Mapping of horizontal refrigerant two-phase flow patterns based on clustering of capacitive sensor signals

Canière, Hugo; Bauwens, Bruno; T’Joen, Christophe; Paepe, Michel De

doi:10.1016/j.ijheatmasstransfer.2010.07.027

Cited by 31 publications

(20 citation statements)

References 18 publications

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“…The capacitive void fraction sensors used in the current study were developed by Ghent University (Canière et al, 2010(Canière et al, , 2009(Canière et al, , 2008(Canière et al, , 2007) and a calibration procedure was developed for adiabatic horizontal flow (De Kerpel et al, 2014. For the current study the sensor responses were calibrated to track the predictions of the Rouhani and Axelsson (1970) correlation for the case of horizontal adiabatic flow at a saturation temperature of 40 ᵒC; good correlation between horizontal adiabatic flow and the Rouhani and Axelsson (1970) predictions has been observed in previous work (De Kerpel et al, 2013).…”

Section: Experimental Set-upmentioning

confidence: 82%

“…As the void fractions and heat transfer correlations are so strongly related there is a need for accurate void fraction measurements, however, instrumentation that can measure void fractions without influencing the flow patterns are not readily available commercially. Such a void fraction sensor has been developed at the Ghent University (Canière et al, 2010(Canière et al, , 2009(Canière et al, , 2008(Canière et al, , 2007, but is not yet commercially available on the open market.…”

Section: Introductionmentioning

confidence: 99%

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The influence of inclination angle on void fraction and heat transfer during condensation inside a smooth tube

Olivier

Meyer

Paepe

et al. 2016

International Journal of Multiphase Flow

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Most work in literature on condensation in tubes has been done for smooth tubes in the horizontal and vertical configurations. Recent experimental works with condensation at different inclination angles showed that the heat transfer characteristics were a function of inclination angle. These works were limited to heat transfer and pressure drop measurements with visual observations. However, no work has been done on measuring the void fractions during condensation at different inclination angles. The purpose of this study was to measure void fractions and heat transfer coefficients during condensation for tube inclinations ranging from vertical downwards (-90ᵒ) to vertical upwards (90ᵒ) at a saturation temperature of 40 ᵒC. Measurements were taken in an experimental set-up in which condensation occurred on the inside of a test section. The test section was a circular tube with an inner diameter of 8.38 mm and a heat transfer length of 1.488. The refrigerant used was R134a, and the void fractions were measured using two capacitive void fraction sensors. Mass fluxes ranging from 100 -400 kg/m 2 .s and vapour qualities ranging from 10 -90% were considered. Heat transfer coefficients were also compared with void fractions. It was found that at combinations of low mass fluxes and vapour qualities, void fraction and heat transfer were significantly affected by changes in inclination angle. Generally, void fractions and heat transfer coefficients increased with downward inclination angles with an optimum angle between -10ᵒ and -30ᵒ (downward flow). At some intermediate mass flux and vapour quality conditions, the void fraction and heat transfer coefficients were observed to be independent of the inclination angle despite changes in the prevailing flow patterns.2

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Section: Experimental Set-upmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

The influence of inclination angle on void fraction and heat transfer during condensation inside a smooth tube

Olivier

Meyer

Paepe

et al. 2016

International Journal of Multiphase Flow

View full text Add to dashboard Cite

show abstract

“…Capacitance measurements acquired 3 simultaneously with high-speed videos of air-water flows have been used to identify two-phase flow patterns [2]. In addition, encouraging results involving the identification of two-phase flow patterns of refrigerants have been obtained using a capacitance probe that produced void fraction signals [10].…”

Section: Introductionmentioning

confidence: 99%

Flow pattern identification of horizontal two-phase refrigerant flow using neural networks

Roman

Kreitzer

Ervin

et al. 2016

International Communications in Heat and Mass Transfer

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In this work, electrical capacitance tomography (ECT) and neural networks were used to automatically identify two-phase flow patterns for refrigerant R-134a flowing in a horizontal tube. In laboratory experiments, high-speed images were recorded for human classification of liquid-vapor flow patterns. The corresponding permittivity data obtained from tomograms was then used to train feedforward neural networks to recognize flow patterns. An objective was to determine which subsets of data derived from tomograms could be used as input data by a neural network to classify nine liquidvapor flow patterns. Another objective was to determine which subsets of input data provide high identification success when analyzed by a neural network. Transitional flow patterns associated with common horizontal flow patterns were considered. A unique feature of the current work was the use of the vertical center of mass coordinate in pattern classification. The highest classification success rates occurred using neural network input which included the probability density functions (in time) for both spatially averaged permittivity and center of mass location in addition to the four statistical moments (in time) for spatially averaged permittivity data. The combination of these input data resulted in an average success rate of 98.1% for nine flow patterns. In addition, 99% of the experimental runs were either correctly classified or misclassified by only one flow pattern. NomenclatureA i Individual pixel area [m 2 ] A T Sum of all pixel areas [m 2 ] D Tube diameter [m] D b Bubble diameter [m] ECT Electrical capacitance tomography L Length [m] ____________________

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“…They also demonstrated that the probability density function (PDF) of the x-ray sign fluctuations can be used to distinguish flow patterns. Since then, several studies on two-phase flow pattern characterization through objective methods have been conducted [11][12][13][14][15][16][17][18][19], with most of them for macroscale conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Canière et al [16] developed an objective method for flow pattern characterization in macroscale tubes based on the two-phase flow capacitance and the analyses of its signal through the fuzzy c-means clustering algorithm. The main advantage of the fuzzy c-means algorithm is the two-phase flow characterization without subjective decisions.…”

Section: Introductionmentioning

confidence: 99%

Two-Phase Flow Characteristics During Convective Boiling of Halocarbon Refrigerants Inside Horizontal Small-Diameter Tubes

Sempértegui-Tapia

Alves

Ribatski

2013

Heat Transfer Engineering

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Two-phase flow observations were performed for The tests were run for mass velocities ranging from 100 to 600 kg/m 2 -s and saturation temperatures of 22, 31, and 41 • C. Additionally, an objective method to characterize two-phase flow patterns was developed. This method is based on simultaneous processing of signals from the following devices: a pair of diodes laser-sensors with a transparent tube between them within which the two-phase flow occurs, a micro-piezoelectric pressure transducer to determine the variation in the local pressure, and a microthermocouple within the fluid. The method was developed based on the k-means clustering algorithm, which consists of the gradual agglomeration of data of similar average characteristics. Simultaneous images of two-phase flow were obtained through a high-speed camera (10,000 frames/s) and used to identify the following flow patterns: bubbly, elongated bubbles, churn, and annular flows. The maps obtained by the objective method were compared against flow pattern results segregated based on flow visualization and a reasonable agreement was obtained between them. The vapor quality for the transition between churn and annular flow pattern decreases with decreasing the tube diameter, whereas the vapor quality for the transition between elongated bubbles and churn flow decreases with increasing tube diameter. Effects of saturation temperature and mass velocity were also verified. Additionally, elongated bubble velocities, frequencies, and lengths were determined based on the analysis of high-speed videos and the processing of signals of the diode/laser-sensor. The elongated bubble velocity was correlated as a linear function of the two-phase superficial velocity. A new image treatment method was developed to automatically identify the entrainment frequencies, which were segregated according to two groups: low and high frequency. The former group was characterized by frequencies lower than 20 Hz and the later by 50-500 Hz frequency ranges.

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Mapping of horizontal refrigerant two-phase flow patterns based on clustering of capacitive sensor signals

Cited by 31 publications

References 18 publications

The influence of inclination angle on void fraction and heat transfer during condensation inside a smooth tube

The influence of inclination angle on void fraction and heat transfer during condensation inside a smooth tube

Flow pattern identification of horizontal two-phase refrigerant flow using neural networks

Two-Phase Flow Characteristics During Convective Boiling of Halocarbon Refrigerants Inside Horizontal Small-Diameter Tubes

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