Abstract

Objective To address the poor performance of turbo air classifier， five different air supply structures were designed to find the optimal scheme to improve its classification efficiency.

Method The accuracy of the calculation model was verified through grid independence analysis and eddy current classification experiments using rice flour. The flow field of the turbo air classifier was simulated using Fluent software to explore the influence of different air supply structures on air retention capacity， uniformity， and dispersion. A discrete phase model （DPM） was used to simulate the motion trajectory of rice flour particles. The cumulative distribution of particle size at the discharge of the classifier was analyzed to determine the influence of different air supply structures on rice flour classification.

Results and Discussion Simulation results revealed that adding a windshield ring structure above the cone fairing in Model 2，based on Model 1， effectively reduced direct air loss from the cone shell wall， significantly increased the residence time of the replenished air in the cone shell， and reduced d₅₀ by 0. 62 μm compared with Model 1. Model 3， which added a flow guide blade to the air outlet plane of the air supply structure on the basis of Model 2， weakened air impact and increased air dispersion. The fluctuation in axial velocity value in Model 3 became smaller， and the d₅₀ was 2. 88 μm lower than that of Model 2.However， insufficient space in the air supply structure reduced airflow retention time and affected air replenishment. A completely different air supply structure was adopted in Models 4 and 5 from Model 3， with staggered inlet and outlet areas in the vertical direction to ensure sufficient retention space for airflow， thereby improving the residence time. The d₅₀ of Model 4 was 30. 22 μm， which was 2. 92 μm higher than Model 3， indicating suboptimal air-replenishment performance. In contrast， Model 5 adopted a downsetting scheme for the air outlet area of the air supply structure， using the conical shell as an air flow guide. Model 5 showed less fluctuation in axial velocity， a more reasonable distribution， and the best air flow dispersion and uniformity. Although the d₅₀ of Model 5 was slightly increased by 0. 62 μm compared with Model 3， its cumulative particle size distribution curve was below that of Model 3 in 0 to 20 μm particle size range， indicating better particle classification efficiency for rice flour.

Conclusion Among the five air supply structures， the baffle structure in Model 1 had the worst air flow retention effect， with the largest d50 of 30. 8 μm. The windshield ring structure in Model 2 effectively reduced air loss， significantly improving air replenishment， with a d₅₀ approximately 0. 62 μm lower than Model 1. The guiding vane structure in Model 3 effectively weakened air impact and improved air dispersion， demonstrating the most noticeable air replenishment effect， with a d₅₀ 2. 88 μm lower than Model 2. Model 4， which adopted the upper scheme for the air supply structure outlet area， performed poorly， while Model 5，adopting the lower scheme， performed better. Although the d₅₀ of Model 5 was 28. 5 μm， slightly larger than 27. 3 μm in Model 3， the cumulative particle size distribution curve was below that of Model 3， showing a better classification efficiency for rice flour particles. Overall， Model 5 performed the best in the particle size range of 0 to 100 μm.

Keywords：turbo air classifier； air supply structure； air retention capacity； uniformity； dispersion