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Mixing efficiency is one of the most significant factors, affecting both performance and scale-up of a gas-solid reactor system. This paper presents an experimental investigation on the particle mixing in a multiple spouted bed. Image processing technique was used to extract the real-time information concerning the distribution of particle components (bed materials and tracer particles). A more accurate definition of the tracer concentration was developed to calculate the mixing index. According to the visual observation and image analysis, the mixing mechanism was revealed and the mixing rate was evaluated. Based on these results, the effects of operation parameters on the mixing rate were discussed in terms of the flow patterns. It is found that the detection of the pixel distribution of each component in RGB images is not affected by the interference of air void, thus maintaining good measurement accuracy. Convective transportation controls the particle mixing in the internal jet and spout, while shear dominants the particle mixing in the dense moving region. Global mixing takes place only when the path from one spout cell to the other is open. This path can be formed either by the bubbles or particle circulation flows. The mixing rate is linked to the bubble motion and particle circulation. Provided that there are interactions between the spout cells, any parameters promoting the bubble motion and circulation can increase the mixing rate. Finally, a mixing pattern diagram was constructed to establish the connection between the flow structure and mixing intensity.

Evaluation of Mixing and Mixing Rate in a Multiple Spouted Bed by Image Processing Technique