Study of local solid volume fraction fluctuations using high speed electrical impedance tomography: Particles with low Stokes number

2019 ◽  
Vol 203 ◽  
pp. 439-449 ◽  
Author(s):  
Maedeh Marefatallah ◽  
David Breakey ◽  
R. Sean Sanders
Keyword(s):  
Electrical Impedance Tomography ◽  
High Speed ◽  
Electrical Impedance ◽  
Volume Fraction ◽  
Solid Volume Fraction ◽  
Stokes Number ◽  
Impedance Tomography

scholarly journals On the Implementation of Simultaneous Multi-Frequency Excitations and Measurements for Electrical Impedance Tomography

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3679 ◽  
Author(s):  
Mathieu Darnajou ◽  
Antoine Dupré ◽  
Chunhui Dang ◽  
Guillaume Ricciardi ◽  
Salah Bourennane ◽  
...  
Keyword(s):  
Electrical Impedance Tomography ◽  
High Speed ◽  
Electrical Impedance ◽  
Fourier Transforms ◽  
Imaging Technique ◽  
Signal To Noise Ratio ◽  
Data Acquisition System ◽  
Impedance Tomography ◽  
Field Programmable ◽  
Propagation Of Uncertainties

The investigation of quickly-evolving flow patterns in high-pressure and high-temperature flow rigs requires the use of a high-speed and non-intrusive imaging technique. Electrical Impedance Tomography (EIT) allows reconstructing the admittivity distribution characterizing a flow from the knowledge of currents and voltages on its periphery. The need for images at high frame rates leads to the strategy of simultaneous multi-frequency voltage excitations and simultaneous current measurements, which are discriminated using fast Fourier transforms. The present study introduces the theory for a 16-electrode simultaneous EIT system, which is then built based on a field programmable gate array data acquisition system. An analysis of the propagation of uncertainties through the measurement process is investigated, and experimental results with fifteen simultaneous signals are presented. It is shown that the signals are successfully retrieved experimentally at a rate of 1953 frames per second. The associated signal-to-noise ratio varies from 59.6–69.1 dB, depending on the generated frequency. These preliminary results confirm the relevance and the feasibility of simultaneous multi-frequency excitations and measurements in EIT as a means to significantly increase the imaging rate.

scholarly journals Experimental analysis of particle clustering in moderately dense gas–solid flow

2021 ◽  
Vol 933 ◽  
Author(s):  
Kee Onn Fong ◽  
Filippo Coletti
Keyword(s):  
High Speed ◽  
Volume Fraction ◽  
Solid Volume Fraction ◽  
Stokes Number ◽  
Spherical Particles ◽  
High Speed Imaging ◽  
Dense Particle ◽  
Laboratory Observation ◽  
Laboratory Setup ◽  
Wide Range

In collisional gas–solid flows, dense particle clusters are often observed that greatly affect the transport properties of the mixture. The characterisation and prediction of this phenomenon are challenging due to limited optical access, the wide range of scales involved and the interplay of different mechanisms. Here, we consider a laboratory setup in which particles fall against upward-moving air in a square vertical duct: a classic configuration in riser reactors. The use of non-cohesive, monodispersed, spherical particles and the ability to independently vary the solid volume fraction ( $\varPhi _V = 0.1\,\% - 0.8\,\%$ ) and the bulk airflow Reynolds number ( $Re_{bulk} = 300 - 1200$ ) allows us to isolate key elements of the multiphase dynamics, providing the first laboratory observation of cluster-induced turbulence. Above a threshold $\varPhi _V$ , the system exhibits intense fluctuations of concentration and velocity, as measured by high-speed imaging via a backlighting technique which returns optically depth-averaged fields. The space–time autocorrelations reveal dense and persistent mesoscale structures falling faster than the surrounding particles and trailing long wakes. These are shown to be the statistical footprints of visually observed clusters, mostly found in the vicinity of the walls. They are identified via a percolation analysis, tracked in time, and characterised in terms of size, shape, location and velocity. Larger clusters are denser, longer-lived and have greater descent velocity. At the present particle Stokes number, the threshold $\varPhi _V \sim 0.5$ % (largely independent from $Re_{bulk}$ ) is consistent with the view that clusters appear when the typical interval between successive collisions is shorter than the particle response time.

Applying the logistic regression in electrical impedance tomography to analyze conductivity of the examined objects

2020 ◽  
pp. 1-18
Author(s):  
Tomasz Rymarczyk ◽  
Edward Kozłowski ◽  
Paweł Tchórzewski ◽  
Grzegorz Kłosowski ◽  
Przemysław Adamkiewicz
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Image Reconstruction ◽  
Electrical Impedance Tomography ◽  
Spatial Data ◽  
High Speed ◽  
Electrical Impedance ◽  
Numerical Models ◽  
Impedance Tomography ◽  
Input Variables

The article presents machine learning methods in the field of reconstruction of tomographic images. The presented research results show that electric tomography makes it possible to analyze objects without interfering with them. The work focused mainly on electrical impedance tomography and image reconstruction using deterministic methods and machine learning, reconstruction results were compared and various numerical models were used. The main advantage of the presented solution is the ability to analyze spatial data and high speed of processing. The implemented algorithm based on logistic regression is promising in image reconstruction. In addition, the elastic net method was used to solve the problem of selecting input variables in the regression model.

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