Applications of wire-mesh sensors in multiphase flows

Peña, Hugo Fernando Velasco; Rodriguez, Oscar Maurício Hernandez

doi:10.1016/j.flowmeasinst.2015.06.024

Cited by 50 publications

(26 citation statements)

References 122 publications

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“…These parameters are essential to understand the heat transfer coefficient and assess the risk of critical boiling, for example in nuclear industry [1,2]. Various techniques have been developed for multiphase flow phase fraction estimation, for example, wire-mesh sensors can provide information about local, cross-section or in-situ volume profiles and distributions of phase fraction, but they have disruptive effects on the flow [3]; optical probes are sensitive to 1 interfacial passages enabling to measure local void fraction with a high precision, however, they are intrusive [4], as are electrical probes as well [5]; X-ray and Gamma-ray tomography allow fast measurements of multiphase flows at high spatial resolution but they require high acceleration voltage (hundreds of kV) and radiation protection [6,7]; Electrical Capacitance Tomography (ECT) has similar characteristics to the EIT but it requires high voltage excitation signals. Note that Huang et al [8] used ECT to measure void fraction based on image reconstruction with a satisfactory accuracy.…”

Section: Introductionmentioning

confidence: 99%

Numerical and experimental analysis of the correlation between EIT data eigenvalues and two-phase flow phase fraction

Dang¹,

Darnajou²,

Bellis³

et al. 2019

Meas. Sci. Technol.

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Electrical Impedance Tomography (EIT) is an imaging technique with advantages of nonintrusiveness, low-cost and high temporal resolution, which is promising for multiphase flow instrumentation. However, it produces smooth images with low spatial resolution where the interface between phases cannot be distinguished and from which the phase fraction cannot be estimated correctly. In this article, an eigenvalue analysis of EIT raw data is used to estimate the void fraction, i.e. the phase area ratio in 2D, without reconstructing images. For a given EIT sensor, each acquisition frame is represented by an impedance matrix whose eigenvalues are computed after normalization. The main characteristics of the eigenvalue distribution for different two-phase flow patterns within a cylindrical pipe are analyzed numerically. The behaviors of the leading eigenvalue and of the sum of the absolute values of the following ones are assessed as functions of the void fraction. This leads to an estimation of the two-phase flow void fraction based on the characteristics of the EIT sensor configuration. The presented numerical results highlight the existing correlation between the eigenvalues and the void fraction for the phase distribution patterns considered. These simulation results are compared with experimental static tests for validation.

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Section: Introductionmentioning

confidence: 99%

Numerical and experimental analysis of the correlation between EIT data eigenvalues and two-phase flow phase fraction

Dang¹,

Darnajou²,

Bellis³

et al. 2019

Meas. Sci. Technol.

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“…Due the intrusive characteristic the wire-mesh sensor is hardly applied in channels with reduced diameter. On the other hand, as reported by Peña and Rodriguez [50], the main advantage is the direct measurement of the phase fraction and is also being used as an aid for Computational Fluid Dynamics (CFD) simulations.…”

Section: Wire-mesh Sensormentioning

confidence: 99%

Overview of Void Fraction Measurement Techniques, Databases and Correlations for Two-Phase Flow in Small Diameter Channels

Gardenghi

Filho

Chagas

et al. 2020

Fluids

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Void fraction is one of the most important parameters for the modeling and characterization of two-phase flows. This manuscript presents an overview of void fraction measurement techniques, experimental databases and correlations, in the context of microchannel two-phase flow applications. Void fraction measurement techniques were reviewed and the most suitable techniques for microscale measurements were identified along its main characteristics. An updated void fraction experimental database for small channel diameter was obtained including micro and macrochannel two-phase flow data points. These data have channel diameter ranging from 0.5 to 13.84 mm, horizontal and vertical directions, and fluids such as air-water, R410a, R404a, R134a, R290, R12 and R22 for both diabatic and adiabatic conditions. New published void fraction correlations as well high cited ones were evaluated and compared to this small-diameter void fraction database in order to quantify the prediction error of them. Moreover, a new drift flux correlation for microchannels was also developed, showing that further improvement of available correlations is still possible. The new correlation was able to predict the microchannel database with mean absolute relative error of 9.8%, for 6% of relative improvement compared to the second-best ranked correlation for small diameter channels.

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“…The data received by the computer is still in a voltage value, to get the capacitance value from the wire-meh sensor it is necessary to change the data using equation (1). This equation is inserted into the code script in the python 2-dimensional image program, so it is not just a program to create images but python software also performs mathematical calculations to get measured capacitance values in wire-mesh sensors.…”

Section: Image Processingmentioning

confidence: 99%

“…In some applications such as health sciences, industry, or in research frequently use various types of fluid that is not mixed in the liquid flow. To study the physical phenomena in this liquid flow, it is required variable measurements such as the velocity of each fluid or phase, concentration, and spatial distribution, among others [1]. Wire-Mesh Sensors (WMS) commonly used to obtain the distribution of the phase fraction and visualize behavior of fluid within a pipe [2].…”

Section: Introductionmentioning

confidence: 99%

Wire-Mesh 16 × 16 Capacitance Sensor for Analysis of Capacitance Distribution on Cylindrical Pipe

Sujiwa

Endarko

2018

IJPS

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The wire-mesh sensor is an intrusive sensor device that uses for generating 2-dimensional (2D) images of fluid flow. Sensors made of 2 layers copper wires, transmitter, and receiver, that perpendicular each other. The wire-mesh sensor will directly to measure the value of inductance or capacitance at the crossing wire. There are 208 data measurements in 16 × 16 cylindrical wire-mesh sensors. All data measurement then processed by Python software to obtain a 2D image of the capacitance distribution. Experiment results show the inhomogeneous distribution of capacitance that occurs in the wire-mesh sensor. Three types of liquids, distilled water, tap water and salt solution, showed circular pattern of capacitance distribution, with the highest capacitance value being in the central area of the image, while at edge area has a lower capacitance value than the central area.

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Applications of wire-mesh sensors in multiphase flows

Cited by 50 publications

References 122 publications

Numerical and experimental analysis of the correlation between EIT data eigenvalues and two-phase flow phase fraction

Numerical and experimental analysis of the correlation between EIT data eigenvalues and two-phase flow phase fraction

Overview of Void Fraction Measurement Techniques, Databases and Correlations for Two-Phase Flow in Small Diameter Channels

Wire-Mesh 16 × 16 Capacitance Sensor for Analysis of Capacitance Distribution on Cylindrical Pipe

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