Advanced Imaging Techniques for Multiphase Flows Analysis

Amoresano, Amedeo; Langella, Giuseppe; Santo, Martin; Iodice, Paolo

doi:10.1088/1742-6596/882/1/012004

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…Vibrational data have been processed by discriminant analysis. Similar applications of this innovative technique have also been realized for the characterization of stationary sprays (gas turbines) [15] and stationary (internal combustion engines) [16,17] . This technique goes beyond the classic identification of characteristic frequencies through Fourier analysis, applying the statistical theory of chaos to identify and characterize particular operating conditionsTo apply this method it is necessary to consider that the signal is the sum of 30 signal of 1 second.…”

Section: Processing Of Resultsmentioning

confidence: 91%

Recognition of two-phase flow pattern inside evaporator tubes

et al. 2021

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The convective heat exchange mechanism in two-phase regime, can allow high exchange coefficients, as long as particular conditions are respected, in terms of vapor quality. In evaporator tubes this problem is particularly important as a deviation from the optimal flow conditions can drastically drop the efficiency of the heat exchange. This work describes an innovative methodology for identifying the different two-phase flow regimes in evaporator pipes, through the processing of the vibrational data acquired on the pipe itself. An experimental apparatus with transparent pipes has been built up to recognize flow patterns by a fast image acquisition camera. Images have been associated to vibration data acquired on pipes by accelerometer. The analysis of frequency spectrum, led to first interesting results thus it is possible to distinguish between “no bubbles” regimes and different “bubbles” regimes. A wide test campaign has been realized on vertical and horizontal pipes, simulating steam bubbles with nitrogen bubbles, reproducing the main flow patterns. The paper demonstrates the possibility to design smart and non-intrusive sensor to be applied on evaporated tubes for the recognizing of anomalous thermal flow condition and sets the stage for future engineering work.

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Section: Processing Of Resultsmentioning

confidence: 91%

Recognition of two-phase flow pattern inside evaporator tubes

et al. 2021

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“…The name and brief principle of work description of the sensors that are usually used for gas–liquid multiphase flow systems in the industrial and academic research sectors are presented in Table 1 . In general, these sensors and measurement devices are (a) high-speed camera [ 10 ], (b) photochromic dye activation [ 11 , 12 ], (c) particles image velocimetry (PIV) [ 13 ], (d) external microphone sensors (i.e., acoustic techniques) [ 14 ], (e) probe-based sensors, such as (i) optical fiber probes [ 15 ], (ii) two hot film anemometers [ 16 ], (iii) capacitance sensors, and (iv) conductivity and conductance probes (even though in principle the conductivity probes are in fact computing conductance based on the capability of the used medium to conduct electrical current, conversely, the conductance probes are influenced by the geometrical dimensions of the electrodes) [ 17 , 18 , 19 , 20 ], (f) tomographic methods including 8–16 electrodes’ capacitance, ionizing radiation (i.e., X-rays and γ-rays), nuclear magnetic resonance, and acoustic (i.e., ultrasound) [ 21 , 22 , 23 , 24 , 25 , 26 ], (g) static and differential pressure transducers [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

A Simplified Numerical Approach to Examine the Sensitivity of Two-Electrode Capacitance Sensor Orientation to Capture Different Gas–Liquid Flow Patterns in a Small Circular Pipe

Al-Alweet

Jaworski

Alghamdi

et al. 2020

Sensors

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This work involved the simulation of both a multiphase gas–liquid flow and the electromagnetic field representing a two-electrode capacitance sensor in a circular pipe. The simulation investigates in particular the sensitivity of the sensor orientation around the pipe (i.e., top-to-bottom or side-to-side) that best capture the induced flow patterns. The presented numerical work is a simplified simulation by COMSOL multi-physics which was validated by a systematic and an extensive experimental work, using (a) a specially designed simple capacitance sensor (i.e., concave two electrodes), (b) different gas–liquid superficial velocity combinations, (c) different flow section inclinations, and (d) high-speed camera images. The numerical modelling capacitance values were validated against the experimentally measured values which shows a satisfactory level of agreement with a deviation of less than ±2%. The quantity of finite points was between 280,000 and 340,000, which was influenced by the simulated flow pattern. The simulated cases captured the generated flow patterns and their variation inside the pipe, which was in a good agreement when compared to the experimental work as time-dependent values. It was found that the best orientation for the utilized two-electrode capacitance sensor was the top-to-bottom configuration. This is because the sensor’s electrical field distribution was more sensitive, and capable of detecting a greater range of capacitance values. The sensitivity of the top-to-bottom configuration was 1.25–1.64 times greater than that of the side-to-side configuration. Therefore, for design purposes and performance optimization, it is recommended to use the top-to-bottom configuration.

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Two-phase flow structure assessment based on dynamic image analysis

Masiukiewicz

Anweiler

2019

Flow Measurement and Instrumentation

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Advanced Imaging Techniques for Multiphase Flows Analysis

Cited by 4 publications

References 11 publications

Recognition of two-phase flow pattern inside evaporator tubes

Recognition of two-phase flow pattern inside evaporator tubes

A Simplified Numerical Approach to Examine the Sensitivity of Two-Electrode Capacitance Sensor Orientation to Capture Different Gas–Liquid Flow Patterns in a Small Circular Pipe

Two-phase flow structure assessment based on dynamic image analysis

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