4.7 Article

Velocity Profiling of a Gas-Solid Fluidized Bed Using Electrical Capacitance Volume Tomography

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2022.3190524

Keywords

Capacitance; Image reconstruction; Solids; Temperature measurement; Permittivity; Particle measurements; Atmospheric measurements; Capacitance sensor; electrical capacitance volume tomography (ECVT); fluidized bed; multiphase fluid flow; velocity measurement

Funding

  1. Department of Energy (DoE) [DE-SC0018758]
  2. U.S. Department of Energy (DOE) [DE-SC0018758] Funding Source: U.S. Department of Energy (DOE)

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In this study, a method based on electrical capacitance volume tomography (ECVT) is developed to reconstruct velocity profile maps in fluidized bed systems. The method takes advantage of the sensitivity distribution gradient of the ECVT sensor to avoid the use of image cross correlation techniques. Experimental data collected from both bubbling and slugging fluidized beds are used to validate the technique, and good agreement is found when comparing the velocity maps obtained with established methods and empirical correlations. The study demonstrates the power of ECVT as a measurement tool for gas-solid fluidized beds.
In this work, a method of producing velocity profile maps from electrical capacitance volume tomography (ECVT) measurements by reconstructing displacement from measured changes in capacitance is developed and applied to fluidized bed systems. The mapping of the reconstruction leverages the gradient of the sensitivity distribution of the ECVT sensor to circumvent the need for image cross correlation techniques. Experimental data of both bubbling and slugging fluidized beds are collected in a cold flow model. Adaptation of the technique is discussed in detail, and velocity profiles are obtained for a range of gas flow rates. The produced velocity maps are compared against the established methods of cross correlation and against empirical correlations from the literature and are found to agree well in tracking slug and bubble velocity. The exception is when the tracked object is large relative to the ECVT sensor dimensions, a scenario that can be avoided through proper sensor design. The quantities of average velocity, momentum, and solid and gas volume fraction are derived from the image and velocity profiles. The results demonstrate and extend the power of ECVT as a measurement tool for the study and monitoring of gas-solid fluidized beds by providing a computationally cheaper alternative to 3-D cross correlation for deriving velocity profiles.

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