Estimation of particle dynamics in 2-D fluidized beds using particle tracking velocimetry--颗粒学报PARTICUOLOGY

Hagemeier, T., Roloff, C., Bück, A., & Tsotsas, E. (2015). Estimation of particle dynamics in 2-D fluidized beds using particle tracking velocimetry. Particuology, 22, 39-51. https://doi.org/10.1016/j.partic.2014.08.004

Estimation of particle dynamics in 2-D fluidized beds using particle tracking velocimetry

Thomas Hagemeier ^a *, Christoph Roloff ^b, Andreas Bück ^a, Evangelos Tsotsas ^a

a NaWiTec, Thermal Process Engineering, Otto-von-Guericke University Magdeburg, Universitaetsplatz 2, 39106 Magdeburg, Germany
b Fluid Dynamics and Technical Flow, Otto-von-Guericke University Magdeburg, Universitaetsplatz 2, 39106 Magdeburg, Germany

10.1016/j.partic.2014.08.004

Volume 22, October 2015, Pages 39-51

Received 6 May 2014, Revised 31 July 2014, Accepted 16 August 2014, Available online 11 December 2014, Version of Record 4 August 2015.

E-mail: Thomas.Hagemeier@ovgu.de

Highlights

• High-speed imaging was coupled with segmentation and Voronoi method to acquire particle velocities.

• Thousands of particles could be tracked at the same time in a 2D fluidized bed.

• Solid volume fraction and granular temperature can be derived from Lagrangian particle description.

• Solid phase velocity field could be reconstructed from instantaneous particle velocities.

Abstract

The experimental characterization of particle dynamics in fluidized beds is of great importance in fostering an understanding of solid phase motion and its effect on particle properties in granulation processes. Commonly used techniques such as particle image velocimetry rely on the cross-correlation of illumination intensity and averaging procedures. It is not possible to obtain single particle velocities with such techniques. Moreover, the estimated velocities may not accurately represent the local particle velocities in regions with high velocity gradients. Consequently, there is a need for devices and methods that are capable of acquiring individual particle velocities. This paper describes how particle tracking velocimetry can be adapted to dense particulate flows. The approach presented in this paper couples high-speed imaging with an innovative segmentation algorithm for particle detection, and employs the Voronoi method to solve the assignment problem usually encountered in densely seeded flows. Lagrangian particle tracks are obtained as primary information, and these serve as the basis for calculating sophisticated quantities such as the solid-phase flow field, granular temperature, and solid volume fraction. We show that the consistency of individual trajectories is sufficient to recognize collision events.

Graphical abstract

Keywords

Particle dynamics; Particle tracking velocimetry; Pseudo-2D; Fluidized bed

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