation-type density meter is based on law of harmonic oscillation, in which a U tube is completely filled with the sample to be analyzed, and subjected electromagnetic force. The measurement of the frequency and duration of vibration of the tube filled with the sample, allows the determination of density valve of sample. The measuring principle is based on the Mass-Spring Model.
Fig. 3.Density Meter DMA 5000 from Anton Parr.
Fig. 4. Basic Principle of Density Measurement
Principle of Operation The working principle of an oscillation-type density meter (Fig 04) is based on law of harmonic oscillation, in which a U tube is completely filled with the sample to be analyzed, and subjected electromagnetic force. The measurement of the frequency and duration of vibration of the tube filled with the sample, allows the determination of density valve of sample. The measuring principle is based on the Mass-Spring Model.
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6. Results and Discussion The prepared nanofluids were tested for dynamic viscosity and density using Rheometer and density meter of Anton Parr make. The results obtained were analyzed and presented as below. 6.1 Dynamic Viscosity The dynamic viscosity measurement is carried out with 500 1/S shear rate applied for 10 minutes with changing temperature from 300C to 700C. The effect of nanoparticles volumetric concentration, temperature and shear rate is investigated and presented as below. 6.1.1 Effect of concentration and temperature: Fig. 5 (a) and 5 (b) shows the relative viscosity of Al2O3/water nanofluids and TiO2/Water nanofluid respectively for different nanoparticle volumetric concentration measured in the temperature range of 300C to 700C. Measurements clearly show increase in the dynamic viscosity of the nanofluid with the addition of the nanoparticles. Also the general trend of reduction in the viscosity with increase in the temperature is observed, as viscosity of base fluid reduces with increase in the temperature. For Al2O3/water nanofluids, increase in the viscosity of nanofluid is 4.25 to 15.5 % with nanoparticle volumetric loading of 0.1% to 1.0% at 300C. With increase in the temperature from 30 to 700C, the viscosity of the nanofluids reduces almost to its half value at 300C. For TiO2/Water nanofluid, at 300C, viscosity increases by 5.65 to 16% with 0.1 to 1.0% addition of nanoparticles in the base fluid. With increase in temperature from 300C to 700C, the viscosity of nanofluid reduces to almost half to that of viscosity of nanofluids at 300C. Compared with Al2O3/water nanofluid, the enhancement in relative dynamic viscosity with concentration is more for TiO2/water nanofluid. But the reduction in the relative dynamic viscosity of both nanofluids is almost same with increase in the temperature of nanofluid. Fig. 6 (a) and (b) presents relative viscosity for SiO2/Water and SiO2/EG nanofluid respectively as a function of Vol.%nano-particle concentration and temperature. The increment in the viscosity of SiO2/water nanofluids is from 2.34% to 13.7% for addition of 0.1 % to 1.0 vol. % nanoparticle concentration.The relative dynamic viscosity of the ethylene based nanofluid changers from 1.5% to 1.7% only with addition of 0.1 to 1.0 vol.% nanoparticles in the base fluid. This may be due to the fact that viscosity of ethylene glycol is high which affect slightly with addition of small amount of nanoparticles.
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0
30 C 0 60 C
1.16
0
511
0
40 C 0 70 C
50 C 0
0
30 C 0 60 C
1.16
0
40 C 0 70 C
50 C
Relative Dy. Viscosity (nf/bf)
Relative Dy. Viscosity (nf/bf)
1.14 1.12 1.10 1.08 1.06 1.04 1.02
1.14 1.12 1.10 1.08 1.06 1.04
0.0
0.2
0.4
0.6
0.8
1.0
0.0
0.2
Concentration (vol%)
(a)
0.4
0.6
0.8
1.0
Concentration (vol.%)
Al2O3 (30 nm)/Water
(b) TiO2 (30 nm)/Water
Fig. 05: Effect on Relative Dynamic Viscosity with Concentration for different Tempt.
Temperature makes higher effect on the dynamic viscosity of this nanofluid where dynamic viscosity reduces almost two times in the range of 300C to 700C.Comparing the relative dynamic viscosities of the tested nanofluids, all nanofluids show enhancement in the viscosity with increase in nanoparticle concentration. The temperature dependant behavior is same for all nanofluids. The Al2O3/ water nanofluid is most useful as it gives less increase in dynamic viscosity and more reduction at higher temperature. 1.16 1.16
0
30 C 0 60 C
0
30 C 0 60 C
0
50 C
1.14
Relative Dy. Viscosity (nf/bf)
Relative Dy. Viscosity (nf/bf)
1.14
0
40 C 0 70 C
1.12 1.10 1.08 1.06 1.04 1.02
0
0
40 C 0 70 C
50 C
1.12 1.10 1.08 1.06 1.04 1.02
1.00 0.0
0.2
0.4
0.6
0.8
1.0
0.0
(a) SiO2 (30 nm)/Water
0.2
0.4
0.6
0.8
1.0
Concentration (Vol.%)
Concentration (vol.%)
(b) SiO2 (30 nm)/Water
Fig.6 Effect on Relative Dynamic Viscosity with Concentration for different Tempt.
6.1.2 Effect of Shear Rate: Figure 07(a) and (b) shows the effect of shear rate on the viscosity of the Al2O3/water and SiO2/EG nanofluids respectively. The rheological measurement shows that Al2O3/water and SiO2/EG nanofluids not shows remarkable shear thing over the shear range of 0.1 to 500 1/S. Fig 7 (a) and (b) shows shear viscosity as a function of shear rate for particle volume loading from 0.1 to 1.0%. Results clearly indicates that shear viscosity almost remains constant over the over entire range of shear rate. This shows the Newtonian behavior of the tested nanofluids with nanoparticle addition of < 1vol.%. With increase in nanoparticle loading (> 4 vol.%), the nanofluids may show the shear thing
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considerably. The nanofluids with carbon nanotubes generally shows shear thing with very small addition of carbon nanotubes. 6.2 Density Figure 08 shows the shear stress v/s shear strain curve for the two nanofluids namely Al2O3/water and SiO2/EG nanofluids. The nanoparticle concentration for both the fluids is 1.0 vol.% and the test is carried out at 30 0C. It is reported from the Fig.3.31, that shear stress increases almost linearly with increase in the shear strain. For Al2O3/Water nanofluid, the increment is steep as compared to the SiO2/EG nanofluid. This indicates the Newtonian behavior of the nanofluids. This indicates that increment in viscosity of Al2O3/water nanofluid is more compared with the increment in viscosity of SiO2/EG nanofluid at same volume concentration and at same temperature.
0.1% 0.7%
0.00098
0.3% 1.0%
0.5
0.1% 0.7%
0.0178
0.3% 1.0%
0.5
0.0176 0.00096
0.0172
Dy. Viscosity (nf)
Dy. Viscosity (nf)
0.0174 0.00094
0.00092
0.00090
0.00088
0.0170 0.0168 0.0166 0.0164 0.0162 0.0160
0.00086 0
100
200
300
400
0
500
100
200
Shear Rate (1/S)
(a)
300
400
500
Shear Rate (1/S)
Al2O3/water
(b) SiO2/EG
Fig .07 Effect on Relative Dynamic Viscosity with Shear Rate
Al2O3/Water
9
0.1 % 0.7 %
SiO2/EG
8
0.3 % 1.0 %
0.5 %
1.025
Relative Density (nf/bf)
2
Shear Stress (N/m )
7 6 5 4 3 2
1.020
1.015
1.010
1.005
1 0
1.000
0
100
200
300
Shear Strain (1/S)
400
500
30
40
50
Fig. 08: Comparison of Shearing
Fig. 9: Effect of Temperature
Behavior of nanofluids.
[Al2O3 (30 nm)/water]
[Al2O3/water and SiO2/EG]
60 0
Temperature C
70
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As fluid density plays important role in controlling many industrial processes, it is essential to investigate the effect of vol.% concentration of nanoparticles on the density of the nanofluid. The density of prepared nanofluids is measured using density meter (DMA 5000) from Anton Parr and results are presented as below: 6.2.1 Effect of Concentration and temperature The density results of all concentrations of Al2O3 nanofluid within the temperature range of 30 – 700C are summarized in the Fig 09. It is observed that the density increases with increase in the nanoparticle loading. At 30 0C, the variation in the density of Al2O3/water nanofluid compared with water is from 0.145% to 2.6% in the range of 0.1 to 1.0 vol.% of nanoparticle loading respectively, whereas at 700C, density variation is from 0.009% to 0.024% in the same range of nanoparticle concentration. The general observation is that density of nanofluid decreases with increase in the temperature which agrees well with the acceptable behavior of the fluids. 6.2.2. Comparison with Existing Correlations The measured value for the density of Al2O3/water nanofluid at 300C is compared with the Pak and Cho [3] equation in Fig. 10. Excellent agreement between measured values and the Pak and Cho equation is observed. The maximum variation between the measured values and values by Pak and Cho is 0.08 %. From this comparison, one can use the mixing formula used by Pak and Choi, for estimation of density of nanofluid with reasonable accuracy.
Density by Pak & Choi Experimental Value
1030
1.030
TiO2/Water
SiO3/Water
SiO2/EG
1.025
Relative Density (Rhonf/Rhobf)
1025
1020 3
Density (kg/m )
Al2O3/Water
1015
1010
1005
1000 0.0
0.2
0.4
0.6
0.8
1.015
1.010
1.005
1.000 0.0
1.0
0.2
0.4
0.6
0.8
1.0
% Volume Concentration
Volume Concentration
Fig. 10: Comparison between measured and estimated value by Pak and Choi [38]
1.020
Fig. 11 Comparison of Relative Densities
with different nanoparticles at 300C [Al2O3 (30 nm)/water]
6.2.3 Effect of Different Nanoparticles Fig. 11 shows the relative density of Al2O3/Water, TiO2/Water, SiO2/Water and SiO2/EG nanofluids at different nanoparticle concentration loading at 300C. The variation in the density of TiO2/water nanofluid compared with water is from 0.0822% to 2.6% in the range of 0.1 to 1.0 vol.% of nanoparticle loading respectively. For SiO2/Water nanofluid, the variation in the density is in the range of 0.0802 to 1.25% whereas for SiO2/EG nanofluid, density variation is in the range of 0.625% to 0.954 %.respectively in the same range of nanoparticle loading. From the density values obtained from measurement, it is observed that the mixture formula is gives good estimation for the density of nanofluids. The density of the nanofluids mainly depends on the densities of the nanoparticles and base fluids. The effect of nanoscale size of the particles, does not affect the effective density of the nanofluid.
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6.3. Uncertainty Analysis: The uncertainties in the measurement of viscosity and density of nanofluids were calculated considering different parameters. The viscosity of nanofluid is measured with MCR -52 rheometer. The minimum torque that can be applied by rheometer is 200 µNm. Thus the error involved in the measurement of torque is ±1.79%. The angular speed of the rheometer spindle is measured with least count of 10-3 rad/sec. This results in error involved in angular speed measurement as ±0.5.58%. As dynamic viscosity measurement involves shear stress and shear strain, the uncertainty in the dynamic viscosity is 3.11%. The density is measured with Density meter with the least count of 0.001 gm/cm3. Thus the error involved in the measurement of density is ±2.34 %.
6.4 Correlations Suggested Based on Measurement Result: Based on the measurement results of dynamic viscosity of the nanofluids, experimental correlations are suggested by many researchers. These correlations are relates the relative thermo-physical properties of nanofluids with percentage volume fraction of nanoparticles and temperatures. Based on the experimental results obtained for dynamic viscosity some experimental correlations are proposed for dilute nanofluids (volume concentration < 1.0%).. The correlations are developed by regression analysis with confidence level of 95%. For density of the nanofluids, the mixture formula gives good agreement with experimental results; hence the correlation for specific density of the nanofluid is not suggested. _
/ _
= 1.027615 + 12.2255 ∅
(3.14)
_
/ _
= 1.4868 ∅^0.033441 ^(−0.03684)
(3.15)
7. Conclusion With the experimental measurement of viscosity and density of nanofluids using different nanoparticles and base fluids with varying nanoparticles concentration, following conclusions can be drawn: i.
The viscosity of the nanofluid, increase with increase in the particle volume concentration of nanofluid. This results in increase in the pressure drop in the thermal system which has adverse effect on the use of nanofluid. For TiO2/water nanofluid with 1.0 vol. %maximum increment of 16 % in viscosity is observed at 300C .
ii. The effect of increased viscosity becomes negligible at higher temperature as viscosity of nanofluid reduces with increase in the temperature of the nanofluid. The increment in viscosity of Al2O3/water nanofluid with 1.0 vol. % at 300C is 15.5% which reduces to 8% at 700C. iii. The increase in the viscosity of nanofluid differs with different base fluids. For SiO2/water and SiO2/EG, enhancement is 14% and 12% with 1.0 vol.5 at 700C. iv. The classical formulas for viscosity of nanofluid under predict the enhancement in the viscosity with increase in nanoparticle volume concentration. v.
The density of the nanofluid increases with increase in the nanoparticles concentration, and slightly decreases with increase in the temperature.
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vi. Increment in the density with particles concentration of 1.0 vol% is 2.6%, 2.6%, 1.25 % and 0.954% at 300C for Al2O3/water, TiO2/water, SiO2/water and SiO2/EG nanofluids respectively. vii. The mixture formula shows good agreement to predict the density of nanofluid.
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Wang B. X., Zhou L. P; Peng X. F, International Journal of Heat and Mass Transfer 46 (2003) 2665–2672. Masuda H., Ebata A., Teramae K., Hishinuma N., NetsuBussei 4 (1993) 227–233 (in Japanese). Pak B. C., Cho Y. I., Experimental Heat Transfer 11 (1998) 151–170. Einstein A., Dover Publications, Inc., New York, 1956. Das S. K., Putra N., RoetzelW, International Journal of Heat and Mass Transfer 46 (2003) 851–862. Putra N., Roetzel W., Das S. K., Heat and Mass Transfer 39 (2003) 775–784. Ding Y., Alias H., Wen D., Williams A.R International Journal of Heat and Mass Transfer 49 (2006) 240–250. Prasher R., Song D., Wang J., Phelan P. E, Applied Physics Letters 89 (2006) 133108-1–133108-3. Wen D., Ding Y.IEEE Transactions on Nanotechnology 5 (2006) 220–227. Murshed S.M. S., Leong K. C., Yang C., International Journal of Thermal Sciences 44 (2005) 367–373. Kang H. U., Kim S. H., Oh J. M.Exp. Heat Transfer 19 (2006) 181–191. Nguyen C.T., DesgrangesF, Galanis N., Roy G., Mare T., Boucher S., H. Angue, S. Mintsa, Int J. Therm. Sci. 47 (2) (2008) 103–111. Xie H., Chen L., Wu Q. High Temp. – High Press. 37 (2008) 127–135 Riehl R. R.,Heat Powered Cycles International Conference (HPC) UK 06102 (2006). Shelton John, PyrtleFrankASME 2010 8th International Conference on Nanochannels, Microchannels, and Minichannels: Parts A and B, (2010). Brinkman H. C., J.Chem. Phys. 20 (4) (1952) 571.N.A. Frankel, AcrivosA. Chem. Eng. Sci. 22 (6) (1967) 847–853. Lundgren T.S., J. Fluid Mech. 51 (02) (1972) 273–299. Batchelor G. K., J. Fluid Mech. 83 (01) (1977) 97–117. Ghadimi A., Saidur R., Metselaar H. S. C.International Journal of Heat and Mass Transfer, 54 (2011) 4051–4068.
ScienceDirect Materials Today: Proceedings 16 (2019) 504–515
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ICAMMAS17
Experimental Investigation of Effective Viscosity and Density of Nanofluids. Durgeshkumar Chavana, Dr. Ashok Piseb. b
aHead of Department, Mechanical Engg. Government Polytechnic, Ambad Dist. Jalna- 431204 Professor, Mechanical Engg. Government College of Engineering, KaradDistSatara, India – 415110
Abstract In the present research work, the effect of nanoparticles volume concentration and the temperature on the effective viscosity and the density of nanofluids were investigated. The stable nanofluids using different base fluids and nanoparticles with varying nanoparticles concentration were prepared. The Rheometer and density meter (Anton Parr Make) were used for the measurement of viscosity and density of nanofluids. The experimental results clearly shows that the viscosity of nanofluid, increase with increase in particle volume concentration and decreases with increase in temperature of nanofluids. The increment in viscosity differs with different base fluids. The classical formulas for viscosity under predict the viscosity enhancement. Experimental data for density of nanofluids shows increase in density with increase in nanoparticles concentration. The temperature has negligible effect on the density of nanofluid. The mixture formula shows good agreement to predict the density of nanofluid. ©2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Advances in Materials, Manufacturing and Applied Sciences. Keywords: Effective viscosity, density, nanofluid, base fluid, rheometer
1.
Introduction Heating or cooling fluids such as water, engine oil and ethylene glycol plays a crucial role in thermal
management of high-tech industries but they have poor thermal characteristics, in particular thermal conductivity. Despite considerable efforts to improve the rate of heat transfer by usage of extended surfaces, mini-channels and micro-channels, further enhancement in heating and cooling rate is always in demand. With ever increasing thermal loads due to high power output and smaller features of microelectronics devices, improvement to make heat transfer equipment more energy efficient become most important technical issue. The thermal management of many applications like transportation, manufacturing and micro-electronics is very important, to maintain their desired performance and durability.
* Corresponding author. Tel.:+91-9970700780; fax:+91-2483275010 E-mailaddress:[email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Advances in Materials, Manufacturing and Applied Sciences
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The improvement to make heat transfer equipment more energy efficient can be made by focus on reduces the size on one hand and huge increase in heat flux on the other. Heat transfer fluids such as water, mineral oil and ethylene glycol are used in many industrial processes. The poor heat transfer properties of these common fluids compared to most solids is a primary obstacle to the high compactness and effectiveness of heat exchangers. As the thermal conductivity of a fluid plays a vital role in the development of energy efficient heat transfer equipment, there is need to find new heat transfer fluid with has higher thermal properties and an advanced cooling techniques. With enhancement in nanotechnology, manufacturing solid particles down to the nanometer scale becomes easier, a new class of heat transfer fluid called Nanofluids can be developed. Nanofluid is heat transfer fluid in which nanometer sized solid particles are dispersed in traditional heat transfer fluid. These fluids have their potential benefits like higher heat conduction, large relative surface area, excellent stability and minimal clogging Along with thermal conductivity, viscosity is important property of the heat transfer fluid that needs to be investigated as pumping power required for circulation of working fluid and pressure drop across the thermal system are directly related to viscosity. The viscosity of nanofluid depends on nano-particle loading and the temperature. Some researchers reported that viscosity of nanofluid is temperature independent. With dilute volume concentration, nanofluids show Newtonian behavior. Very limited literature is available on the effect of temperature on viscosity of nanofluids. Density plays very important role in heat transfer especially in natural convection. As natural convection affected by the buoyancy force and density gradient, accurate determination of the density of nanofluids is very important in the heat transfer applications using nanofluids. 2. Experimental and Theoretical Studies Review In the design of thermal systems, viscosity and the density of the working fluid plays the vital role. In comparison with the study of thermal conductivity of nanofluids, very few studies were reported on the effective viscosity and the density of the nanofluids. The experimental and theoretical models developed for effective viscosity and density are discussed as below. Wang et al. [1]used mechanical blending technique for nanofluid preparation and measure effective viscosity of Al2O3 (28 nm)/ DI water nanofluid. They reported about 86% increment in the effective viscosity for a 5 vol.%of nanoparticles and an increase of 40 % in viscosity of Al2O3/ethylene glycol base nanofluid at a volumetric loading of 3.5%. Masuda et al. [2]recorded 60% increase in the viscosity of water at a volumetric loading of 4.3 vol. % loading of TiO2(27 nm) nanoparticles. Pak and Cho [3]observed several times increment in the viscosity of water with 10 vol.% addition of Al2O3 (13 nm) and TiO2 (27 nm) nanoparticles. They concluded that the large increment in viscosity may be due to differences in dispersion techniques and size of the particles. They apply an electronic repulsion technique and adjusted pH values, and found that viscosity of nanofluids depends on the methods used to disperse and stabilize the nanoparticles suspension. The experimental obtained were significantly larger than the prediction from classical model of Einstein [4]. The effect of shear rate on the viscosity of Al2O3/water and CuO/water-based nanofluids was studied by Das et al. [5] and Putra et al. [6]andreported Newtonian behavior of the nanofluids for a range of volume percentage between 1% and 4%. Das et al.[5] also observed an increase in viscosity with an increase of particle volume fraction
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for Al2O3/water based nanofluids. Ding et al. [7] experimented effect of particle loading and temperature on viscosity of nanofluid at a given shear rate and observe increase in viscosity of nanofluids with increase in CNT concentration and decreasing temperature. They also observed clear shear thinning at all concentrations of CNT, which indicates nanofluids can offer better fluid flow performance due to the higher shear rate at the wall resulted in low viscosity. Prasher et al. [8]measured viscosity of Al2O3/water based nanofluid and reportedNewtonian behavior of the nanofluid. Their experimental data conform that viscosity increases withincreasing particle volume fraction. However they found contrary result that viscosity is independent of temperature. Wen and Ding [9] reported 20 % increase in the effective viscosity for TiO2 (34 nm) / water based nanofluid with 2.4 weight % particle loading and recorded much higher viscosity increase under low shear rate condition of 25- 100 1/S. Murshed et al.[10] reported nearly 82% increase in the viscosity of Al2O3(80 nm) and TiO2 (27nm)/Di water based nanofluid for the 5 % maximum volumetric loading. Similar increment (86%) of the effective viscosity was observed by Wang at al.[1] for same nanofluid. They also measured viscosity of TiO2 (27nm) / DI water based nanofluid, reported higher viscosity than those of Masuda et al. [2] who recorded 60% increase in the viscosity of water at a volumetric loading of 4.3 %. Kang et al. [11] measured viscosity of different nanofluids like ultra dispersed diamond/EG, silver/water and silica /water and reported 50%, 30% and 20% increment in the viscosity for UDD/EG, silver/water and silica/water nanofluids with the particle concentration of 1%, 2% and 3 % respectively. Nguyen et al. [12] studied the effect of temperature and particle volume concentration on the dynamic viscosity of Al2O3/water nanofluid. They concluded that dynamic viscosity of the nanofluid is function of particle loading and temperature. They criticize the use of nanofluid as a heat transfer fluid as beyond critical temperature, the properties of particle suspension seem to be varied. Xie et al. [13]compared the increment in viscosity of Al2O3 /EG and Al2O3 /Water nanofluid and showed that increment in the viscosity of EG based nanofluids is smaller than those of water based nanofluids which shows the effect of base fluid properties on the nanofluids. They also examined the effect of pH value on the viscosity of nanofluid and found increment in the viscosity due to coagulation of nanoparticles when pH value is close to IEP. Riehl [14] carried out an experimental work to measure density of Nikel-water nanofluid. He observed an increasing the density near 3.2% and 4.7% for particle concentration increasing from 3.5% to 5%. Shelton et al. [15]used molecular dynamic simulation to investigate the local density of surrounding xenon base fluid with platinum nanoparticles. They considered lognormal size distribution and agglomeration of nanoparticles over the range of nanoparticles diameters (25 – 150nm).The radial distribution function showed an increase in the local fluid density. This increase in local density was shown to be caused by the formation of liquid layers that surround the nanoparticle. There are a few theoretical models reported in the published literature to approximate nanofluid viscosities. All these relations based on the original work of Einstein [4], which is based on the assumption of a linearly viscous fluid containing a dilute, suspension of spherical particles. Einstein calculated the energy dissipated by the fluid flow around a single particle and from the work required for moving a particle relatively to the surrounding fluid, he found that, _ = _
/ _
= 1 + 2.5∅
(1)
This relation is found to be applicable for relatively low particle volume fraction,∅ < 2%, beyond this it underestimates the effective viscosity. For moderate particle concentration, Brinkman [16] proposed the relation for relative viscosity as :
Durgeshkumar Chavan and Ashok Pise / Materials Today: Proceedings 16 (2019) 504–515
_
= 1/〖(1 − ∅)〗^2.5
/ _
507
(2)
The formula proposed by the Frankel and Acrivos [17] for the relative viscosity as: _
/ _
= 9/8 [(∅ ⁄ ∅_
)^(1 ⁄ 3)/(1 − (∅ ⁄ ∅_
)^(1 ⁄ 3) )]
(3)
where∅ is the experimental value for the maximum particle volume fraction. Lundgren [18] use Taylor series in to estimate effective viscosity as: _
/ _
= 1 + 2.5∅ + 25/4 ∅^2 + 0(∅^3 )
(4)
Clearly, when higher terms of higher power of are neglected, it reduces to Einstein equation. By considering the effect due to the Brownian motion of particles on the bulk stress of an approximately isotropic suspension of rigid and spherical particles, Batchelor [19] proposed the following formula: _
/ _
= 1 + 2.5∅ + 6.5 ∅^2
(5)
Nguyen et al [12] found that the conditional formulas as discussed above underestimate the relative viscosity even at low particle volume concentration and for Al2O3 /water nanofluid suggested two correlations as: _
/ _
_
= 0.904 ^0.4835 (for 47 nm Al2O3)
/ _
= 1 + 0.025∅ + 0.015 ∅^2 (for 36 nm Al2O3)
(6) (7)
Other than the particle volume fraction, temperature is another important factor which influences the viscosity of nanofluids. There are limited researches about the dependence of viscosity on temperature. Ghadimi et al. [20] suggested two formulas for relative viscosity of Al2O3/water and Cuo/Water nanofluids as: _ _
/ _ / _
= 1.1250 − 0.0007 × = 2.1275 − 0.0215 ×
(8) + 0.0002 × ^2
(9)
Using mixture formula, the density of the nanofluid can be estimated as: _
= (1 − ∅) _ + ∅ _
(10)
3. Nanofluid Preparation Nanofluids are prepared by selecting three types of nanoparticles and two types of base fluids. The quality of the nanoparticles is very important for obtaining the stable nanofluid by dispersing it into a base fluid. The nanoparticles were examined using (i) Scanning electron microscope and (ii) X – ray diffraction machine. The Scanning electron microscopy gives information of particle size distribution, which is normally represented in terms of a mean diameter and a standard deviation. X – ray diffraction (XRD) technique is used to determine the phase composition and phase purity. The SEM images and XRD pattern of Al2O3 nanoparticlesis shown in Fig.01. The SEM image of selected nanoparticles confirms that nano-particles are of reported size and present without agglomeration before disperse in the base fluid. The XRD of the selected nanoparticles were compared with the standard XRD patterns to find the phase composition and purity, impurities present. For comparison, the Xperthighscore software is used.
The comparison between XRD of selected nanoparticles and standard XRD provided by Xperthighscore
software shows that intensity peak matches with standard XRD peak. Therefore nanoparticles used for nanofluid preparation have purity more than 90 %.
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For preparation of the nanofluids, various equipments such as magnetic stirrer, ultrasonic bath Sonicator and pH meter are used. The two step method is used for nanofluid preparation. The clustering of the nanoparticles is avoided to get a stable nanofluid. This is done by inducing surface charge on to the particles by adjusting the pH value of the base fluid. The pH value of the base fluid is adjusted in such a way that pH value is well away from the isoelectic point (IEP) of the nanoparticles. Iso-electic point is pH value at which the particular molecules carries no net electric charge. IEP value of Al2O3, TiO2 and SiO2 is 9.4, 5.8 and 2.3 respectively. Therefore, during preparation of
(2 0 0)
nanofluids using these nanoparticles, pH value is adjusted at about 6.4, 8.6 and 5.3 respectively.
2.4
(2 2 0)
Intensity (a.u.)
2.2 2.0 1.8 1.6 1.4 1.2 1.0 20
(a) SEM images with 20 kx
40
2degree)
60
80
(b) XRD plot Fig. 1. SEM image and XRD plot for Al2O3 nanoparticles
After preparing the stable nanofluid samples of various concentration (vol.% concentration), the dynamic viscosity is measured with rheometer whereas the density is measured with density meter, both are of Anton Parr make. 4. Viscosity Measurement The viscosity of the fluids is measured by viscometers working on different principles. As nanofluids is a fluid with dispersion of nano-sized solid particles in base fluid, rheometer will be the best choice to measure viscosity of nanofluids compared to viscometers.A rheometer is a laboratory device used to measure the way in which a liquid, suspension or slurry flows in response to applied forces. It is used for those fluids which cannot be defined by a single value of viscosity and therefore require more parameters to be set and measured than is the case for a viscometer. It measures the rheology of the fluid. The schematic diagram of Rheometer is as shown in Fig. 02 (a) In the present research work, the dynamic viscosity of different nanofluids is measured using rotational rheometer from Anton Parr. The equipment consisted of MCR 52 viscometer with concentric cylinder measurement system. The liquid is placed within the annulus of one cylinder inside another. One of the cylinders is rotated at a set speed. This determines shear rate inside the annulus. The liquid tends to drag the other cylinder round, and the force it exerts on that cylinder (torque) is measured, which can be converted to a shear stress. The photograph of MCR 52 rheometer is shown in Fig. 02 (b). To determine the dynamic viscosity of nanofluids at different temperatures, the shear rate was set to 500 1/S. The nanofluids temperature varied from 20 to 700C in 10 minutes. The temperature variation is done with the help of automatic temperature controller. The rheometer took 30 measuring points with the interval of 20 seconds. Similarly to
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determine the rheology of the fluid, the shear rate was set to increase from 0 to 500 1/S in the duration of 300 sec. The rheometer took 15 measuring points with the interval of 20 seconds. The fluid was kept constant at 30 0C with automatic temperature control from the rheometer.
(a)
Basic Principle of Rheometer work
(b) Rheometer Model MCR 52 Fig. 2: Rheometer Model MCR 52 from Anton Parr.
5. Density Measurement In the present research work, the density of different nanofluids is measured using density meter (DMA 5000) from Anton Parr. The Measuring range of the DMA 5000 is 0 to 3 gm/cm3 with accuracy of 0.0001 g/cm3. The photograph of Density meter is as shown in Fig. 03. The instrument use the principle of the U shaped vibration tube to measure density of the fluid. The working principle of an oscillation-type density meter is based on law of harmonic oscillation, in which a U tube is completely filled with the sample to be analyzed, and subjected electromagnetic force. The measurement of the frequency and duration of vibration of the tube filled with the sample, allows the determination of density valve of sample. The measuring principle is based on the Mass-Spring Model.
Fig. 3.Density Meter DMA 5000 from Anton Parr.
Fig. 4. Basic Principle of Density Measurement
Principle of Operation The working principle of an oscillation-type density meter (Fig 04) is based on law of harmonic oscillation, in which a U tube is completely filled with the sample to be analyzed, and subjected electromagnetic force. The measurement of the frequency and duration of vibration of the tube filled with the sample, allows the determination of density valve of sample. The measuring principle is based on the Mass-Spring Model.
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6. Results and Discussion The prepared nanofluids were tested for dynamic viscosity and density using Rheometer and density meter of Anton Parr make. The results obtained were analyzed and presented as below. 6.1 Dynamic Viscosity The dynamic viscosity measurement is carried out with 500 1/S shear rate applied for 10 minutes with changing temperature from 300C to 700C. The effect of nanoparticles volumetric concentration, temperature and shear rate is investigated and presented as below. 6.1.1 Effect of concentration and temperature: Fig. 5 (a) and 5 (b) shows the relative viscosity of Al2O3/water nanofluids and TiO2/Water nanofluid respectively for different nanoparticle volumetric concentration measured in the temperature range of 300C to 700C. Measurements clearly show increase in the dynamic viscosity of the nanofluid with the addition of the nanoparticles. Also the general trend of reduction in the viscosity with increase in the temperature is observed, as viscosity of base fluid reduces with increase in the temperature. For Al2O3/water nanofluids, increase in the viscosity of nanofluid is 4.25 to 15.5 % with nanoparticle volumetric loading of 0.1% to 1.0% at 300C. With increase in the temperature from 30 to 700C, the viscosity of the nanofluids reduces almost to its half value at 300C. For TiO2/Water nanofluid, at 300C, viscosity increases by 5.65 to 16% with 0.1 to 1.0% addition of nanoparticles in the base fluid. With increase in temperature from 300C to 700C, the viscosity of nanofluid reduces to almost half to that of viscosity of nanofluids at 300C. Compared with Al2O3/water nanofluid, the enhancement in relative dynamic viscosity with concentration is more for TiO2/water nanofluid. But the reduction in the relative dynamic viscosity of both nanofluids is almost same with increase in the temperature of nanofluid. Fig. 6 (a) and (b) presents relative viscosity for SiO2/Water and SiO2/EG nanofluid respectively as a function of Vol.%nano-particle concentration and temperature. The increment in the viscosity of SiO2/water nanofluids is from 2.34% to 13.7% for addition of 0.1 % to 1.0 vol. % nanoparticle concentration.The relative dynamic viscosity of the ethylene based nanofluid changers from 1.5% to 1.7% only with addition of 0.1 to 1.0 vol.% nanoparticles in the base fluid. This may be due to the fact that viscosity of ethylene glycol is high which affect slightly with addition of small amount of nanoparticles.
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0
30 C 0 60 C
1.16
0
511
0
40 C 0 70 C
50 C 0
0
30 C 0 60 C
1.16
0
40 C 0 70 C
50 C
Relative Dy. Viscosity (nf/bf)
Relative Dy. Viscosity (nf/bf)
1.14 1.12 1.10 1.08 1.06 1.04 1.02
1.14 1.12 1.10 1.08 1.06 1.04
0.0
0.2
0.4
0.6
0.8
1.0
0.0
0.2
Concentration (vol%)
(a)
0.4
0.6
0.8
1.0
Concentration (vol.%)
Al2O3 (30 nm)/Water
(b) TiO2 (30 nm)/Water
Fig. 05: Effect on Relative Dynamic Viscosity with Concentration for different Tempt.
Temperature makes higher effect on the dynamic viscosity of this nanofluid where dynamic viscosity reduces almost two times in the range of 300C to 700C.Comparing the relative dynamic viscosities of the tested nanofluids, all nanofluids show enhancement in the viscosity with increase in nanoparticle concentration. The temperature dependant behavior is same for all nanofluids. The Al2O3/ water nanofluid is most useful as it gives less increase in dynamic viscosity and more reduction at higher temperature. 1.16 1.16
0
30 C 0 60 C
0
30 C 0 60 C
0
50 C
1.14
Relative Dy. Viscosity (nf/bf)
Relative Dy. Viscosity (nf/bf)
1.14
0
40 C 0 70 C
1.12 1.10 1.08 1.06 1.04 1.02
0
0
40 C 0 70 C
50 C
1.12 1.10 1.08 1.06 1.04 1.02
1.00 0.0
0.2
0.4
0.6
0.8
1.0
0.0
(a) SiO2 (30 nm)/Water
0.2
0.4
0.6
0.8
1.0
Concentration (Vol.%)
Concentration (vol.%)
(b) SiO2 (30 nm)/Water
Fig.6 Effect on Relative Dynamic Viscosity with Concentration for different Tempt.
6.1.2 Effect of Shear Rate: Figure 07(a) and (b) shows the effect of shear rate on the viscosity of the Al2O3/water and SiO2/EG nanofluids respectively. The rheological measurement shows that Al2O3/water and SiO2/EG nanofluids not shows remarkable shear thing over the shear range of 0.1 to 500 1/S. Fig 7 (a) and (b) shows shear viscosity as a function of shear rate for particle volume loading from 0.1 to 1.0%. Results clearly indicates that shear viscosity almost remains constant over the over entire range of shear rate. This shows the Newtonian behavior of the tested nanofluids with nanoparticle addition of < 1vol.%. With increase in nanoparticle loading (> 4 vol.%), the nanofluids may show the shear thing
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considerably. The nanofluids with carbon nanotubes generally shows shear thing with very small addition of carbon nanotubes. 6.2 Density Figure 08 shows the shear stress v/s shear strain curve for the two nanofluids namely Al2O3/water and SiO2/EG nanofluids. The nanoparticle concentration for both the fluids is 1.0 vol.% and the test is carried out at 30 0C. It is reported from the Fig.3.31, that shear stress increases almost linearly with increase in the shear strain. For Al2O3/Water nanofluid, the increment is steep as compared to the SiO2/EG nanofluid. This indicates the Newtonian behavior of the nanofluids. This indicates that increment in viscosity of Al2O3/water nanofluid is more compared with the increment in viscosity of SiO2/EG nanofluid at same volume concentration and at same temperature.
0.1% 0.7%
0.00098
0.3% 1.0%
0.5
0.1% 0.7%
0.0178
0.3% 1.0%
0.5
0.0176 0.00096
0.0172
Dy. Viscosity (nf)
Dy. Viscosity (nf)
0.0174 0.00094
0.00092
0.00090
0.00088
0.0170 0.0168 0.0166 0.0164 0.0162 0.0160
0.00086 0
100
200
300
400
0
500
100
200
Shear Rate (1/S)
(a)
300
400
500
Shear Rate (1/S)
Al2O3/water
(b) SiO2/EG
Fig .07 Effect on Relative Dynamic Viscosity with Shear Rate
Al2O3/Water
9
0.1 % 0.7 %
SiO2/EG
8
0.3 % 1.0 %
0.5 %
1.025
Relative Density (nf/bf)
2
Shear Stress (N/m )
7 6 5 4 3 2
1.020
1.015
1.010
1.005
1 0
1.000
0
100
200
300
Shear Strain (1/S)
400
500
30
40
50
Fig. 08: Comparison of Shearing
Fig. 9: Effect of Temperature
Behavior of nanofluids.
[Al2O3 (30 nm)/water]
[Al2O3/water and SiO2/EG]
60 0
Temperature C
70
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As fluid density plays important role in controlling many industrial processes, it is essential to investigate the effect of vol.% concentration of nanoparticles on the density of the nanofluid. The density of prepared nanofluids is measured using density meter (DMA 5000) from Anton Parr and results are presented as below: 6.2.1 Effect of Concentration and temperature The density results of all concentrations of Al2O3 nanofluid within the temperature range of 30 – 700C are summarized in the Fig 09. It is observed that the density increases with increase in the nanoparticle loading. At 30 0C, the variation in the density of Al2O3/water nanofluid compared with water is from 0.145% to 2.6% in the range of 0.1 to 1.0 vol.% of nanoparticle loading respectively, whereas at 700C, density variation is from 0.009% to 0.024% in the same range of nanoparticle concentration. The general observation is that density of nanofluid decreases with increase in the temperature which agrees well with the acceptable behavior of the fluids. 6.2.2. Comparison with Existing Correlations The measured value for the density of Al2O3/water nanofluid at 300C is compared with the Pak and Cho [3] equation in Fig. 10. Excellent agreement between measured values and the Pak and Cho equation is observed. The maximum variation between the measured values and values by Pak and Cho is 0.08 %. From this comparison, one can use the mixing formula used by Pak and Choi, for estimation of density of nanofluid with reasonable accuracy.
Density by Pak & Choi Experimental Value
1030
1.030
TiO2/Water
SiO3/Water
SiO2/EG
1.025
Relative Density (Rhonf/Rhobf)
1025
1020 3
Density (kg/m )
Al2O3/Water
1015
1010
1005
1000 0.0
0.2
0.4
0.6
0.8
1.015
1.010
1.005
1.000 0.0
1.0
0.2
0.4
0.6
0.8
1.0
% Volume Concentration
Volume Concentration
Fig. 10: Comparison between measured and estimated value by Pak and Choi [38]
1.020
Fig. 11 Comparison of Relative Densities
with different nanoparticles at 300C [Al2O3 (30 nm)/water]
6.2.3 Effect of Different Nanoparticles Fig. 11 shows the relative density of Al2O3/Water, TiO2/Water, SiO2/Water and SiO2/EG nanofluids at different nanoparticle concentration loading at 300C. The variation in the density of TiO2/water nanofluid compared with water is from 0.0822% to 2.6% in the range of 0.1 to 1.0 vol.% of nanoparticle loading respectively. For SiO2/Water nanofluid, the variation in the density is in the range of 0.0802 to 1.25% whereas for SiO2/EG nanofluid, density variation is in the range of 0.625% to 0.954 %.respectively in the same range of nanoparticle loading. From the density values obtained from measurement, it is observed that the mixture formula is gives good estimation for the density of nanofluids. The density of the nanofluids mainly depends on the densities of the nanoparticles and base fluids. The effect of nanoscale size of the particles, does not affect the effective density of the nanofluid.
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6.3. Uncertainty Analysis: The uncertainties in the measurement of viscosity and density of nanofluids were calculated considering different parameters. The viscosity of nanofluid is measured with MCR -52 rheometer. The minimum torque that can be applied by rheometer is 200 µNm. Thus the error involved in the measurement of torque is ±1.79%. The angular speed of the rheometer spindle is measured with least count of 10-3 rad/sec. This results in error involved in angular speed measurement as ±0.5.58%. As dynamic viscosity measurement involves shear stress and shear strain, the uncertainty in the dynamic viscosity is 3.11%. The density is measured with Density meter with the least count of 0.001 gm/cm3. Thus the error involved in the measurement of density is ±2.34 %.
6.4 Correlations Suggested Based on Measurement Result: Based on the measurement results of dynamic viscosity of the nanofluids, experimental correlations are suggested by many researchers. These correlations are relates the relative thermo-physical properties of nanofluids with percentage volume fraction of nanoparticles and temperatures. Based on the experimental results obtained for dynamic viscosity some experimental correlations are proposed for dilute nanofluids (volume concentration < 1.0%).. The correlations are developed by regression analysis with confidence level of 95%. For density of the nanofluids, the mixture formula gives good agreement with experimental results; hence the correlation for specific density of the nanofluid is not suggested. _
/ _
= 1.027615 + 12.2255 ∅
(3.14)
_
/ _
= 1.4868 ∅^0.033441 ^(−0.03684)
(3.15)
7. Conclusion With the experimental measurement of viscosity and density of nanofluids using different nanoparticles and base fluids with varying nanoparticles concentration, following conclusions can be drawn: i.
The viscosity of the nanofluid, increase with increase in the particle volume concentration of nanofluid. This results in increase in the pressure drop in the thermal system which has adverse effect on the use of nanofluid. For TiO2/water nanofluid with 1.0 vol. %maximum increment of 16 % in viscosity is observed at 300C .
ii. The effect of increased viscosity becomes negligible at higher temperature as viscosity of nanofluid reduces with increase in the temperature of the nanofluid. The increment in viscosity of Al2O3/water nanofluid with 1.0 vol. % at 300C is 15.5% which reduces to 8% at 700C. iii. The increase in the viscosity of nanofluid differs with different base fluids. For SiO2/water and SiO2/EG, enhancement is 14% and 12% with 1.0 vol.5 at 700C. iv. The classical formulas for viscosity of nanofluid under predict the enhancement in the viscosity with increase in nanoparticle volume concentration. v.
The density of the nanofluid increases with increase in the nanoparticles concentration, and slightly decreases with increase in the temperature.
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vi. Increment in the density with particles concentration of 1.0 vol% is 2.6%, 2.6%, 1.25 % and 0.954% at 300C for Al2O3/water, TiO2/water, SiO2/water and SiO2/EG nanofluids respectively. vii. The mixture formula shows good agreement to predict the density of nanofluid.
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