Boiling of R134a inside a glass minichannel. A new statistical approach of flow pattern characterization based on flow visualization

International Journal of Heat and Mass Transfer 55 (2012) 1048–1065

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Boiling of R134a inside a glass minichannel. A new statistical approach of flow pattern characterization based on flow visualization Stefano Dall’Olio, Marco Marengo ⇑ University of Bergamo, Dept. of Industrial Engineering, Viale Marconi 5, 24044 Dalmine (BG), Italy

a r t i c l e

i n f o

Article history: Received 1 September 2010 Received in revised form 1 October 2011 Available online 19 November 2011 Keywords: Microfluidics Two-phase flow Flow pattern ITO Boiling

a b s t r a c t A test rig to study R134a flow boiling inside mini and micro-channels has been constructed. The test section is made up of a glass tube and several ITO conductive layers as heaters. A novel image processing technique has been developed for the study of R134a flow boiling regimes. The software routine extracts the bubble contours, measures geometrical features of each frame and collects the data analytically and statistically. The results refer to mass flux between 20 and 122 kg/m2 s and the heat flux between 200 and 45,000 W/m2, at the saturation temperatures of 20–25 °C. The tube inner diameter is 4 mm and the heated length was globally of 320 mm, distributed in eight shorter heaters of 40 mm each. The main goals are the development of a method that, starting from the analysis of several parameters, is able to identify the flow pattern inside the tube, as well as the study of the effects of coalescence on the flow pattern development along the tube. The flow patterns have been identified from a statistical point of view and the ‘‘transition zone’’ has been quantitatively characterized. Part of the analysis is then devoted to the flow pattern variation along the test section. The experiments demonstrated that coalescence is a phenomenon that can be analyzed also in terms of a statistical approach and that the flow pattern variations are not only a function of the mass flux and the quality, but along the tube bubble coalescence and gravity effects have a role in the flow patterns appearance. Ó 2011 Elsevier Ltd. All rights reserved.

1. Introduction The increase of processor miniaturization, higher packing densities of electronic chips, and the engineering of high-end memory devices has led to the development of high power, high heat flux electronics used, for example, by telecommunications, server industries and digital signal processing. The drive toward higher system performances has put a larger demand on forced air convection cooling techniques and is heading toward the thermal limit of such standard technologies. Therefore thermal management is becoming the limiting factor in the development of higher power electronic devices, and to meet future heat transfer demands, innovative methods of thermal control of such components are required. Also for the design of new refrigerators and industrial cooling systems, heat flux correlations are needed also for non-fully developed thermo-hydraulics conditions, especially for small duct diameters. Refrigerants two-phase flows are used in many industrial applications and present various and complex regimes, which depend on the mass flow rate, the channel geometries and the heat transfer ⇑ Corresponding author. Tel.: +39 0352052309. E-mail address: [email protected] (M. Marengo). 0017-9310/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijheatmasstransfer.2011.10.005

values. In such scenario, researches on refrigerant two-phase flows are fundamental to improve the efficiency of the systems mentioned before. Void fraction, flow pattern, and pressure losses are all important parameters to be investigated in two-phase flow experiments. Flow pattern maps developed from flow visualizations are commonly described in the scientific literature, such as in Wojtan et al. [1], Kattan et al. [2], Revellin and Thome [3], Didi et al. [4], Zurcher et al. [5], Mandhane et al. [6], and Baker [7], in order to help the modeling of the two-phase flows. The three main types of two-phase flow regime maps are from Mandhane et al. [6], Taitel–Dukler [8] and the most commonly used called ‘‘Steiner type’’ [9], which depicts sharp boundaries between different flow regimes. The study of Kattan et al. [2] proposes a modification of the Steiner map, which in turn is a modified Taitel–Dukler map [8], and which includes a method for predicting the onset of dryout at the top of the vertical tube in diabatic annular flow. To calculate flow pattern transition curves, six dimensionless geometrical variables were defined. An iterative method is required to find the above dimensionless variables from the geometrical equations presented in [2]. After calculating them, the flow pattern transition curves can be determined for defined properties of the fluid.

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Nomenclature b

rM r2 A D Dext Dh Din fmin g G h hs hi hin hLV IITO j jj L LITO Lobs _ M _ ref m N Npx,y P PITO Q_

Rmax/Rmin of each bubble standard error of the mean variance of the measure area [m2] internal diameter of the channel [m] external diameter of the channel [m] hydraulic diameter [m] internal diameter of the channel [m] minimum frame rate acceleration of gravity [m/s2] mass flux [kg/m2 s] enthalpy [J/kg K] height of one slice [m] height of the bubble [m] enthalpy of the fluid at the inlet [J/kg K] latent heat of vaporization [J/kg K] electrical current intensity [A] superficial velocity [m/s] drift flux [m/s] length of the channel [m] ITO coating length [mm] observation length [m] mass flow rate [kg/s] refrigerant mass flow rate [kg/s] total number of bubbles in one video number of pixel in the y-dir wetted perimeter [m] heating power [W] volumetric flow rate [m3/s]

Kandlikar [10] asserts than three flow patterns are commonly encountered during flow boiling in minichannels: isolated bubble, confined bubble or plug/slug, and annular flow. Many others have observed these three basic flow patterns [11,12]. In Kandlikar’s opinion the literature on flow patterns in microchannels is insufficient to draw any conclusions, even if it is possible to underline that the effect of surface tension is quite significant, causing the liquid to form uniformly spaced small slugs filling the tube, sometimes forming liquid rings. In his important review in 2006 Thome [13] asserts that at very low mass velocities the two-phase flow in microchannels approaches capillary flow as a natural limit, where all the liquid flow is trapped between a pair of menisci with dry wall vapor flow in between; no stratified flow is observed in microchannels due to the predominance of surface tension over gravity forces, so that the tube orientation has negligible influence on the flow pattern. In the work of Wojtan et al. [1], several important modifications to the flow pattern map of Kattan–Thome–Favrat [2] were added, resulting in a noteworthy new version of the map. Based on the dynamic void fraction measurements described in [14], the stratified-wavy region has been subdivided into three sub-zones: slug, slug/stratified-wavy, and stratified-wavy. Furthermore, annularto-dryout and dryout-to-mist flow transition curves have been added and integrated into the new flow pattern map, identified by distinct trends of the heat transfer coefficient – as a function of vapor quality – and by the flow pattern observations, in order to determine (and then predict) the inception and completion of dryout in horizontal minitubes. New transition curves have been found to define annular– dryout and dryout–mist flow transitions based on their new heat transfer measurements and observations. Ribatski et al. [15] underline that bubbly flow is seldom observed due to the fact that its lifespan is very short as bubbles

q0 (z) q Q RITO Rb r Re T t Tref Tsat Vb Vc VITO Vj W x(z) x Dtfr Dx

q qb s e

heat input from unit of length [J/m2] heat flux [W/m2] power entering the test section [W] electrical resistance [X] mean radius of one bubble [m] resolution Reynolds number temperature [°C] thickness of the ITO coating [lm] reference temperature [°C] saturation temperature of the fluid [°C] volume of one bubble [m3] volume of the observed channel [m3] voltage [V] drift velocity of the vapor phase [m/s] circumference of the tube [m] vapor quality at the z axial position vapor quality time interval between frames [s] length of an interval [m] density [kg/m3] bulk resistivity (X m) shape parameter for the bubble void fraction

Subscripts L liquid phase V vapor phase

coalesce or grow to the channel size very quickly. The three-zone heat transfer model proposed by Thome et al. [16] illustrates the strong dependency of heat transfer on the bubble frequency, the lengths of the bubbles and liquid slugs and, the liquid film thickness. For these reasons, it is opportune to apply an optical measurement technique to quantitatively characterize flow pattern transitions and to measure the frequency, velocity, and length of vapor bubbles in microchannels, in particular at the exit of microevaporators where the flows are formed. So the best approach is to use a quantitative mean to identify flow patterns, for which various techniques are available; one is the two laser/two diode optical technique developed by Revellin et al. [17] for microchannels. In [17] the tests were run in a 0.5 mm glass channel using saturated R-134a at 7.7 bar; the optical technique used two laser diodes and photodiodes to measure the parameters described above and to identify the flow regimes and their transitions. Four principal flow patterns (bubbly flow, slug flow, semi-annular flow and, annular flow) with their transitions (bubbly/slug flow and slug/ semi-annular flow) were observed in these experiments and it is evidenced that the thin film surrounding the bubbles becomes more uniform as the diameter decreases, giving evidence that buoyancy may have a role. In 2007 Revellin and Thome [18] described experiments of flow visualization of R-134a and R-245fa inside 0.5 and 0.8 mm diameter pipe. They observed four principal flow patterns (bubbly flow, slug flow, semi-annular flow, and annular flow) with their transitions (bubbly/slug flow and slug/semi-annular flow). The higher the mass flux, the earlier annular flow arises, while bubbly flow tends to disappear at high mass flux because small bubbles quickly coalesce to form elongated ones. The flow pattern transition has been shown to be dependent on the coalescence rates and, because the observed transitions do not compare well with the existing macroscale flow maps both for refrigerants and for air–water

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flows, a new type of flow pattern map for evaporating flow in microchannels has been considered necessary. This model has been proposed by Revellin and Thome in [19]. They again categorized the microscale flow patterns observed in the classical manner: bubbly flow, bubbly/slug flow, slug flow, slug/semi-annular flow, semi-annular flow, and annular flow. Two-phase flow pattern observations were done based on the above categories. The transitions are controlled primarily by the rate of coalescence, and this is in contrast with the previous flow pattern maps. They proposed three classes of regimes, such as the isolated bubble, the coalescing bubble, and the annular flow. All regimes were also observed by Ong and Thome [20], with the addition of mist flow at very high vapor qualities. Considering the approach with which flow pattern maps have been evaluated, probabilistic two-phase flow regime map first obtained by Nino [21] for refrigerant. Air-water flow in multi-port microchannels was statistically described by Jassim and Newell [22] to eliminate the discontinuities created by traditional flow maps. Generally probabilistic two-phase flow regime maps have quality on the horizontal axis and on the y-axis the fraction of time in which a particular flow regime is observed in a series of pictures taken at a given flow condition. Jassim and Newell [22] developed fit functions to represent Nino’s 6-port microchannel time fraction data that are continuous for the entire quality range. Jassim and Newell then utilized the probabilistic flow regime map time fraction curve fits to predict pressure drop and void fraction. The difficulty with the probabilistic flow map based modeling technique is that large numbers of pictures must be classified for each flow condition in order to create a large amount of data necessary to generalize the time fraction functions with respect to refrigerant properties and flow conditions. 1.1. The research strategy A new test rig was built to study R134a flow boiling inside mini and micro-channels. The experimental apparatus allows to visually investigate the two-phase flow also in the diabatic zone of the test section and not just in the adiabatic. To obtain such results Indium Tin Oxide (ITO) coatings are used as electrical heaters. ITO thin film has attracted interest because of its characteristics of high optical transmittance over the visible wavelength region, and excellent adhesion to glass substrates. The test section is the most innovative part of all the system and is made up of a glass tube and is heated by a number of Indium Tin Oxide (ITO) conductive layers, distributed along the entire length of the outer surface of the tube. Thanks to the choice of ITO layers [23,24], it is possible to visually analyze the phenomena and mechanisms governing the boiling process, such as bubble nucleation, bubble growth, departure, and bubble lift-off, and to improve the understanding of the transition lines in flow pattern maps. The main measurement tool is the high-speed flow visualization, which is used to acquire the data to create the flow pattern maps. This technique will allow identifying the boiling process with high accuracy even at the microscale level. It is possible to observe several phenomena connected to the bubble formation process. The present is among the rare researches presenting an experimental analysis of refrigerants boiling phenomena in horizontal minichannel heated with a transparent coating system, and visualized with a high speed camera. It is important to underline that in the actual state of the art, there are no studies regarding the basic physical phenomena that take place at the onset of flow boiling, because the most common

heaters consist of a metallic tube connected to an electrical generator that provides the thermal power to the fluid by the Joule effect. The complexity of identifying flow regimes and their transitions comes from the difficulties in obtaining good high speed images, in the interpretation of the flow (subjectivity and pattern definition depending on the author), and also in choosing the channel size that determines either macro or microscale or the transition between them. From the visualization point of view, a new image processing technique based on a routine created inside the commercial code Image ProÒ Plus has been developed and applied to the study of R134a two-phase flow inside mini and micro-channels. The new image processing technique has been developed to perform visualization of forced convection saturated R-134a boiling in a horizontal glass mini tube. Compared to the other two main optical flow pattern identification methods, the first developed by Revellin and Thome [25] based on a frequency analysis of the light signal from a laser–diode system, Newell and Jassim [26] more focused on the development of an image based recognition software image analysis, the present method is easier and therefore a wider range of flow patterns can be rapidly analyzed. In their study Revellin and Thome [25] used an optical measurement method to characterize flow pattern transitions of two-phase flow in micro-tubes. It consists of shining two micro laser beams through a glass tube and the fluid at two different locations, using two lenses to focus the laser beams to the middle of the microtube, and using two photodiodes to recuperate the intensity of the light, whose signals are used to distinguish whether liquid, vapor, or liquid and vapor are present in the cross section. Bubble frequency, lengths of bubbles, and flow pattern transitions are parameters that are able to be determined by this technique. Mean vapor velocity is also calculable from the measurements at some test conditions. Four principal flow patterns (bubbly flow, slug flow, semi-annular flow, and annular flow) with their transitions (bubbly/slug flow and slug/semi-annular flow) were observed in the present experiments with R134a and R-245fa in 0.50 mm and 0.80 mm circular channels. Many observations have been made on the transitions between flow regimes. The two-phase flow pattern transitions observed with R-134a did not compare well to a primary macroscale flow map for refrigerants nor to a microscale map for air-water flows. No significant influence of the inlet subcooling nor the saturation pressure has been observed on the flow pattern transitions. A shorter heated length did not influence the locations of the transition lines. The diameter effect did not show any difference, although bubbly/slug flow is present over a wider range of mass flux. Jassim–Newell–Chato [26] obtained experimentally probabilistic two-phase flow map for R134a at 25.0, 35.0, and 49.7 °C, R410A at 25.0 °C, mass fluxes from 100 to 600 kg/m2 s1, qualities from 0 to 1 in 8.00, 5.43, 3.90, and 1.74 mm ID. The weak points of these two works are the non constant effectiveness of the method to all he flow regimes in the first case, and the complexity and statistical uncertainty of the method reported in the second work. The originality that is at the basis of the new classification method presented in this paper is an attempt to overcome the limits of the past works, presenting a more effective and objective way to analyze and classify the flow patterns. Furthermore till now the flow pattern classification has been accomplished mostly subjectively, sometimes being not possible for the researchers to compare their results, and in many cases some author stressed the importance to reach a way of flow

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pattern identification that could be as objective as possible and not based on the subjectivity of the scientist. This work presents an objective classification technique, and the parameters that are at the basis of the identification will be analyzed statistically in order to understand the efficiency of the model, to optimize the values and to validate the results. Moreover, a detailed statistical analysis has also been carried out in order to decide the number of samples needed for a flow characterization and to validate the classification itself. Finally a special attention was devoted to the incipient boiling process, i.e. the analysis of the flow characteristics for very low values of the vapor quality, since the transparent heater is allowing the visualization of the bubbles originates at the nucleation sites on the glass surface. 2. Macro to microscale transition in two phase flow Since the flow patterns are strictly dependent on the scale of the flow considered, it is necessary to give a classification of the micro to macroscale transition. While in single phase heat transfer the threshold between microscale and macroscale can be determined on the basis of scaling effect, in flow boiling the transition between micro- and macroscale has not been very well defined. In fact a universal criterion for the definition of micro-macro transition does not yet exist. Just to give some indications about the importance that such distinction has in the literature, some references of the most important criterions are reported in the following. In [27] a classification for the transition from macroscale to microscale heat transfer based on the hydraulic diameter Dh is proposed. The size ranges recommended by Kandlikar are: microchannels (50–600 lm), minichannels (600 lm to 3 mm) and conventional channels (Dh > 3 mm). Such criterion does not reflect the influence of channel size on the physical mechanisms, as the effect of reduced pressure on bubble sizes and flow transitions and does not take in consideration the properties of the test fluid and should be rejected as too rough. Thome et al. [28] suggested that confined bubble flow is the threshold criterion beyond which macroscale theory is no longer applicable. A more general macro to micro criterion should address the limit where classical theory is no longer fully applicable with respect to the two-phase flow and heat transfer processes. Such transition criterion might be related to the bubble departure diameter, which is defined as the point at which the bubble departure diameter reaches that of the flow channel, such that further growth is confined by the channel and only one bubble can exist in the channel cross-section at a time. As already remarked Thome et al. [28], we assume that the macro to micro transition starts when the diameter of a growing bubble reaches the internal diameter of the tube before detachment and then only grows in length as it flows downstream. Rigorously the microscale should be defined as a given scale or a given characteristic length keeping into account also the physical properties of the fluid. Under such given size, some of the usual physical phenomena in macroscale (i.e. in a bigger scale) should change. Therefore it could be useful for example the so-called capillary length lc:

lc ¼



r

12

gðqL  qV Þ

:

The most recent criterion to identify the threshold has been recently proposed by Ullmann and Brauner [29] on the basis of flow pattern maps, using the dimensionless Eötvös number, Eo:

Eo ¼

gðqL  qV ÞL2

r

:

On the basis of flow pattern map deviation for experiments in pipes, Ullmann and Brauner proposed a microscale threshold of Eo 6 1.6.

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It has been already remarked that though starting from a less physical viewpoint, Kew and Cornwell [30] have proposed the confinement number, Co, as an alternate parameter, assuming microscale flow when Co > 0.5. Note that Eo 6 1.6 means Co P 0.79. For the same fluid, i.e., R134a, at the saturation temperature of 0 °C, the two criteria yield the transition between micro- and macroscale of 1.21 mm [29] and 1.92 mm [30], respectively. Rewriting all the above criteria in terms of the Eötvös number, it is found that Kew and Cornwell [30] criterion corresponds to Eo = 4, the Li and Wang [31] threshold to macroscale equals to Eo = 3.06 and the Cheng and Wu [32] classification to Eo = 3. As concluding remarks of this macro to micro section, it is necessary to underline that in flow boiling there are effects that have still to be investigated and analyzed in detail, like: bubble confinement, the prevalence of surface tension over buoyancy and the importance of inertial forces in the forces balance. In spite of the micro-to macroscale threshold has been associated with bubble confinement, a more refined correlation is necessary for a better and more universal definition of the transition from macroscale to microscale. 3. Experimental setup 3.1. The experimental test rig A detailed description of all the components of the test rig, together with the explanation of the constructive choices, is reported in [33]. A schematic view of the experimental apparatus is also given in Fig. 1, while in Fig. 2 there is a scheme of the instrumentation used. The set-up runs with R134a and consists of two main loops: the test section loop and a secondary loop, where the fluid is thermally controlled and the vapor formed in the test section is condensed. A helix type heat exchanger is inserted into an external cooling unit, which maintains propylene glycol at a constant pre-imposed temperature (down to 40 °C). This unit is necessary to define the fluid operating experiment temperature and to condense the fluid coming from the test section as wet vapor. The fluid is pumped by a Cole-Parmer Gear MicropumpÒ able to provide a maximum flow rate of 2 l/min without fluid contamination and with a very regular flow. A start-up procedure, consisting on closing the test loop and circulating the fluid into the secondary loop, is necessary. This procedure is necessary to assure all the fluid inside the tank at the desired pressure and temperature, in general between 0 °C and 30 °C. The mass flow rate can be adjusted by working on the microregulation valve positioned at the inlet of the test section, by closing the bypass valve or by changing the pump speed, so that the resulting flow rate is a consequence of the interaction of the regulation of these features. After these steps, being all the system at the required condition, it is possible to open the test section loop and heat the fluid inside the test section, visualize and record the images coming from the high speed camera and acquire and store the data coming from the sensors. 3.2. The transparent test section The test section consists of a high precision glass (DURAN) tube, with the possibility to use internal diameters tubes ranging from 4 to 0.4 mm and lengths typically from 1000 to 500 mm. The heating system consists of ITO (Indium Tin Oxide) coatings on the outer surface of the tube. The coated tube is enclosed in a co-axial vacuum chamber made by a glass tube of larger diameter which has the aim to eliminate,

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Fig. 1. Experimental test rig scheme.

Fig. 2. Test section instrumentation scheme.

in the global heat transfer rates, the convection losses and consider only the radiation losses from the test section to the environment (Fig. 3). The convective and radiative heat losses have been evaluated by the application of the 2D standard heat transfer theory to the system under study. The detailed procedure of the calculation and the estimation of the error committed are reported in [33]. Thanks to the versatility of the whole system it is possible to easily change the tube of the test section with smaller internal diameter tubes and different distribution of the coating length. The present system can work with tubes with an internal diameter from 4 to 0.4 mm, and with heat fluxes from 0.5 to 300 kW/m2. The vacuum deposited ITO film is used to electrically heat the outer surface of the test section tube, allowing the observation of the boiling mechanisms taking place inside the tube. In the present test section, the internal diameter of the glass tube is 4 mm and there are eight heaters on the outer surface of

the glass tube, making it possible to reach heat fluxes from 2 to 40 kW/m2. The number of ITO layers coated on the test section tube has been chosen according to the total final amount of heat power that could be given to the flow, and to the possibility to regulate in a more precise way the power provided. In this way low vapor quality flows are easily obtained and a slow and precise increasing in heat flux is obtained. 3.3. The heating layer Indium Tin Oxide layers with variable lengths, characterized by a mean electrical resistance of 50 X/square have been coated on the outer surface of the test section glass tube (Fig. 4). Typically, the ranges of the final electrical resistance of each heater is between 130 and 150 X. ITO thin films are electrically

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Fig. 3. Schematic view of the basic unit of the test section: the glass tube, the heaters and the glass chamber that encloses the tube.

From Ohm’s law

V ITO ¼

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi PITO  RITO ;

ð3:2Þ

where VITO is the voltage and PITO is the heating power. Therefore, for a given heating power PITO, to minimize the required voltage potential VITO to safe and practical levels, RITO needs to below. 3.4. Data acquisition devices

Fig. 4. Image of the test section showing the electrical wires that provide power to the ITO heaters and the white connectors that fix the wires at the borders of the coating.

conductive and have the characteristics of high optical transmittance (in our case around 85%) over the visible wavelength region, and excellent adhesion to glass substrates. Indium Tin Oxide is a conductive oxide that has the benefit of being simultaneously electrically conductive and transparent to visible light. For these reasons, ITO layers have been used as electrical heaters, being able to provide the thermal energy to the glass tube thanks to the Joule effect. When ITO is vacuum deposited on an appropriate transparent surface it provides the opportunity to observe – from a new perspective – boiling through the electrically heated surface. The resistivity of a coating is inversely proportional to its thickness, since the layer has a bulk resistivity qb (X m) and final resistance RITO (X) which are found from:

RITO ¼

q  L  b

t

W

;

ð3:1Þ

where L, W, t are, in the case of a tube, the axial length, the circumference and the thickness of the coating, respectively. It is important that the coating has a final electrical resistance that is low enough to ensure that sufficient power can be applied to the surface with practical, readily available power supplies.

To control the flow characteristics at the inlet and outlet of the test section, at the entrance of the test section a rotameter that measures the flow rate till a maximum value of 5.5 kg/h was positioned, together with a micro-regulation valve, which is needed to have a very precise regulation of the flow and to stabilize the flow itself. Subsequently the refrigerant inlet temperature and its relative pressure are measured in sequence respectively with a K-thermocouple and the pressure sensor SMC-PSE510. Between the entrance and the exit of the test section, a differential pressure meter is positioned to measure the pressure drop during the flow boiling. Thermocouples are positioned sidely on the ITO coatings and on the outer surface of the glass tube at the exit of the test section. To obtain the values of the temperature for the other heaters, a routine has been created. Starting from the values of power and corresponding temperature at which the first heater is working, the routine calculates the value of the temperature of each heater considering a direct proportional governing law between temperature and power. ITO coatings power is controlled by the PC through several NIÒ (National Instrument) USB-6008/9 acquisition and control devices, and a specifically designed electronic boards (one for each heater), which are supplied with a 56 V DC power supplier, as sketched in Fig. 5. Every electronic board applies the correct value of voltage to each heater in order to reach the desired electrical power and amplifies the coating voltage and current signals adequately, so that these can be acquired by the data acquisition module and transmitted to the PC. Thermocouples signals are acquired using the HP-Agilent 34970 Data Acquisition Switch Unit, which has specific modules for thermocouples measurements. With regards to the software, a dedicated LabVIEWÒ program has been written to manage the data flow and the system control. The power on the ITO coatings is controlled with a standard PID (proportional–integral-derivative) control, which is easy-to-handle and adaptable to all different coatings, with no need for specific tuning.

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after the introduction of more power in different positions along the tube. The flow maps can be hence defined at different distances from the incipient boiling position. 3.6. Error analysis 3.6.1. Diameter As reported in [33], the test tube is made of DURAN glass. The tube diameters are given with the accuracy by the glass producers:

Dint ¼ 4  1%; Dext ¼ 6  2%: Fig. 5. Experimental set-up acquisition scheme.

Furthermore, a sub-module estimates the heat losses due to heat conduction and radiation to the tube. All the most significant thermo-dynamical data are acquired with a frequency of around 20 Hz, which is considered adequate for stationary flow. The data are periodically averaged (1 Hz), so that mean values (and optionally standard deviations) are available and stored for the post-processing. 3.5. The experimental condition and flow visualization During experiments the configuration of the test section is showed in Fig. 6. As shown in the pictures, there are three main components working simultaneously to perform the heat transfer measurements and the visualization experiments. The high-speed camera (PCO 1200HS, 636 fps at full resolution, 1280  1024 pixel) allows the recording of videos of the flow configuration inside the test section, both in the diabatic and in the adiabatic zones. Usually the camera works at a speed of 1000 frames/s to have well defined bubble contours in the videos. As luminous source two continuous current lamps of 65 W are used. An infrared filter together with a diffuser glass is used to avoid light spots and the thermal radiation from the lamp. The camera is fixed with a specific support on a semi-circular structure to ease its movement around the test section and to acquire images from different angles with respect to the horizontal plane, requiring only small regulations on the focus. It must be underlined that the present technique, thanks to the completely transparency of the test section, allows studying the evolution of the flow pattern just at the incipient boiling and also

3.6.2. Coating/evaporator length The length of each ITO coating can vary for less than 1 mm for each side. This means:

DLITO ¼ 4%: The standard coating length is equal to 40 mm. 3.6.3. Pressure drop measurement accuracy The PSE pressure transducer is used to measure the pressure at the inlet of the test section. It is connected to a National Instrument USB 6008 device. During the experiments the pressure range is between 4 and 8 bar. This means:

Pmin ¼ 4 bar  2%; Pmax ¼ 8 bar  1:25%: 3.6.4. Mass flux measurement accuracy The definition of the mass flux G is:

G¼

_ 4m

pD2int

;

_ is the refrigerant mass flow rate. where m The mass flow rate measurement accuracy is:

_ ¼ 1 kg=h  6%; m _ ¼ 5 kg=h  3%: m With the present configuration the mass flux ranged from 22 to 110 kg/m2 s, which means that the uncertainties are:

G ¼ 22 kg=m2 s  6:3%; G ¼ 110 kg=m2 s  3:5%: In fact the flow rate may oscillate, but it was not possible to establish the amplitude and the frequency of such variations. 3.6.5. Temperature measurement accuracy All the thermocouples are K-type (Chromel–Alumel) and have been made specifically by the Research center ENEA (Dr. Gianpietro Celata). They are connected to a Agilent acquisition system and they were calibrated to have an absolute error of 0.4%/°C. Being the range of fluid temperatures in experiments between 10 and 30 °C, it is possible to conclude that:

DT ¼ 0:1 K: 3.6.6. Power supply measurement accuracy The electrical power supplied to the ITO coating is calculated from the measured value of voltage and current: Fig. 6. Image of the test section, where it is possible to notice the high speed camera (1), the light source (2) and the test section (3).

PITO ¼ V ITO IITO :

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Fig. 7. Visualization window aspect for different situations.

As DV/V = ±0.28% and DI/I = ± 0.87%, it results:

Quality-mass flux map of the experiments performed 140

DPITO ¼ 0:91%PITO : 3.6.7. Heat flux measurement accuracy The contribution of the power, diameter and the coating length are ±0.91, ±2% and ±4%, respectively. Heat fluxes ranges from 2 to 40 W/m2 K. The resulting uncertainties are:

qlow ¼ 2 kW=m2  4:6%; qhigh ¼ 40 kW=m2  4:6%: 3.6.8. Vapor quality measurement accuracy The vapor quality is calculated at the outlet of a certain evaporator corresponding to the z axial position. Considering for example a Tref of 20 °C (at which hLV = 182 kJ/kg) and a total power of 20 W, the result is:

xðzÞ ¼ 0:395  6:1%

_ ¼ 1 kg=h; at m

_ ¼ 5 kg=h: xðzÞ ¼ 0:079  3:1% at m 4. Experimental results 4.1. Statistical dataset The first part of the experiments regarded the two-phase flow with a vapor quality between 0 and 0.8. Seven mass fluxes have been considered, from 20 to 120 kg/m2 s, and in some experiments more than one heater has been turned on in order to reach a total power to the fluid higher than the 20 W achievable by one single heater. In Fig. 8 all the points analyzed are represented in the mass flux–vapor quality diagram. Around 120 videos and 60,000 frames have been analyzed. The recording position along the axial dimension of the tube varies according to the total power provided to the flow. Being each heater able to provide maximum 20 W, for higher value of power supplied more than one heater must work, and consequently the camera must be positioned after the last heater that is working.

Mass Flux, kg/m 2 s

120 100 Second set of experiments

80

First set of experiments

60 40 20 0 0

0.2

0.4 0.6 Vapour quality (x)

0.8

1

Fig. 8. Mass flux vs. vapor quality map showing the experiments performed during the thesis.

The aim of the experimental campaign was to define which of the dimensional bubble characteristics could be more suitable and reliable for the flow pattern identification. The second part of the experiments was focused on the bubbly flow regime (vapor quality between 0 and 0.025). This choice is due to the fact that the incipient boiling/bubbly flow region (compared to the elongated bubble and to the stratified flow regimes) is the most interesting both for the visualization and for the heat transfer coefficient evaluation. Actually, not many scientific data exist in the literature for the incipient boiling, and none from the visualization side for flow boiling conditions. In order to study the evolution of the flow pattern and the flow pattern transition along the tube, videos have been recorded in three different positions of the tube as shown in Fig. 9: after the first heater, in the middle of the glass tube (around 30 cm ahead) and close to outlet of the glass channel (70 cm ahead).

4.2. Flow morphology In the experiments, a large range of the possible flow conditions was observed and classified. The two extreme situations are represented by the condition of (1) very small bubble nucleated at the wall of the first heater and (2) the stratified flow in which the

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Fig. 9. Three position along the tube at which the video to study the evolution of the flow pattern have been recorded.

upper part of the channel is occupied by the vapor phase and the lower by the liquid. Considering the observation window, the image analysis steps of a bubble inside the tube are represented in Fig. 7. As it can be seen watching the window from the right to the left, the bubble enters in the observation window, and, after several steps, it is inside the observation window with all its shape. Considering the data acquisition, the information relative to this entering period are not recorded, otherwise it would be very difficult to distinguish the reasons of data deviation, that could be also due to the fact that not the entire bubble is considered in the analysis, and giving for this the impression that the bubble is smaller. Then, frame by frame the bubble is completely included in the camera window. If the bubble is small, with its main size of the same order of the tube diameter, the entrance conditions do not influence so much the statistical analysis. On the other hand, in case of an elongated bubble, a larger deviation of the values recorded is introduced and a higher number of videos must be collected. In fact if the bubble elongation is important, the two-phase flow seems to be fully stratified for a long sequence of images, and only when the bubble backside come into the observation window is possible to detect the true flow regime. For such reason, in the study of the bubble parameters, those frames in which a whole bubble is not visible inside the observation window, have been rejected in a part of the statistical analysis (see below). In order to characterize the flow pattern inside the minichannel, four standard parameters have been considered: the equivalent diameter, the aspect parameter (s), the void fraction and the slip velocity.

All the parameters have been calculated by processing the images obtained by means of the high speed camera, with the first three that have been evaluated in two ways: first considering all the frames, even those where the whole bubbles did not appear, and a second way considering only the frames in which the bubbles appeared with their whole contour. In this last case, the frames without a complete bubble have been rejected and a ‘‘rejection ratio’’ has been calculated as the ratio between the number of the rejected frames and the total number of frames containing bubbles. In Fig. 10a an example of a rejected frame is shown, the two bubbles are partly out of the frame, while in Fig. 10b bubble 2 is complete and the frame is not rejected. The value of the rejection ratio can be used to estimate the statistically correct time length of frames to be recorded: a high value of the rejection ratio means in fact that many bubbles are not entirely contained in the frame and that the time length of observation must be increased. 4.3. The equivalent diameter This parameter is obtained from the bubble area, assuming an originally spherical shape. This hypothesis is sometimes far from the reality, but the equivalent diameter is a useful tool to compare the bubbles. The equivalent diameter is given by

Di ¼

rffiffiffiffiffiffiffi 4Ai

p

;

where Di is the diameter of the ith bubble and Ai is the area.

Fig. 10. (a) Example of a rejected frame. (b) Example of an accepted frame.

ð4:1Þ

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Fig. 11. Scheme of the quantities used to calculate the void fraction.

of the frame. The second one is the 3D void fraction, obtained as the ratio between the volume of the bubble and the volume of the frame, i.e. the volume of the part of the channel observed. The volume of the bubble has been evaluated as follows: the length of the frame has been divided in N smaller intervals:

Dx ¼

Lobs : N

ð4:2Þ

In this way also the bubble is divided in ‘‘slices’’, each of them is long Dx and has a volume given by

Vs ¼

p 4

2

Dxhs ;

ð4:3Þ

where hs is the height of the slice. The total volume of the bubble is

Vb ¼

p 4

Dx

Npx X

2

hi ;

ð4:4Þ

i¼1

while the volume of the frame is the internal volume of the portion of the channel observed:

Vc ¼ Fig. 12. Cyclic procedure to perform the flow pattern identification of several images.

4.4. Void fraction

4

D2i Lobs :

ð4:5Þ

The resolution r is the ratio between the internal diameter and the number of pixels along y

r¼

The void fraction is an index that gives an idea of the percentage of area of the frame that is occupied by the bubbles, and two types of void fraction have been calculated. The first one is the 2D void fraction, obtained as the ratio between the area of the bubbles in the frame and the whole area

p

Di ; N px;y

ð4:6Þ

and it gives the number of millimeters covered by each pixel so that the real dimensions of the objects in the frame can be obtained. We can now define the height of the bubble as

hi ¼ Nb r;

Fig. 13. Effect of the automatic image analysis steps visible in a frame.

ð4:7Þ

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where Nb is the number of pixels that correspond to the bubble along y in the ith Dx interval. In a similar way we can define the length of observation:

Lobs ¼ N px;x r;

ð4:8Þ

where Npx,x is the number of pixels along the x direction. Finally the void fraction is given by the ratio of Eqs. (3) and (4)

VF ¼

p DxPNpx;x h2 i¼1

4

p D2 L i

4

¼

i

p Lobs

¼

4 N px;x

obs N px;x X

Npx;x N2px;y

1¼1

i¼i

p D2 L 4

1

PNpx;x i

N2b r2

obs

p Lobs

¼

4 N px;x

PNpx;x i¼i

D2

N2b N2 i

px;y

p D2 L 4

i

obs

N2b ;

ð4:9Þ

where hi is the height of the bubble, Di is the internal channel diameter, Npx,x and Npx,y are respectively the number of pixels in the x and y direction and Nb is the number of pixels of the bubble for each column of the frame. In Fig. 11 a bubble and the quantities described above are shown. 4.5. The aspect parameter (s) To define the aspect parameter we first introduce b as the ratio between the maximum and the minimum diameters of the bubble:

b¼

Dmax : Dmin

ð4:10Þ

And consequently the aspect parameter is given by

s¼

Dmax  Dmin b  1 ; ¼ b Dmax

ð4:11Þ

and s is equal to zero when b = 1, i.e. when the bubble is spherical. 4.6. The slip velocity The ratio between the velocity of the bubble and the average velocity of the fluid is called slip velocity. The velocities of the front and of the back of the bubbles can be calculated as follows:

Fig. 15. Void fraction as a function of the vapor quality and the mass flux. Fluid: R134a, D = 4 mm, Tsat = 22 °C, G = 20–120 kg/m2 s.

Fig. 14. (a) Relationship between pixels and the unit length; and (b) zoom on the bubble contour during the segmentation process in order to find the relative error of the area measurement.

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xf;k;iþ1  xf;k;i ; Dt fr xb;k;iþ1  xb;k;i ; Vb ¼ Dt fr Vf ¼

ð4:12Þ

where xf,k,i+1 and xf,k,i are the positions of the front of the bubble k in the (i + 1)th and ith frames respectively, while xb,k,i+1 and xb,k,i are the positions of the back of the bubble in the same frame, and Dtfr is the time interval between the frames. On the other hand, the average velocity is given by the ratio between the volume flow rate and the area of the cross section of the tube, and since we are in presence of a two-phase flow the density of the fluid has been calculate according to the homogeneous model:

1

q

¼

1 ; ð1  xÞql þ xqv _ m

v¼

qA

;

ð4:13Þ

ð4:14Þ

where x is the vapor quality, ql and qv are respectively the liquid _ is the mass flow rate and A is the cross secand vapor densities, m tional area of the channel. The slip velocity can be used to calculate the minimum frame rate needed to detect each bubble: if Dmax is the average length of the bubbles and V b the average speed we can say that

Fig. 16. Void fraction as a function of the vapor quality and the mass flux. Fluid: R134a, D = 4 mm, Tsat = 22 °C, G = 20–120 kg/m2 s.

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Dtmax ¼ DVmax is the maximum time interval between frames, and b fmin ¼ Dt1max is the minimum frame rate.

5. The image analysis technique 5.1. The automated bubble recognition routine Several routines have been developed within the commercial code Image-ProÒ Plus 4.5.1. The software has been used to automatically perform the image analysis of a selected number of frames from a recorded video, and to give the final result of a statistical description of the two-phase flow patterns. The main routine steps are shown in Figs. 12 and 13 and can be summarized as follows: starting from a number of frames selected by the user and taken from a video sequence, the routine analyzes each of the frames, it stores the measured data to a pre-structured file, and then it gives as final output the identification of the most probable flow pattern of the flow. Before running the routine, a spatial calibration has been run. The main geometrical data of the objects identified in the active window such as bubbles diameter, area and main axis lengths are collected and stored for post-processing purposes in text files. To show the operations performed on an image, a real case is reported in Fig. 13. From the input image (a), the area of interest (b) is extracted, then the image is cleaned (c) and the data acquisition occurs (d and e).

Fig. 17. Void fraction as a function of the vapor quality and the mass flux. Fluid: R134a, D = 4 mm, Tsat = 22 °C, G = 20–120 kg/m2 s.

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The number of frames taken into account in the analysis has been chosen a priori according to some tests of reliability and repeatability performed at the beginning of the experimental campaign. In order to obtain an excellent quality for the results, a number of 500 frames for each movie was chosen. 5.2. Automatic flow pattern identification One of the novelties of the work is the attempt to obtain a method that is able to provide an objective, fast and automated way to perform the flow pattern characterization of a two-phase flow. This method has flow visualization and two phase flow image recording has its key elements. The data files obtained by the application of the frame analysis are then processed to extract the parameters that will be at the basis of the flow regime classification. The statistical classification is based on the four parameters presented above. Differently from other researches [22] where the classification was mainly based on the deformation of a black lines mask positioned on the test section tube, in the present case the discriminating criteria are both based on the physical characteristics of the flow regime and on statistical features. It must be underlined that the statistical analysis improves the flow pattern classification, because it is defining the accuracy of the main discriminating physical criteria.

Fig. 18. Dimensionless bubble diameters as a function of the vapor quality and the mass flux. Fluid: R134a, D = 4 mm, Tsat = 22 °C, G = 20–120 kg/m2 s.

5.3. Statistical tools to operate and validate flow pattern identification This paragraph reports about the method allowing the flow pattern identification and about the procedure that will be used for the discriminating parameters. As an example, in order to explain the procedure, the diameter of a single bubble is considered as discerning parameter, and the steps of the analysis are the same for all the parameters. The equivalent (or nominal) diameter of each bubble contained in one frame is defined in 3.1 Then it is possible to evaluate the mean and the variance of Di in one movie as:

D¼

N 1X Di ; N i¼1

r2 ¼

N 1 X ðDi  DÞ2 ; N  1 i¼1

ð5:1Þ

ð5:2Þ

where D is the mean diameter of the bubbles in a movie, N is the total number of bubbles in the video and r2 is the variance. The difference among flow regimes is defined by the different values of D, and the value of r allows the calculation of the standard error of the mean (indicated as SEM)

r rM ¼ pffiffiffiffi ; N

ð5:3Þ

Fig. 19. Dimensionless bubble diameters as a function of the vapor quality and the mass flux. Fluid: R134a, D = 4 mm, Tsat = 22 °C, G = 20–120 kg/m2 s.

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which allows to evaluate quantitatively the transition regions by means of the 3r criteria. 5.4. Error in the bubble identification process During the bubble identification process it is possible to commit an error due to the gray intensity threshold set to identify the contour of the bubble itself. The magnitude of this error has been evaluated considering the bubble identification process in the two extreme conditions for the recognition: the threshold for the bubble identification was first set to the value of the darkest limit (boundary level 1) and then to the highest value that allowed the detection. The inaccuracy of the bubble contour identification was found to be around 1%, and the small magnitude of this value is mainly due to the fact that the gray scale levels change at the borders of the bubble, while remain constant in the remaining area (Fig. 14).

6. Experimental results 6.1. The flow regimes Figs. 15 and 16 show the void fraction trend at several flow rates, and in Figs. 15a,b and 16a a closer look to what happens in the lowest vapor qualities is reported. For all the parameters, each point on the graphs represents one movie, i.e. 500 full frames.

Fig. 20. s parameter as a function of the vapor quality and the mass flux. Fluid: R134a, D = 4 mm, Tsat = 22 °C, G = 20–120 kg/m2 s.

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The graphs with error bars are traced using the standard deviation as dispersion index: a high value of the standard deviation indicates therefore a transition zone. The void fraction increases with the vapor quality and for the low heating powers the standard deviation presents little variations. For higher powers, there is a wider region of instability (Fig. 15b and 16), up to vapor qualities equal to 0.10, and after this point the mean value of the standard deviation again decreases. From this point on, the mean value of the void fraction is stable, because the bubbles have reached their maximum dimensions inside the channels. The data available for the interval of vapor quality between 0.3 and 0.4 seem to confirm the trend found for the smaller values (Fig. 17). In the same Fig. 17 the homogeneous void fraction is reported together with the measured data, and it seems quite in agreement with the trend found. For vapor quality smaller than 0.1, there is only a very small gap between the homogeneous model and the data recorded, while for values than 0.1 the difference increases. This is meanly due to the fact that the homogeneous model predicts with higher accuracy the bubbly flow and the high vapor quality flows. The mean void fraction is weakly dependent on the mass flow rate. The bubble diameters are shown in Figs. 18 and 19. The graphs show the trend of the bubble dimensionless diameter, i.e. the ratio between the diameter of the bubbles and the internal diameter of the tube.

Fig. 21. s parameter as a function of the vapor quality and the mass flux. Fluid: R134a, D = 4 mm, Tsat = 22 °C, G = 20–120 kg/m2 s.

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The bubbly flow pattern is well defined for the lowest values of the vapor quality. It is also visible the transition region, identified by a very fluctuating region between two constant trend regions of the bubble diameter. In this case no asymptotic value at high vapor quality (Fig. 19) exists, even if the bubble dimensionless diameters tend to an almost constant value.

From Fig. 20, it is evident that the spherical bubbles are absent, with a minimum value for s around 0.45 (for spherical bubbles s = 0). Considering Fig. 20a and b, there are three main different values of s that are present starting from the total liquid condition (vapor quality x = 0.01) to the vapor quality of 0.4. The transition zone is established between vapor qualities of 0.025 and 0.09, and is characterized by more elongated and similar shape bubbles. This is the

Fig. 22. Void fraction evolution along the test section tube. (a) After the first heater, together with the homogeneous void fraction, (b) 30 cm ahead of the first position, (c) 70 cm ahead of the first position.

Fig. 23. Dimensionless bubble diameter evolution along the test section tube. (a) After the first heater, (b) 30 cm ahead of the first position, and (c) 70 cm ahead of the first position.

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so-called bubbly/elongated bubble transition zone. Then, around vapor quality 0.09 there is an evident step in the value trend and the value of s approaches its asymptotic value, then maintained for the highest power. The mass flux seems not to influence the bubble mean size. Fig. 21 represents a more wide view of the previous presented graphs, where it is possible to see the results of the experiments for the s parameter till a vapor quality of 0.8. The results presented from Figs. 22–24, the analysis refers to movies recorded in three different positions along the tube, and in this experimental campaign the main aim was the study of

the effect of coalescence on the flow pattern. In Fig. 22a the homogeneous void fraction is reported together with the measured data, and it seems quite in agreement with the trend found. For all the values of vapor quality considered there is only a very small gap between the homogeneous model and the data recorded. From Fig. 22a, it is again evident that the void fraction is not a function of the flow rate, because the three groups of values grow in strength but remaining within a very small interval. This characteristic is visible only in Fig. 22a, which regards the images recorded right after the first heater, while in Fig. 22b and c this trend is not maintained because they refer to different position along the tube. In these positions, the coalescence of bubbles has an important role and its main consequence is the modifications of the flow pattern. In the case shown in Fig. 22b, a shift appears in the value of the vapor quality at which the void fraction assumes the mean asymptotic values of the elongated bubble regime. Hence the coalescence is beginning to play an increasingly important role along the tube, and the main effect is that the bubbles are less in number but bigger in size. It is interesting to notice that the relative trend of the void fraction according to the mass flux remain in the same order of magnitude for the three positions. In Fig. 22c the effect of coalescence is visible: the data appear more scattered, but with the tendency shown in the previous graph which is mainly maintained. Fig. 22c suggests that coalescence is a function of the flow velocity, and so the situation with higher mass flux – and higher fluid speed – is the one that reaches the regime of elongated bubble faster. The behavior of the bubble dimensionless diameters shown in Fig. 23a–c, is similar to that of the void fraction. The main trend is the same and also here at higher mass fluxes, the more is the distance from the inlet, before the elongated bubble regime is reached. Fig. 24 represent the values of s parameter as a function of the mass flux and the vapor quality. The same considerations presented for the two previous quantities are valid, but in this case, the separation of the trend related to the mass flux is not so evident. Especially in Fig. 24c it is not possible to see a real separation of the three groups of values according to the three mass fluxes considered. This fact is mainly due to the coalescence of bubble along the tube, which changes the flow pattern of the flow and consequently also the parameters considered.

Fig. 24. s parameter evolution along the test section tube. (a) after the first heater, (b) 30 cm ahead of the first position, and (c) 70 cm ahead of the first position.

Fig. 25. Rejection ratio trend with vapor quality for videos taken after the first heater.

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6.2. Extended analysis In the last analysis only complete bubbles have been considered, and this leaded to the rejection of those frames that contain only partial bubbles. Fig. 25 shows the trend of the rejection ratio for videos after the first heater. It can be clearly seen that this trend increases with the vapor quality, because the bubbles reach the elongated bubble state faster for higher powers. All videos with vapor quality higher than 0.0198 and those taken at 30 and 70 cm from the first heater have a rejection ratio of 1 and could not been processed. If for a video the reject ratio is close to one, the number of rejected frames is very high and only few data could be extracted. The volume void fraction has been calculated considering the whole frame, and its value (Fig. 26) seems not to depend on the flow rate, and in fact the values are very similar for the three mass flow considered. A higher standard deviation can be noticed for vapor qualities higher than 0.005. Fig. 28. s trend for complete bubbles.

Fig. 26. Volume void fraction. Fig. 29. Slip velocity trend.

The dimensionless diameter shows a similar trend to the void fraction one (Fig. 27), while the standard deviation assumes higher values for the highest flow rates. Comparing Fig. 28 to Fig 29a, the value of the aspect parameter s is lower, and the shape of the bubbles is hence closer to the spherical one (s > 0.3). The standard deviation is higher for higher powers, with a stability region for vapor qualities higher than 0.015. Finally, in Fig. 29 the slip velocity of the various videos is shown. For most of the videos the slip velocity has a value around 0.8, and it assumes the highest values for lower flow rates and higher powers. This trend agrees with the main data that can be found in the literature for a similar tube [1,2].

7. Conclusions

Fig. 27. Dimensionless diameter trend of complete bubbles.

An image processing technique was developed to perform visualization of forced convection saturated R-134a boiling in a

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horizontal glass mini tube coated with several transparent conductive layers of Indium Tin Oxide (ITO). The inner diameter of the tube was 4 mm and the heated length was globally of 320 mm, distributed in eight shorter heaters of 40 mm each. A dedicated routine was created inside the commercial code Image ProÒ Plus to extract the bubble contours, measure geometrical features of each frame and collect the data both analytically and statistically. The method is mostly based on bubble geometrical features and their statistical analysis. Considering the common qualitative way for flow pattern identification, the flow pattern maps definition has been conducted in an alternative way trying to completely avoid the subjectivity of the definition of the common flow pattern maps that can be found in the literature. Classifying the flow pattern from the statistical point of view, it is possible to study the transition lines and expand them in transition zones. Considering a second group of experiments, a specific study taking into account different axial position along the channel has been conducted to study the bubbles evolution along the tube. Due to coalescence, it is possible to measure the flow pattern variation along the test section. The experiments demonstrated that coalescence is a phenomenon that can be studied from the statistical point of view. Generally the flow pattern variations along the tubes are not a function of the mass flux. The effect of coalescence was underlined and shown from the variation of bubbles geometry along the tube, and the key point was also for this part the possibility to visualize the flow inside all the tube. In the experiment range, the bubble geometrical data are weakly dependent on the refrigerant mass flux. Acknowledgments The research was conducted and financed within the Italian PRIN program 2005 and 2007. Many thanks also to Gianpietro Cossali, University of Bergamo, Paolo di Marco, University of Pisa, Iztok Zun, University of Ljubljana, Gian Piero Celata, ENEA, Rome, who gave us many useful suggestions and offered comments during the research. References [1] L. Wojtan, T. Ursenbacher, J.R. Thome, Investigation of flow boiling in horizontal tubes: Part I. A new diabatic two phase flow pattern map, Int. J. Heat Mass Transfer 48 (2005) 2955–2969. [2] N. Kattan, J.R. Thome, D. Favra, Flow boiling in horizontal tubes: Part 1. Development of a diabatic two-phase flow pattern map, J. Heat Transfer 120 (1998) 140–147. [3] R. Revellin, J.R. Thome, New diabatic flow pattern map for evaporating flows in microchannels, 13th International Heat Transfer Conference, Sydney, Australia, August 14–18, LTCM-CONF-2006-012, 2006. [4] M.B. Didi, N. Kattan, J.R. Thome, Prediction of two-phase pressure gradients of refrigerants in horizontal tubes, Int. J. Refrigerat. 25 (2002) 935–947. [5] O. Zurcher, D. Farvat, J.R. Thome, Development of a diabatic two-phase flow pattern map for horizontal flow boiling, Int. J. Heat Mass Transfer 45 (2002) 291–301. [6] J.M. Mandhane, G.A. Gregory, K. Aziz, A flow pattern map for gas–liquid flow in horizontal and inclined pipes, Int. J. Multiphase Flow 1 (1974) 537–553. [7] O. Baker, Simultaneous flow of oil and gas, Oil Gas J53 (1954) 185–195. [8] Y. Taitel, A.E. Dukler, A model for predicting flow regime transitions in horizontal and near horizontal gas–liquid flow, AIChE J. 22 (2) (1976) 43–55.

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