Performance evaluation of alumina nanofluids and nanoparticles-deposited surface on nucleate pool boiling phenomena

International Journal of Heat and Mass Transfer 146 (2020) 118833

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Performance evaluation of alumina nanofluids and nanoparticlesdeposited surface on nucleate pool boiling phenomena Mihir Modi, Prasad Kangude, Atul Srivastava ⇑ Department of Mechanical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India

a r t i c l e

i n f o

Article history: Received 2 July 2019 Received in revised form 2 October 2019 Accepted 2 October 2019

Keywords: Nucleate pool boiling Nanofluids Nanoparticles-deposited surface Single bubble dynamics Heat transfer rate

a b s t r a c t Single bubble-based nucleate boiling phenomena of water and alumina-water nanofluids (0.005 and 0.01 vol% concentrations) have been studied under nucleate pool boiling regime for two different superheat levels. While nanofluids-based boiling experiments have been performed on plain substrate surface, experiments with water have been conducted on plain as well as nanoparticles-deposited surfaces. For developing an understanding of the influence of nanoparticles, simultaneous measurements of bubble dynamic parameters as well as associated thermal gradients field have been made using non-intrusive rainbow schlieren optical technique. A direct comparison of water and nanofluids experiments revealed significant changes in bubble dynamic parameters such as reduction in bubble departure diameter and growth time, increase in departure frequency and wait time for the case of nanofluids. Thermal gradients field showed more spreading out of the superheat layer adjacent to the heater substrate due to the addition of nanoparticles in the bulk liquid. In a subsequent study, surface modification of the heated substrate has been realized in the form of deposition of nanoparticles during nanofluid-based boiling experiments. The nanoparticles that get deposited on the surface during long time boiling experiments lead to surface modifications. The resultant nanoparticle-deposited surface is employed as the heater surface for conducting pool boiling experiments with water. Results of these experiments have been compared with those conducted using plain (smooth) heated substrate. Similar trends have been observed in the bubble dynamic parameters for the experiments with water on nano-deposited surface vis-a-vis nanofluids on plain surface. Heat transfer partitioning study revealed that natural convection component reduces and evaporative heat transfer increases significantly in the presence of nanoparticles. Plausible mechanisms for the observed trends have been investigated and discussed. Ó 2019 Elsevier Ltd. All rights reserved.

1. Introduction Heat transfer is one of the most important engineering subjects in view of its ubiquitous nature across all engineering fields. With the growing technological advancements, there is a need for effective heat transfer enhancement techniques for efficient and safe working of thermal systems. In this regards, many active and passive enhancement techniques have been reported depending upon the application. It may be use of high thermal conductivity materials, extended surfaces (fins), additives to the fluid, jet impingement, application of fluid vibration etc. Active enhancement techniques are bulky and relatively costlier, whereas passive ones are compact and cheaper. In view of this, passive techniques have been explored extensively in the open literature [1]. One of the most popular passive enhancement techniques is to use of latent ⇑ Corresponding author. E-mail address: [email protected] (A. Srivastava). https://doi.org/10.1016/j.ijheatmasstransfer.2019.118833 0017-9310/Ó 2019 Elsevier Ltd. All rights reserved.

heat of vaporization of the working fluid, commonly known as boiling heat transfer. It is an efficient heat transport mechanism as it provides large values of heat transfer rates for a given temperature potential due to the occurrence of phase change phenomenon. With the sharp increase in energy demand, the technological advance demands an effective mode of transferring heat. Various industry fields, where the cooling of a high heat flux is needed, including nuclear power plants, chemical reactors, electronic devices, etc., use boiling heat transfer extensively. The nucleate boiling regime is the area of interest, the study of which provides fundamental insights of the two-phase process. In applications involving high heat fluxes, performance of boiling of conventional fluids such as water, ethylene glycol, and refrigerants has been observed to be inadequate. In order to further enhance the thermal performance of these fluids in the context of boiling heat transfer, many possible ways have been reported in the literature. One of them is to disperse the nanosized particles in the conventional fluids which significantly

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Nomenclature A area (mm2) BHTC boiling heat transfer coefficient (W/m2 K) CHF critical heat flux (W/m2) D diameter (mm) f bubble departure frequency (Hz) H hue (radians) hfg latent heat of vaporisation (J/kg) k thermal conductivity (W/m K) NF_0.005 boiling of Al2O3-water (0.005% (V/V)) on a clean substrate NF_0.01 boiling of Al2O3-water (0.01% (V/V)) on a clean substrate ND_0.01 boiling of water on nanoparticles-deposited substrate surface obtained after the end of the experiment with Al2O3-water (0.01% (V/V)) nanofluid n refractive index q heat transfer rate (W) T temperature (°C) TBL thermal boundary layer t time (ms)

enhance the properties like thermal conductivity, surface wettability, etc. known as nanofluids. These fluids are engineered colloidal suspensions of nano-particles in a base fluid. The nanoparticles are typically less than 100 nm size and made of metals, oxides, carbides, or carbon nanotubes. Common base fluids include water, ethylene glycol and oil. It has been reported in literature [2,3] that the addition of the nanoparticles has shown a significant increase in thermal conductivity of the base fluids. In the context of boiling phenomenon, it is widely accepted that the nanofluids enhance CHF performance by delaying the occurrence of CHF. This delay provides a larger regime for the nucleate boiling heat transfer (efficient heat transfer regime) to occur. However, at the same time, it is also to be noted here that there is no general consensus on the nature of modification in HTC for the nanofluids. Experimental investigation of pool boiling of water-Al2O3 nanofluid (0.05 wt%) was done by Hamda and Hamed [4]. Isolated bubbles were generated to study the bubble dynamic parameters such as bubble departure diameter, rate of growth using high speed imaging. One active nucleation site was observed in the case of pure water on small heated area in comparison to the nanofluid where multiple active nucleation sites were seen. The authors report that the bubbles generated for nanofluid were more spherical and smaller in size than pure water in addition to the significant higher bubble departure frequency. Gerardi et al. [5] performed infrared thermometry study of nanofluid pool boiling phenomena on silica (0.1% (V/V)) and diamond (0.01% (V/V)) nanoparticles. The effective boiling heat transfer coefficient decreased compared to water but, higher value of CHF was obtained for the nanofluids case. It was found that the nanofluids had significantly lower bubble departure frequency, higher wait time, lower bubble departure diameter and higher growth. Kim et al. [6] performed pool boiling experiments with dilute dispersions of alumina, zirconia and silica nanoparticles in water. An enhancement in CHF was observed for low concentrations (less than 0.1% (V/V)) due to the change in surface wettability. It was observed that nanofluids have a higher CHF value, but a lower nucleate boiling heat transfer coefficient (BHTC). The observed trend was attributed to the deposition of nanoparticles at the surface which creates a thermal resistance to heat transfer from heater surface to the fluid. The porous layer formed after nanofluid pool boiling was analyzed and an increase in surface wettability was observed owing to the static contact angle measurement.

V

bubble volume (mm3)

Greek symbols d refractive index difference w.r.t bulk liquid, uncertainty h angular deflection (radians) Subscripts b bubble bulk bulk conditions eb ebullition cycle evap evaporation g growth NC natural convection w wait wall heater substrate surface v vapour

Quan et al. [7] first reported that the wettability of the suspended nanoparticles plays an important role in altering the boiling performance. The authors observed that the moderately hydrophilic silica nanoparticles suspended in the bulk liquid tend to avoid bubble coalescence and, in turn, increase CHF and BHTC as compared to that observed for strongly hydrophilic nanoparticles. It is also reported that the wettability of the suspended nanoparticles has significant impact on the nature of nanoparticle deposition, surface roughness and bubble dynamics during the nanofluids-based pool boiling. Ham et al. [8] investigated pool boiling characteristics in Al2O3 nanofluid in terms of surface roughness and concentration. The surfaces with average roughness, Ra = 177.5 nm and Ra = 292.8 nm were used and the nanofluid concentrations used were 0.001, 0.01, 0.05 and 0.1% (V/V). A reduction in boiling heat transfer coefficient or the extension of natural convection boiling was found in addition to the CHF enhancement up to 0.05% (V/V). As the nanofluid concentration was increased from 0.05% (V/V) to 0.1% (V/V), the CHF was found to decrease due to excessive deposition. Das et al. [9] conducted a survey on the nucleate pool boiling of nanofluids with low and high solid particle concentrations. The authors found that the boiling performance deteriorates for higher concentrations due to faster sedimentation. The heat transfer with nanofluids showed an enhancement in heat flux at low solid particle concentrations. Bubble dynamics plays an important role in influencing the associated heat transfer rates. A heat flux partitioning model was proposed by Kurul and Podowski [10]. The heat removed by the boiling fluid is assumed to be through the following contributions – (a) latent heat of evaporation to form the bubbles, (b) heat expended in the re-formation of the thermal boundary layer following bubble departure, or the so-called quenching heat flux, and (c) heat transferred to the liquid phase outside the zone of influence of the bubbles by convection. In pool boiling, during the bubble growth, there exists a thin microlayer of liquid beneath the bubble. Most heat and mass transfer occurs in this layer. The growth of vapour bubbles due to the microlayer evaporation leaves behind the solid nanoparticles, which get deposited on the heater surface. This nanoparticledeposited layer plays an important role in the boiling heat transfer in terms of surface wettability, nucleation density, bubble dynamics, etc. Kwark et al. [11] experimentally studied the pool boiling behaviour of nanoparticles-deposited surfaces created during

M. Modi et al. / International Journal of Heat and Mass Transfer 146 (2020) 118833

nanofluid pool boiling experiments. The results showed an enhancement of CHF, however, the boiling performance influenced by the thickness and structure of the deposited nanoparticles was degraded. Ahmed and Hamed [12] performed experiments with nanofluids at concentrations of 0.01, 0.1 and 0.5% (V/V), followed by water pool boiling on the same nanoparticle deposited surfaces to investigate the transient nature of nanoparticles and its effect on boiling heat transfer coefficient. It was reported that nanofluids concentration affects the rate and uniformity of particles deposition. The results for water boiling on nanoparticles-deposited surface produced using the highest concentration of nanofluid gave the highest heat transfer coefficient, which is contradictory to the fact that higher deposition occurs at higher nanofluid concentration thereby causing larger deterioration in heat transfer rates. This was explained on the basis that layers were less uniform owing to faster deposition rates leaving parts of the surface exposed due to which higher heat transfer rates were obtained. Kwark et al. [13] showed that the deposition thickness (modified surface) depends on the duration of the nanofluid pool boiling experiment and the applied heat flux, consequently affecting both CHF as well as BHTC. Most of the literature discussed above focuses on the application of nanofluids and/or nanoparticles-deposited surfaces for CHF enhancement and, in turn, extending the nucleate boiling regime which indeed is best suited for high heat flux applications. For such applications involving high heat fluxes, the phenomenon of nucleate boiling gets characterized by the formation of multiple bubbles on the heated surface, a situation that is desirable from the point of view of enhancing CHF. However, for developing a fundamental understanding of the coupled bubble dynamics and associated heat transfer phenomena, the presence of multiple number of vapour bubbles in the field of view becomes a constraint. In addition, the mutual interaction of closely-spaced multiple bubbles also affects the dynamic parameters of the bubbles of interest. Under these limitations, the importance of single vapour bubblebased pool boiling experiments become important. The dynamics of single bubble in pool of liquid may be understood in absolute terms and its influence on the resultant heat transfer phenomena may be successfully elucidated. While the importance of single bubble-based experiments with water as the working fluid has been realized by a number of researchers in the past [14–18], such experiments with nanofluids (on plain heater surfaces) and nanoparticles-deposited surfaces are extremely scarce. Very recently, Wang et al. [19] performed single bubble-based pool boiling experiments with silica nanofluids on plain substrate surface. The authors studied the effect of nanoparticles wettability on bubble dynamics parameters for various concentrations of silica nanofluids and applied heat flux. Some of the recent works of the authors of the present study in this direction have been reported by Bhatt et al. [16], Kangude and Srivastava [17]. However, these studies are limited to SiO2/water-based nanofluids pool boiling experiments on a plain heated surface. Moreover, with SiO2/ water-based nanofluids, the authors reported a deterioration in the nucleate boiling heat transfer rates. Performance evaluation of Al2O3/water-based nanofluids and Al2O3 nanoparticles-deposited heated substrates in the context of nucleate pool boiling heat transfer and its dependence on the dynamics of single vapour bubble has not been reported in the literature. In this direction, the experimental work reported in this manuscript is an effort to bridge the gap in literature. We report single vapour bubble nucleate pool boiling experiments conducted with varying volume concentrations of Al2O3/water-based dilute nanofluids (with a plain surface being the heated substrate) and water-based boiling experiments conducted on nanoparticlesdeposited heated substrate for a direct comparison. The nanoparticles-deposited surface has been obtained at the end of the boiling experiments of 0.01% volume concentration of Al2O3

3

nanofluid conducted with a plain surface as the heated substrate. Evaporation of microlayer leads to the settlement of the nanoparticles on the surface of the plain heater, which subsequently leads to nanoparticles-deposited heated surface (referred to as ND_0.01 in the present manuscript henceforth). The dynamic parameters of single vapour bubble in all these sets of experiments (water and nanofluids of 0.005 and 0.01% volume concentration on plain surface, water with nanoparticles-deposited surface (ND_0.01)) have been recorded and compared with each other. Simultaneously, whole field thermal measurements have been made using the same imaging technique (rainbow schlieren deflectometry) and the dependence of heat transfer rates on vapour bubble dynamics has been discussed in detail. Finally, the performance evaluation of nanoparticles-deposited surface (with water as the working pool of liquid) vis-à-vis nanofluids on plain heated surface has been investigated and presented in the context of single bubble-based nucleate pool boiling regime. 2. Experimental apparatus and instrumentation The pool boiling experimental setup consists of mainly boiling chamber and heater substrate, which are discussed below. 2.1. Boiling chamber and heater substrate The pool boiling experiments with water and nanofluids were carried out in a specially-designed optically accessible chamber, Kangude and Srivastava [18]. The schematic of the apparatus is shown in Fig. 1(a) and (b). The boiling chamber made of stainless steel has a square base with optical windows installed in two directions on the opposite side faces. The boiling test cell consists of annular cubical chambers with optical windows mounted on the walls of the inner chamber. Dimension of the inner chamber is 45 mm
45 mm
80 mm and is chosen so as to capture all the refracted light rays propagating through it by the 25 mm diameter optical windows. The test cavity (1) holds test fluid (water/nanofluid) during experiments. Annular jackets (2) have been provided around the test cavity to maintain the constant temperature of test fluid. It is done by recirculating constant temperature fluid (ethylene glycol) through the outer annulus. Optical access to the test cavity has been facilitated by fixing optical windows (3) on the opposite walls of the test cavity. The optical windows are circular in shape to ensure tight sealing against test fluid and circulating oil by using standard high temperature ‘‘O” rings. Parallelism and straightness of the walls & optical windows were ensured in order to produce meaningful images. There is a provision for placing heater substrate at the bottom of the test cell. The heater is connected to DC power source to heat up the substrate so that boiling can be occurred on the surface. K-type thermocouples are used to measure the temperature of the test cell fluid and the bottom of the heater substrate. A reflux condenser is mounted on the top of the test cell to ensure no loss of test fluid during boiling due to the evaporation at the top interface and also to help in maintaining atmospheric pressure in the test cell. The heater substrate, which is a borofloat glass substrate of dimension 25 mm
25 mm
0.7 mm coated with a thin layer (700 nm thickness) of indium-tin oxide (ITO) was used in the experiment. The ITO film has good electrical conductivity. In view of this, on application of DC voltage to the ends of the ITO film through silver paint electrodes, Joule’s heat is generated in the film. Commercially available borofloat substrate usually has ITO coating all over the surface. However, in order to produce concentrated heat flux at the pre-defined bubble nucleation site, ITO layer is washed-off the surface by chemical etching to a shape shown in Fig. 1(c). This shape provides maximum electrical resistance to

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Fig. 1. Front view & section view (a), isometric view of pool boiling chamber ((b), all dimensions are in mm), and schematic of ITO film coated heater surface (c) [18].

DC current at the center (7 mm
5 mm) of the film since the cross sectional area available to the current flow is minimum. As a result, greater amount of heat is generated at the locations of higher values of electrical resistance following joule’s heating, which subsequently facilitates concentrated heat flux. To visualize the bubble growth and also simultaneously map the temperature field in the boiling chamber, rainbow schlieren deflectometry (RSD) is employed as the imaging technique. RSD is a non-intrusive method based on the principle of deflection of light rays due to spatially varying refractive index. Fig. 2(a) shows the optical configuration of the RSD, Bhatt et al. [16]. A 250 W white light source (1) with a suitable aperture has been used to produce a point source (3) at the focal plane of the collimating lens (4). This diverging beam is collimated using a 100 mm planoconvex lens with a focal length of 1000 mm. The collimated beam, thus obtained passes through the optical windows of the pool boiling chamber which is placed between lens (4) and the decollimating lens (5). Further, this light falls on lens (5) which focuses the light rays on a graded colour filter (6) placed at the focal plane of

the decollimating lens. The colour filter (6), developed on a photographic film with a continuous gradual variation of different colours along the radial direction, as shown in Fig. 2(b). A high speed colour CMOS camera (IDT vision, NX8S1) (7) with a zoom lens of 12X has been integrated with the system for recording the colour schlieren images (10) of the phenomena studied in the form of colour re-distributions/colour contrast. When the bulk fluid is at uniform temperature, i.e., no heat flux is applied, the light passing through the fluid remains undeflected and is focused at the centre spot of the colour filter, thereby showing the uniform red shade in the schlieren image. On application of the heat flux to the substrate surface, due to changes in refractive index of the working fluid, light rays get deflected at different angles depending on the magnitude of thermal gradients in the field of view. The focused refracted light (after lens (5)) onto the colour filter shifts radially outward from its centre and different colour distribution (colour contrast) is recorded. Stronger angular deflections of light rays result in larger values of hue, which correspond to stronger thermal gradients in the field of view. With ref-

M. Modi et al. / International Journal of Heat and Mass Transfer 146 (2020) 118833

5

Fig. 2. Schematic of the rainbow schlieren deflectometry setup (a) and digital image of the rainbow colour filter employed in the experiments (b). The principle of colour redistribution depending on the strength of temperature gradients has also been shown [16].

erence to the schematic shown in Fig. 2(b) of refraction of light rays, the increasing order of strength of temperature gradient is thus identified in the form of continuous variations of colours from Yellow (relatively weak thermal gradients) ? Green ? Blue ? Magenta (strong gradients of temperature). Thus, in the recorded rainbow schlieren images, shades of green/blue/magenta can be identified as regions of stronger gradients (green < blue < magenta) whereas yellow/red shades represent weak or almost zero thermal gradients. 2.2. Experimental methodology Single bubble pool boiling experiments have been carried out with water, 0.005 and 0.01 vol% nanofluids under saturated bulk conditions and at two different levels of superheat (7 and 9 °C). In the case of nanofluids-based experiments on a plane heated substrate, evaporation of the base fluid (water) leads to the settlement and eventual deposition of the left over nanoparticles on the top surface of the heater. Then, this achieved nanoparticles-deposited surface has been used as the substrate for conducting waterbased nucleate pool boiling experiments. The nanoparticlesdeposited surface has been referred to as ND_0.01 in the manuscript for the sake of brevity. Before the start of any experiment, test fluid (water/nanofluid) is heated to the saturation temperature by circulating hot oil through the annular jackets and maintained it for 2 to 3 h at that temperature for degasification. Degasification process removes the non-condensable gases from the test fluid and thus, tends to minimize the effect of dissolved gases on the boiling phenomenon. After degasification, single bubble is generated on the heater surface by applying heat flux to the surface, where the Joule heat is generated due to increased resistance (local etching of the ITO coating at the centre of the substrate). A high-speed colour camera

integrated with the schlieren system records the experimental data in the form of rainbow schlieren images of the boiling process with a spatial resolution of 1600
1200 pixels and at a frame rate of 1000 Hz. These images are processed to quantify the bubble dynamic parameters as well as the individual contributions of the associated heat transfer rates. Nanofluid is a colloidal mixture of nano-sized particles and liquid, which is usually free of agglomeration and sedimentation. In order to ensure this, the mixture is subjected to ultrasonic vibration. However, certain type of nanoparticles have tendency to form bigger particles by agglomeration even after subjected to ultrasonic vibration at higher concentrations. To minimize the effect of agglomeration in that case, it is imperative to add surfactant into the nanofluid. In the present work, Al2O3 nanoparticles (13 nm in size) were mixed with water and ultrasonically vibrated for 3 h. Two concentrations of nanofluids were prepared containing 0.005 and 0.01 vol% Al2O3 nanoparticles. To avoid agglomeration, Sodium Dodecyl Benzene Sulphonate (SDBS) was added as a surfactant in concentrations of 0.02 and 0.03 wt% for 0.005 and 0.01 vol% nanofluid, respectively. Following [20], the influence of such low levels of surfactant addition on thermal conductivity of dilute nanofluids can be considered to be quite negligible and thus has been ignored in the present study. The thermo-physical properties of the employed working fluids (water and nanofluids), as determined following the correlations reported by Bang et al. [21], have been presented in Table 1. 3. Data reduction methodology 3.1. Calibration curve and temperature distribution In order to study the bubble dynamics, Schlieren technique has been employed which is a refractive-index based optical

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Table 1 Thermo-physical properties of water and nanofluids. Working fluid

Density (kg/m3)

Thermal conductivity (W/m K)

Viscosity (mPa s)

Specific heat capacity (kJ/kg K)

Water NF_0.005 NF_0.01

958.37 958.38 958.38

0.6790 0.6791 0.6792

281.83 281.86 281.90

4.215 4.214 4.214

technique. Light rays under the influence of varying refractive index field due to temperature gradient in the test region undergoes angular deflections and these deflections correspond to the hue values which are stored in the pixels. These are calculated with the help of calibration curve obtained using the methodology reported in literature [14,17]. Average hue values are calculated and plotted with the radial displacement. With the help of the linear fit equation, the spatial map of hue distribution (recorded in the form of Schlieren images) is then converted into the twodimensional distribution (map) of radial distances. The calibration curves for water and 0.01% (V/V) alumina-water nanofluid are shown in Fig. 3. The angular deflection distribution (h(x,y)) in the region of interest is determined by applying geometric transformation and the Snell’s law to the radial distance data and the angular deflection data (e(x,y)). The mathematical relation between angular deflection (h(x,y)) and the refractive index gradient for the axisymmetric measurement can be seen in Eq. (1) [17]. The Abel transformation is used to obtain the refractive index difference (d) from the angular deflection. This Abel inverted field provides a representation of the refractive index field at any sectional plane. The associated axisymmetric temperature field in the bulk liquid is then calculated using Equation (2). Subsequently, numerical one step discretization method has been employed to map the temperature gradient field adjacent to the heater surface [17]. The dependence of refractive index of water on temperature is determined from the empirical correlation proposed by Bashkatov and Genin [22]. The dependence of refractive index of the employed nanofluids on temperature is also determined using the same correlation following the observation made by Jain et al. [23], wherein, no considerable change in the refractive index of dilute nanofluids as a function of temperature was observed vis-a-vis that of water.

dðr; yÞ ¼

nðr; yÞ 1 1¼ nbulk p

Z1 r

hðx; yÞ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi dx x2  r2

ð1Þ

T ¼ T bulk þ

Dn dn=dT

ð2Þ

3.2. Heat transfer rates The whole field temperature distribution determined above is used to obtain instantaneous natural convection heat transfer rates. Applying energy balance at the heater surface leads to the quantification of the natural convection component of heat transfer,

  @T qNC ¼ kðAwall  Ab Þ @y wall

ð3Þ

Here, Ab is the circular area at the surface whose diameter is equal to the bubble departure diameter and Awall is the area of the heater surface. For the purpose of analysis and in order to have uniformity across all the experiments, the wall area chosen is a circular one around the nucleation site having radius equal to the departure diameter of water vapour bubble for any given working fluid. The selection is based on the assumption that the heater surface is at uniform temperature over this area. Thus, the annular area is the area of consideration for natural convection. It should be noted that the wall area remains same for all the experiments but the bubble area is different for different experiments as the bubble departure diameter is not expected to be same in all the cases. The evaporative component of the total heat transfer is determined with the help of experimentally measured transients of bubble dynamic parameters such as bubble departure diameter and bubble growth rate, as expressed as Eq. (4). For experiments with low heat flux/low wall superheat, the evaporation component (qevap) can be considered to comprise of the contributions from the evaporation of microlayer and superheat layer around the vapour bubble.

dV qev ap ¼ qv hfg dt

Fig. 3. Calibration curve along the radial direction of the colour filter for water (a) and 0.01 vol% nanofluid (b).

ð4Þ

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For evaluation of heat transfer performance, the natural convective and evaporative heat transfer rates are obtained by averaging the respective instantaneous heat transfer rates over the entire ebullition cycle. The time-averaged value obtained has further been averaged for 3 cycles, where each cycle was analyzed at 15 distinct instants (15 instantaneous schlieren images). Subsequently, the overall heat transfer rate has been expressed as the summation of the average natural convection and evaporative heat transfer rates as:

  qtotal ¼ ðqNC Þav g þ qev ap av g

ð5Þ

The heat utilized in the re-formation of thermal boundary layer is the quenching heat transfer. The temperature at the dry spot area is higher than the surrounding liquid. The apparent temperature at which the surface begins to cool rapidly with a sudden drop in temperature is the rewetting temperature which is a difficult parameter to directly measure in such experiments. Upon bubble departure, cold liquid rushes to fill the area vacated by the departing bubble. This cooler liquid is heated by transient conduction. The temperature distribution in the localized region that gets influenced by the bubble departure is highly non-linear and further adds to the experimental complexity. The real time measurement of the 2-D temperature field within the heater surface is beyond the scope of the present work and thus, the quenching heat transfer rate has not been experimentally determined. 3.3. Equivalent diameter at bubble departure The equivalent bubble diameter has been evaluated by calculating the diameter of a completely spherical bubble, which occupies the same volume as that of the actual vapour bubble [24,25]. As part of the procedure followed to calculate the bubble volume and departure diameter, area occupied by the bubble in any given schlieren image is masked using Photoshop software so that it becomes easy to trace the bubble interface with the help of a MATLAB code. The volume of an actual vapour bubble is then calculated from the masked image wherein, the bubble is considered axisymmetric and thus can be considered to be formed by stacking of circular disks of thickness equal to the pixel size. Following this, the volume and the equivalent diameter of the vapour bubble can respectively be calculated by the following geometric mathematical formulation:

V¼

i¼h X i¼1

Deq ¼

p 4

D2
pixelsize

rffiffiffiffiffiffiffi 3 6V

p

ð6Þ

ð7Þ

3.4. Uncertainty analysis Schlieren-based experimental measurements involve unavoidable errors due to slight optical misalignment, fluctuations in the ambient conditions, uncertainties associated with the data reduction methodology and the inherent uncertainties in the input parameters of the experiments (supplied heat flux, volume concentrations of nanoparticles etc.). Various components of the rainbow schlieren system were carefully aligned in order to reduce the uncertainties due to optical misalignment to the maximum extent possible. These uncertainties have been quantified by the approach initiated by Kline and McClintock [26] and further implemented by other researchers in the context of optics based measurements (Naylor and Duarte [27], Kangude and Srivastava [17], Narayan et al. [28]). Table 2 summarizes the uncertainties associated with the various parameters that eventually propagate into the

Table 2 Uncertainty values associated with the major individual parameters. Parameter

Uncertainty (0.01% (V/V) nanofluid)

Linear deflection Abel inversion transformation Bulk temperature Thermal conductivity Temperature dependence of refractive index Temperature field Rate of change of bubble volume

0.59 mm 0.0022 0.5 °C 0.001 W m1 °C -1 1
10-5 °C-1 1.2 °C 3.72
10-8 m3 s1

determination of natural convection rate. The total uncertainty involved to obtain the natural convective heat transfer rate can be expressed as:

dqNC

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  2  2  2 @qNC @qNC @qNC ¼ dk þ dA þ dð@T=@yÞ @k @A @ ð@T=@yÞ

ð8Þ

The maximum uncertainty associated with the natural convection rate determined using Eq. (8) has found to be 10% and 13% respectively in the case of water and 0.01 vol% nanofluid experiments. The evaporative component of heat transfer depends on the rate of bubble growth (dV/dt) as seen from Eq. (4), which is the only uncertainty parameter that has been accounted in the computation of the uncertainty involved in the evaporative component. Thus, based on uncertainty in the bubble growth rate, total uncertainty associated with the determination of evaporative heat transfer rate has found to be 1%. 4. Results and discussions 4.1. Comparison of pool boiling phenomenon of water and nanofluids on a plain surface and water on nanoparticles-deposited surface This section reports the experimental findings/observations of single bubble-based nucleate pool boiling phenomena in both qualitative and quantitative terms with the help of rainbow schlieren diagnostic technique. Different sets of boiling experiments have been carried out as: (1) Boiling experiments on a clean (plain) substrate with water and Al2O3-water nanofluids (0.005 and 0.01% (V/V), henceforth referred to as NF_0.005 and NF_0.01 respectively) and (2) experiments on nanoparticles-deposited substrate surface with water as the working fluid.1 Based on the recorded schlieren images in each experiment, the bubble dynamic parameters and individual contribution of heat transfer mechanisms have been compared across the two sets of experiments. This comparative study is expected to help in gaining better insight into understanding the influence of small levels of concentrations of suspended nanoparticles on the single bubble-based pool boiling heat transfer phenomenon. Moreover, it would further assist in differentiating the influence of suspended nanoparticles from that of the deposited ones on the associated heat transfer mechanisms by comparing the results of NF_0.01 with that of the ND_0.01. Time elapsed schlieren images of a single bubble nucleating on plain and nano-deposited heater substrate for two sets of experiment carried out under constant wall superheat and saturated bulk liquid conditions have been shown in Fig. 4 for one ebullition cycle. The spatial resolution of the schlieren images in terms of pixel size 1 Nanoparticles-deposited substrate used in these experiments is the substrate obtained after the end of the boiling experiment carried out with 0.01% (V/V) concentration of Al2O3/water-based nanofluid on an originally clean substrate. Such surfaces are henceforth referred to as ND_0.01 in the context of the present discussions.

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Fig. 4. Rainbow schlieren images of a single vapor bubble recorded at various time instants during one complete ebullition cycle for water on a plain surface (a), 0.005 vol% nanofluid (b), 0.01 vol% nanofluid (c) and water on ND_0.01 surface (d) under constant surface temperature conditions (107 °C) (t = time instant, teb = ebullition cycle time).

is on average 12 lm and the temporal resolution is 1000 fps. With reference to Fig. 2(b) (colour filter), the red/lighter yellow background in each schlieren image represents zero (or very weak) thermal gradients region, which corresponds to the bulk liquid maintained at uniform temperature. The spatial region of the gradual color variation (magenta ? blue ? green ? yellow ? red) from the heated substrate (bottom of the image), in the normal direction to the substrate towards the uniform temperature bulk liquid, corresponds to the region of the prevalence of strong thermal gradients and hence, it can be identified as thermal boundary layer formed on the heated substrate. It is quite clear in the images from Fig. 4 that the thermal gradients are maximum adjacent to the heated substrate and are found to be gradually reducing as one moves towards the bulk liquid irrespective of the set of experiment. The presented images in Fig. 4 show various bubble dynamics processes associated with nucleate boiling such as bubble nucleation, bubble growth & departure, wait time followed by the inception of the next bubble. Simultaneously, these images also show a range of thermal sub-processes associated with nucleate boiling, such as development of superheat layer on the heated sub-

strate. In addition, scavenging of a part of the superheat layer upon bubble departure in the wake region of departing bubble for the case of water pool boiling on nanoparticles-deposited surface can also be seen (Fig. 4(d)). With reference to Fig. 4, one can see that the superheat layer adjacent to the heater surface is very thin (TBL  0.38) with water as the working fluid (Fig. 4(a)) and the bubble growth takes place almost throughout the ebullition period, leaving minuscule amount of waiting period. However, in the case of nanofluids (Fig. 4(b) and (c)), the superheat layer is relatively more stretched out (TBL  0.63) and the time elapsed bubble growth process is less than around 50% of the ebullition period. This implies that the bubble grows and departs the surface faster in the presence of suspended nanoparticles in comparison to the case of pure water. The nature of superheated boundary layer formed on the substrate surface in the case of ND_0.01 (nanoparticle-deposited surface, Fig. 4(d)) is more or less identical (TBL  0.60) to that observed in the case of NF_0.01 (Fig. 4(c)). It implies that the suspended nanoparticles have very little impact on the development of the superheated boundary layer. The observed stretching of

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M. Modi et al. / International Journal of Heat and Mass Transfer 146 (2020) 118833 Table 3 Applied heat fluxes for water and nanofluids to maintain the surface temperatures. Applied heat flux (kW/m2) Surface temperature

Water

NF_0.005

NF_0.01

ND_0.01

107 °C 109 °C

28.8 (±0.9) 46.7 (±1.4)

30.1 (±0.9) 47.1 (±1.4)

37.6 (±1.1) 49.5 (±1.5)

35.8 (±1.1) 48.6 (±1.5)

the thermal boundary layer in the case of NF_0.01 and ND_0.01 can thus be attributed to the additional thermal resistance caused by the thin layer of nanoparticles deposited on the heater substrate surface. However, it cannot be neglected that the deposited layer of nanoparticles inherently forms a loose porous layer due to which some of the nanoparticles might get detached from the substrate surface consistently upon bubble departure and in turn, influence the spread of the thermal boundary layer. 4.1.1. Comparison of applied heat fluxes Table 3 shows the average values of the heat fluxes applied during the respective experiments to maintain the superheat levels of 7 and 9 °C with single bubble nucleation. The heat flux supplied to maintain the required superheat is likely to be different based on the effectiveness of the heat transport from the heater surface. With reference to Table 3, it can be seen that to maintain a wall superheat of 7 °C, the heat flux applied is the highest for the NF_0.01 case which is approximately same to that of the nanoparticles-deposited surface (ND_0.01) within the limits of error. It implies that the nanofluid with 0.01% (V/V) concentration is able to transport the heat from the heater substrate at a faster rate in comparison to the water and NF_0.005 cases. The heat transfer rates of water (on plain surface) and NF_0.005 can be considered approximately the same by accounting for the level of uncertainty in the measurement. In general, this data provide direct evidence of efficient heat transfer capability of alumina nanofluids at 0.01% (V/V) concentration. However, it does not provide any information on the influence of nanoparticles on the heat transfer mechanism(s), which resulted into the augmentation in the heat transfer rates. The main heat transfer mechanism, which has been subjected to great step-up due to the addition of nanoparticles is thought to be evaporative heat transfer in the form of latent heat energy. The magnitude of evaporative heat transfer rate for a given fluid depends on the bubble dynamic parameters such as bubble size, bubble departure frequency, and cycle time. Hence, in the subsequent section, the dependence of bubble dynamics parameters on the volumetric concentration of nanofluids has been discussed. It is to be noted that the values of heat flux at 109 °C are quite close to one another. This can be attributed to the increasing thickness of the nanoparticles deposited layer on the heater substrate surface with increasing heat flux and concentration. At high levels of heat flux applied, the evaporation of the base fluid leads to the formation of a layer of nanoparticles (that are left over) on the surface. This leads to an increase in the thermal resistance to the heat flow, which in turn, reduces the relative heat removal capability of NF_0.01 nanofluid at higher wall superheat and so for the ND_0.01 surface. The evidence of nanoparticles deposition on the heater substrate surface has been provided in the form of SEM images in the subsequent section. 4.1.2. Bubble dynamics Quantitative data on various bubble dynamic parameters, such as bubble departure diameter and departure frequency, growth and wait times have been presented for the two sets of experiments. These parameters have been averaged over a total of 30 bubble cycles. The plausible mechanisms through which the

nanoparticles in the suspended form as well as the deposited form affect the bubble dynamics have also been discussed. 4.1.2.1. Bubble departure diameter. Bubble departure diameter represents the equivalent spherical bubble diameter at the time instant of its departure from the heater substrate surface and it has been calculated using the methodology discussed in Section 3.3. Fig. 5(a) and (b) show the variation of bubble departure diameters for the two sets of experiments at superheat levels of 7 and 9 °C. The bubble departure diameter is seen to be reducing with increasing concentration of nanofluid. The trends of the variation of bubble departure diameter as a function of varying nanofluid concentration have been explained on the basis of SEM images of the plain and nanoparticles-deposited surface, as shown in Fig. 6. The figure shows SEM images of the clean heater substrate surface before and after the pool boiling experiment with 0.01% (V/ V) nanofluid. As seen from the SEM images, a thin porous layer of nanoparticles gets formed on the substrate surface in the case of NF_0.01. The deposition at the nucleation site seems to be random and in a clustered manner in comparison to the area around it. It has been well documented in the literature that deposition of nanoparticles as porous layer enhances the surface wettability and the capillary flow rates [29].2 In the context of the present experiments, surface wettability has been quantified in terms of static contact angle of the sessile droplet. As shown in Fig. 6(c) and (d), the static contact angle of the sessile droplet of water (Vol. = 1 ml) on clean substrate surface (h = 85 ± 3°) is quite higher than that observed for the ND_0.01 case (h = 64 ± 3°). Thus, these modified characteristics of the surface (due to the deposition of suspended nanoparticles), in turn, tend to reduce the dynamic contact angle as well as the contact line area (dry patch) of the vapour bubble by providing liquid to the evaporating microlayer at a faster rate as compared to the case observed with a clean surface. The reduction in contact angle and the dry patch area leads to the weakening of surface tension force acting on the bubble in the case of nanofluids, vapour bubble of smaller volume departs the surface and thus, the bubble departure diameter reduces with increasing concentration of nanofluids (0 to 0.01% (V/V)). The bubble departure diameter is almost the same for the cases of NF_0.01 and ND_0.01 for any given level of wall superheat. This observation suggests that the suspended nanoparticles have very little impact on the bubble departure diameter and the phenomenon of bubble departure is primarily influenced by the 2 It is to be mentioned here that for any given heater substrate (clean and/or nanoparticles-deposited surface), the nucleate boiling experiments have been conducted in a continuous manner and the experimental data has been recorded over a large number of bubble cycles. In view of this, the dependence of nanoparticles deposition thickness on bubble cycle could not be quantified as this exercise would have required dismantling the boiling chamber to take out the heater substrate and measure the deposition thickness during the experimental run time, an exercise that is practically impossible. Moreover, the fact that the heater substrate is a transparent glass, measurement of instantaneous thickness of nanoparticles-deposited layer using tools such as an ellipsometer becomes highly challenging. In view of these constraints, the thickness of nanoparticles-deposited layer on the heated substrate could not be quantified as a function of bubble cycle and hence, for these reasons, the experimental observations of the present study have been interpreted based on the widely-reported fact that the thickness of nanoparticles layer on the substrate increases with experimental run time as well as with increasing concentration of nanoparticles [8,13].

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2.5

3.0 2.462

2.0 1.5

1.448 1.18

1.0

1.053

0.5 0.0

Water

NF_0.005

NF_0.01

ND_0.01

(a)

Bubble departure diameter (mm)

Bubble departure diameter (mm)

3.0

2.5

2.383

2.0 1.5

1.47

1.42

1.553

1.0 0.5 0.0

Water

NF_0.005

NF_0.01

ND_0.01

(b)

Fig. 5. Bubble departure diameters in pool boiling experiments conducted with water, nanofluids of two concentrations (0.005 and 0.01% (V/V)) on a plain surface and water on nanoparticles-deposited surface (ND_0.01). Data is presented for two values of surface temperatures i.e. 107 °C (a) and 109 °C (b).

Fig. 6. SEM images for (a) clean surface and (b) ND_0.01 surface at magnification of 35 K. Static contact angle of water sessile droplet on: (c) clean substrate h = (85 ± 3°) and (d) ND_0.01 substrate h = (64 ± 3°).

deposited part of the nanoparticles. The decrease in departure diameter in the case of ND_0.01 can also be explained on the basis of Modified Young’s equation (Eq. 9) [6], which accounts for the surface roughness factor, r and is the ratio of the effective contact area to the smooth contact area.

c  cSL cosðhÞ ¼ r SV r

ð9Þ

Here, h is the static contact angle, r is the surface tension and cSV  cSL is called the adhesion tension. The nano-deposited surface is expected to have higher roughness than the plain surface, which enhances the surface wettability, as per Eq. (9). The increased

surface wettability due to the deposition of nanoparticles is also quite evident through the experimental data presented (in the form of contact angles) in Fig. 6(c) and (d). 4.1.2.2. Wait, growth and cycle times. When a vapour bubble nucleates and starts to grow on a heated surface, finite amount of time is required for the bubble to grow and depart from the surface. This time period is known as the growth time (tg). On the other hand, the time interval between the departure of one bubble to the nucleation of the next at a given nucleation site is referred to as the waiting period (tw). The addition of growth and wait times results in one complete cycle, known as the ebullition cycle time

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250

Wait time Growth time Total cycle time

198 190

Time (ms)

200

40 37.04

30 21.28

20

15.21

10 5.05

0

Water

NF_0.005

NF_0.01

ND_0.01

Fig. 8. Bubble departure frequency for pool boiling of water, nanofluids on a plain surface and water on nanoparticle-deposited surface at surface temperature of 107 °C.

to water, has earlier been demonstrated on the basis of applied heat fluxes, as discussed in 4.1.1. As a result, extra time is needed to superheat the liquid and reform the thermal boundary layer that is required to sustain such a minuscule or to incept entirely new vapour nucleus in the case of nanofluids. The behavior of decrease in wait time from NF_0.005 to NF_0.01 can be explained with reference to the applied heat flux values (Table 3). It is seen in Table 3 that to maintain the same superheat level of 7 °C, the heat flux applied is significantly higher for NF_0.01 in comparison to NF_0.005. The extra heat flux available is utilized for the faster reformation of the thermal boundary layer resulting in drop in wait time. With increase in superheat, along the expected lines, a reduction in wait, growth and cycle time is observed.3 4.1.2.3. Bubble departure frequency. Bubble departure frequency refers to the rate at which the bubbles depart from the surface to complete one full ebullition cycle and is defined as Eq. (10). The variation of values of bubble departure frequency as a function of nanofluids concentration for a surface temperature of 107 °C is shown in Fig. 8. The figure reveals a significant increase in bubble departure frequency with increasing nanofluid concentration from 0 to 0.01% (V/V). This observation can be justified based on the trend seen in growth time, wait time and bubble departure diameter. As discussed, bubble grows faster and leaves the surface at smaller sizes in the case of nanofluids, whereas due to very high growth time of water vapour bubble, it exhibits very small value of departure frequency.

f ¼

1 tw þ tg

ð10Þ

Mchale and Garimella [30] reported higher bubble departure frequencies on rough surfaces. Wang et al. [19] found that the roughness of the substrate surface due to nanoparticles deposition increases with increasing nanofluid concentration during single bubble-based pool boiling experiments. Thus, the trend of bubble

150 100

67 47

50

49

34 8

0

50

Bubble departure frequency (Hz)

(teb) or just the cycle time. The wait, growth and cycle times for water and nanofluids on a plain surface and water on ND_0.01 surface under constant surface temperature condition of 107 °C are shown in Fig. 7. Important aspect to note here is that majority of the cycle time is constituted by the growth time for the water case and its value is one order magnitude greater than that of nanofluids and nanoparticles-deposited cases. It suggests that the vapour bubble grows faster in the presence of nanoparticles in comparison to that growing on plain surface with pure water. The observed attenuation in the growth time for nanofluids can be explained on the basis of possible modification in the microlayer evaporation dynamics due to deposition of nanoparticles on the heater surface. As discussed earlier, thin porous layer of nanoparticles enhances the surface wettability and capillary flow rates by facilitating more number of nano-channels (pathways) to the liquid flow. This results into continuous and faster replenishment of liquid that gets evaporated during the microlayer evaporation. As a result, majority of the bubble base area is occupied by the microlayer, leaving only a small dry patch area. All these mechanisms cause the microlayer to evaporate at a faster rate, which in turn, reduces the bubble growth time in the case of nanofluids as well as the ND_0.01 case with respect to the case of boiling of water on the plain surface. The values of wait time are seen to increase from the water case to NF_0.005 (nearly 4 times higher) but then decrease from NF_0.005 to NF_0.01. The overall rise in wait time in the case of nanofluids in comparison with water can possibly be the result of the mechanism through which the next bubble nucleates. It has been observed that the water vapour bubble departs the surface leaving a large amount of vapour on the surface. Due to surface tension, the leftover vapour forms a small vapour nucleus. Since, the wettability of water on plain surface is less, re-wetting phenomenon upon previous bubble departure does not wet the surface at the location of this small nucleus and thus the small nucleus starts to grow as soon as it is formed. However, in the case of nanofluids, leftover vapour nucleus is minuscule as the contact line area is very small. In addition, due to the enhanced wettability, there is a possibility of complete re-wetting of the tiny vapour nucleus by flooding all the pores in the deposited layer. Furthermore, by examining the growth and cycle time data, it can be inferred that the local temperature of the nucleation site is slightly less in the case of nanofluids as more number of bubbles are observed to leave the surface in a given time, which in turn make the tiny vapour nucleus to condense. The direct evidence of better heat removal capability of nanofluids, which reduces the nucleation site temperature faster compared

Water

27 13

NF_0.005

14 13

NF_0.01

18

ND_0.01

Fig. 7. Wait, growth & cycle times for pool boiling of water, nanofluids on a plain surface and water on nanoparticle-deposited surface at surface temperature of 107 °C.

3 It is important to note here that a significant rise in wait time has been observed for the ND_0.01 surface with respect to the case of NF_0.01, a trend which is not to be expected. However, with the current experimental approach, it is difficult to bring out the plausible reason(s) that would support the observed increase in the wait time for the case of ND_0.01. In order to fully understand this phenomenon, it is imperative to integrate an IR thermal camera with the schlieren system so as to get the in situ temperature distribution of the heater surface. By capturing the changes in the local temperatures around the nucleation site in the case of NF_0.01 and ND_0.01, it would be possible to highlight the mechanism(s) that causes the observed increment in wait time, a subject that forms the scope of future extension of this work.

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departure frequency as a function of nanofluids concentration, as observed in the present experiments, finds support in these works of Wang et al. [19] and Mchale and Garimella [30] reported in the literature. In the context of the present work, the ND surfaces have higher surface roughness relative to the plain heater surface. In addition, the surface tension force depends on the bubble base diameter (perimeter). The reduction in bubble diameter at departure, as observed in Fig. 5, is due to the shrinking of the triple line and eventually resulting in decrease in the surface tension force. This causes the bubbles to detach from the surface with ease and at a faster rate, thereby increasing the bubble departure frequency. It is worth noting here that the bubble departure frequency for the case of ND_0.01 with respect to the cases of NF_0.005 and NF_0.01 is relatively smaller. This is due to the fact that the wait time for the case of ND_0.01 is much higher than that observed in the case of nanofluids. As a result, total ebullition cycle time, which is the inverse of departure frequency (Eq. (10)), is comparatively higher for the case of ND_0.01 than that of nanofluids experiments (NF_0.005 and NF_0.01). As a result, the bubble departure frequency is not highest for the case of ND_0.01 (vis-a-vis nanofluids cases (NF_0.005 and NF_0.01)) even though departure diameters are almost the same for all three cases. In general, higher frequency corresponds to an increase in the evaporative component of heat transfer. In addition, it causes faster re-wetting of the dry patch area of the heater surface, which is expected to help in enhancing the heat transfer rates. Such heat transfer aspects of the study have been presented in following sections: 4.1.3. Temperature distribution and heat transfer rates In this section, heat transfer performance of water has been compared with that obtained for two different concentrations of nanofluids (0.005 and 0.01 V/V %) on a plain surface as well as water-based experiment on nanoparticles-deposited (ND_0.01) surface. In order to understand the plausible mechanisms through which the nanoparticles (both in suspended and deposited form) affect the various thermal processes, whole-field temperature distributions have been determined from the recorded sequence of schlieren images following the data reduction methodology discussed in Section 3.1. Based on quantitative analysis, individual contributions of natural convection-based heat transfer and evaporative heat transfer rates have been determined. Fig. 9 shows the whole field temperature distribution contour plots for water and 0.01% (V/V) nanofluid on a plain surface and water on ND_0.01 surface. The data shown reveal the possible impact of suspended nanoparticles on the superheated layer adjacent to the heater surface; superheat layer is more stretched out and thus, the same DT across the superheat layer gets spread over a larger distance in the case of nanofluids. This leads to a reduction in the strength of thermal gradients, which in turn, deteriorates the natural convection heat transfer component. The stretching of the superheat layer in the presence of suspended nanoparticles has been attributed to

the outcome of the random movement of the suspended nanoparticles under the influence of the temperature gradients in the superheat layer [23,31]. The cycle averaged magnitudes of natural convection, evaporation and overall heat transfer rates have been presented in the form of bar charts in Fig. 10(a). Three random ebullition cycles have been analysed to determine the cycle averaged heat transfer rates for each set of experiments. These values are calculated as indicated in the Section 3.2 on data reduction methodology. The reliability of the methodology followed for determining the heat transfer rates has previously been checked by validating the results obtained from the present approach with that predicted by the RPI model [32]. Fig. 10(a) clearly depicts the dominance of the natural convective heat transfer rates over the evaporative one for any given experimental case but in the case of NF_0.01, both these rates show almost the same values within the limit of error bars. The contribution of natural convection comes out to be the highest for the water case due to the presence of strong thermal gradients in the vicinity of the heated substrate. Smaller thickness of thermal boundary layer for any given DT in the case of water on plain surface indicates the higher strength of temperature gradients adjacent to the heater substrate in comparison with that of the nanofluids (Fig. 4(a)). In quantitative terms, the strength of temperature gradients adjacent to the heater substrate has been presented in Table 4 in the form of natural convection-based heat transfer coefficient (NHTC). The data presented in Table 4 infers that the single phase heat transfer is more efficient with the water as the working fluid as compared to the case of nanofluids. However, the natural convection component for the ND_0.01 case is the highest, as shown in Fig. 10(a), which seems contrary to the data presented in Table 4, wherein NHTC is smaller for the case of ND_0.01 than that of the water case. This contrasting observation has been explained as follows: It is to be noted that the absolute magnitude of each component of the heat transfer rates is influenced by the value of surface area taken in its calculation. As discussed in Section 3.2, the total area under consideration over which heat transfer analysis has been carried out is same for all the cases but the relative area available for the natural convection and the evaporation are different for each case due to the corresponding bubble departure diameters. In order to calculate the rate of natural convection, the annular area that is being considered is highest for the case of NF_0.01 and ND_0.01 due to their low bubble diameter at the departure. Thus, the decrease in natural convection-based heat transfer rate is not very significant despite the observed stretching of the thermal boundary layer in the case of NF_0.01 and ND_0.01. Nonetheless, significant increment in departure frequency dramatically increases the relative contribution of evaporation in the case of nanofluids with respect to the water case, as clearly shown in Fig. 10(a) based on the present experiments.

Fig. 9. Whole field temperature distribution contour plots for (a) water, (b) 0.01 vol% nanofluid on a plain surface and (c) water on ND_0.01 surface at a wall superheat of 7 °C.

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13

Fig. 10. Cycle-averaged heat transfer rates (a) and boiling heat transfer coefficient (b) for water, NF_0.005 and NF_0.01 and ND_0.01 at a wall superheat of 7 °C.

Table 4 Natural convection based heat transfer coefficient at a surface temperature of 107 °C. Case

Natural convection heat transfer coefficient (W/m2 K)

Water NF_0.005 NF_0.01 ND_0.01

1321 1126 924 1256

The evaporation component indicates the amount of heat carried away by the departing bubbles in the form of latent heat, which shows an increasing trend with increasing concentration of nanoparticles. This trend can be attributed to the significant increment in the bubble departure frequency as one increases the concentration from 0 to 0.01% (V/V) (Fig. 8). This aspect of nanofluid boiling becomes more significant if more number of nucleation sites are active over a unit area. In the present case, only one nucleation site is active due to which the effect of nanoparticles on the evaporative heat transfer rate is underfelt. The evaporative component is significantly higher for NF_0.01 than ND_0.01 despite the fact that the bubble size obtained for both these cases is nearly the same. In this regard, it should be noted that the evaporation heat transfer rate depends on the rate of bubble growth for the entire ebullition cycle and the cycle time is notably higher (almost 2.5 times) for the nanoparticles-deposited surface (ND_0.01). In overall, total heat transfer rate for the case of NF_0.01 is relatively greater than that obtained for the case of water, but approximately the same with that obtained for the case of NF_0.005 and ND_0.01 within the limits of error bars. 4.1.3.1. Boiling heat transfer coefficient. Boiling heat transfer coefficient (BHTC) is a two phase heat transfer coefficient analogous to that of single phase heat transfer. It is determined by considering natural convection, evaporation and the additional quenching heat transfer rate and has been presented in Fig. 10(b) for all the two sets of experiments. It should be noted that the additional quenching heat flux has been considered here in the calculation of BHTC to justify the magnitude of efficiency of boiling heat transfer phenomenon. Otherwise, the values of BHTC would have been underestimated. The assumption made for determining the quenching component is that its heat transfer coefficient is of the same order of magnitude as that obtained for the natural convection component. In actual case, it would be always on the higher side than the assumed one due to the fact that the departing bubble induces enhanced mixing of superheat layer liquid with the bulk liquid and thus enhances the quenching component. Since the quenching

heat flux could not be measured directly in the present experiments, as discussed in Section 3.2, heat transfer coefficient associated with it has been taken conservatively as the value that is equal to that of the natural convection component. Subsequently, based on the summation of all the three components of heat flux – natural convection, evaporation and quenching, BHTC for a given superheat is obtained. It can be clearly seen in Fig. 10(b) that an increase in BHTC is observed with an increase in the concentration of nanoparticles as well as for the nanoparticles-deposited surfaces. An increment of 5%, 17% and 11% in BHTC is obtained as compared to that of water case for 0.005, 0.01 vol% of alumina nanofluid and ND_0.01 surface respectively. This increment is not that significant as these values are based on single bubble nucleate boiling regime. However, the values of BHTC for the case of water and NF_0.005 are almost same within the limits of error bars and hence it implies that these two working fluids exhibit almost same overall boiling thermal performance. However, NF_0.01 shows noticeable enhancement in the BHTC, which is justifiable based on the observed significant increase in the relative contribution of the evaporative component to the overall heat transfer, as can be seen from Fig. 10(a). Low growth time along with smaller bubble base diameter implies that the sustainability of dry spot remains for a short period of time, thereby causing the rewetting of the surface through the porous layer on a faster basis. This ensures that liquid is in direct contact with the surface in comparison to the low conductivity vapour (the case of water on a plain surface) resulting in an enhancement in heat transfer performance. Based on the heat transfer rates and BHTC, it can be concluded that the NF_0.01 and ND_0.01 cases offer better thermal performance in the context of single bubble-based pool boiling heat transfer phenomenon. Further, it can be inferred that the alumina nanoparticles enhance the single bubble-based boiling heat transfer performance irrespective of the mode through which these nanoparticles are made use of in the boiling process, i.e., either in the suspended form in the bulk fluid or deposited on the heater substrate surface.

5. Conclusions Experimental study to evaluate the performance of water, alumina nanofluids of varying concentration on plain surface and nanoparticles-deposited surface with water as the working fluid was reported in the context of isolated nucleate boiling phenomenon. Nanoparticles-deposited surface was achieved at the end of 0.01% (V/V) alumina-water nanofluid experiment. Real time

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M. Modi et al. / International Journal of Heat and Mass Transfer 146 (2020) 118833

bubble dynamics parameters and the associated thermal gradients fields around the vapour bubble as well as adjacent to the heater substrate were captured simultaneously in the form of schlieren images. Quantitative analysis of these images revealed that bubble dynamics get changed significantly due to the addition of nanoparticles in bulk liquid. The bubble departure diameter was found to reduce with increasing concentration of nanofluids. The cycle time comparison showed that the growth time dominates the cycle for the water case whereas the wait time constitutes the major portion of the ebullition cycle for nanofluids. The overall cycle time was found to decrease significantly for the nanofluids case, thereby leading to an increased departure frequency. Based on thermal gradients and bubble dynamics information, individual contributions of natural convection and evaporation-based heat transfer rates were determined. The findings showed that the nanofluids deteriorate the strength of natural convection component for any given concentration. Whereas, the magnitude of evaporative component increases substantially as one increases the concentration from 0 to 0.01% (V/V). The overall BHTC showed an improvement of around 17% for the case of 0.01% (V/V) nanofluid over the case of water due to the observed dramatic changes in the bubble dynamics parameters. The trends of bubble dynamics parameters and heat transfer rates for the case of water on nano-deposited surface were consistent with that obtained for the case of nanofluids on the plain surface. However, it was noted that though, the overall BHTC was greater than the case of water on plain surface, it is still on the lower side to the case of 0.01% (V/V) nanofluid on the plain surface. The experiments revealed that the alumina nanoparticles, either in suspended form in the bulk liquid or in the deposited form on heater substrate, enhanced the heat transfer performance of single bubble-based pool boiling phenomenon. Declaration of Competing Interest None declared. Acknowledgement This work was supported by Department of Science and Technology (DST), India through the Grant ID RD/0119-DST0000-007. Authors acknowledge the support received from the Department of Science and Technology (DST), India. References [1] A. Dewan, P. Mahanta, K.S. Raju, P.S. Kumar, Review of passive heat transfer augmentation techniques, Proc. Instn Mech. Engrs. 218 (2004) 509–526. [2] J.A. Eastman, S.U.S. Choi, S. Li, W. Yu, L.J. Thompson, Anomalously increased effective thermal conductivities of ethylene glycol-based nanofluids containing copper nanoparticles, Appl. Phys. Lett. 78 (2001) 718–720. [3] S.U.S. Choi, J.A. Eastman, Enhancing thermal conductivity of fluids with nanoparticles, ASME Int. Mech. Eng. Congr. Expo. 66 (1995) 99–105. [4] M. Hamda, M.S. Hamed, Bubble Dynamics in pool boiling of nanofluids, in: 12th Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Canada. [5] C. Gerardi, J. Buongiorno, L.W. Hu, T. McKrell, Infrared thermometry study of nanofluid pool boiling phenomena, Nanoscale Res. Lett. 6 (2011) 232. [6] S.J. Kim, I.C. Bang, J. Buongiorno, L.W. Hu, Surface Wettability change during pool boiling of nanofluids and its effect on critical heat flux, Int. J. Heat Mass Transfer 50 (2007) 4105–4116.

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