Multiphase-flow Statistics using 3D Detection and Tracking Algorithm (MS3DATA): Methodology and application to large-scale fluidized beds

Abstract

Bubble dynamics play a critical role in the hydrodynamics of fluidized beds and significantly affect reactor performance. In this study, MS3DATA (Multiphase-flow Statistics using 3D Detection And Tracking Algorithm) is developed, validated and applied to numerical simulations of large-scale fluidized beds. Using this algorithm, bubbles are detected using void fraction data from simulations and are completely characterized by their size, shape and location while their velocities are computed by tracking bubbles across successive time frames. A detailed analysis of 2D (across vertical sections) and 3D bubble statistics using 3D simulations of lab-scale (diameter 14.5 cm) and pilot-scale bed (diameter 30 cm) is presented and it is shown that the former (a) under-predicts sizes of larger bubbles, (b) cannot detect a large fraction of small bubbles (<3 cm) and (c) is unable to track the azimuthal motion of bubbles in the larger bed. The scalability of the algorithm is discussed by comparing the computational cost of computing bubble statistics on highly resolved grids. Even though 3D bubble detection is significantly more expensive than 2D detection, the cost is still negligible compared to the cost of accurate simulations. Besides application to fluidization simulation data of large fluidized beds, this algorithm can be easily extended to characterize bubbles, droplets and clusters in other areas of multiphase flows. Keywords: Multiphase flow; Fluidized bed; Eulerian simulations; Bubble dynamics; 3D statistics; Large-scale detection and tracking