Development and validation of a novel digital image analysis method for fluidized bed particle image velocimetry

Particle Image Velocimetry (PIV) is a widely applied non-intrusive, optical experimental technique to measure characteristics of the solids motion in pseudo 2D fluidized beds. However, the majority of the research that concerns the use of PIV on granular systems focused thus far on either particle velocities or on particle fluxes with very rudimentary implementation for the correction for the presence of bubbles. A reliable correlation between 2D image intensity and the true 3D solids fraction in fluidized beds is required to obtain more accurate information on the solid particle flux profiles in granular systems. Using only experimental data, it is difficult - if not impossible- to obtain such a correlation, but by using data from Discrete Particle Model (DPM) simulations to create artificial 2D-images, we reconstructed this 2D-3D correlation for the solids fraction correlation. In this paper the influence of particle size, fluidization velicity, bed depth and intensity distribution function on the 2D-3D correlation has been investigated, in particular for the application in gas-solid fluidized beds in the bubbling regime. It was found that the particle size and fluidization velocity have no influence on the correlation and the intensity distribution function only slightly affects the results for dilute regions, but the bed depth shows the most prominent effect. A detailed comparison between the DPM velocity field as a reference and the conventional and newly introduced Digital Image Analysis (cDIA/nDIA) techniques shows that the error in the solids flux decreases from 18.7% to 12.3%. Also, we used PIV software to reconstruct the solids velocity field, based on a pair of artificial images from DPM simulations (as done for experimentally acquired data based on a pair of real images), and showed that the largest error is introduced in the determination (cross-correlation) of the particle velocity field