Particle Circulation and Mixing Kinetics in Bubbling Fluidised Beds Using Pept | AIChE

Particle Circulation and Mixing Kinetics in Bubbling Fluidised Beds Using Pept

Authors 

Windows-Yule, K. - Presenter, University of Birmingham
Werner, D., University of Birmingham
Wellings, A., Recycling Technologies
Seville, J., The University of Birmingham
Thorpe, R. B., School of Engineering
Bhattacharya, S., Recycling Technologies
Sanchez, A., Recycling Technologies
Besong, M., Recycling Technologies
Prediction of the solids motion and the kinetics and extent of mixing in fluidised beds is important in a new generation of industrial processes including, for example, thermal treatment of mixed plastic waste as part of the circular economy in plastics. Verification of classical two-phase type predictions at industrial scale has been limited by lack of appropriate non-invasive measurement approaches. We describe the use of a new generation of Positron Emission Particle Tracking (PEPT) software and hardware [1] to track particle motion in scaled laboratory and pilot-plant fluidised beds up to 1.5m in diameter, giving more detailed solids motion information than ever before obtained, including complete motion maps at 100Hz acquisition rates and ~1mm accuracy. Time averaged bed circulation patterns generally show the behaviour predicted by Geldart, with strong upward motion towards the centre-line and down at the walls. However, PEPT trajectory analysis at all scales also shows the discontinuous “jump” and “idle time” behaviour observed earlier by Stein et al. [2]. This is significant for reactions and in processes such as agglomeration, which depend on local particle contact. The measurements obtained also enable indirect measurement of bubble velocity. As expected, mixing time is related to individual particle circulation time. We demonstrate the use of the trajectory analysis method first proposed by Martin et al. [3] for measurement of dispersion and mixing rate, showing the dependence of mixing time on excess gas velocity and the relationship to particle circulation time. We demonstrate the use of the Barracuda computational software to predict particle motion in equivalent circumstances.

[1] Windows-Yule et al 2022 Rep. Prog. Phys. 85 016101

[2] Stein et al 2000 Chem. Eng. Sci. 55 5291

[3] Martin et al 2007 Chem. Eng. Sci. 62 3419

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