Multi-scale analysis on particle dynamics in horizontal pneumatic conveying with oscillating air flow

This study focuses on multi-scale particle dynamics of horizontal pneumatic conveying equipped with two types of soft fins at the air velocity of the minimum pressure drop. The particle velocity fields of non-fin and using soft fin's cases are measured by high-speed particle image velocimetry. Then the particle fluctuation velocities are decomposed into various scales based on one-dimensional orthogonal wavelet decomposition. It is found that the non-uniform case of Fin260 yields the highest axial-and vertical-particle velocities and fluctuation energies, giving rise to the lowest pressure drop and conveying air velocity. The overall relative energy distributions of wavelet components suggest that the particle fluctuation energies become more concentrated at wavelet levels 3 and 4 by using fins, especially for the case of non-uniform Fin260. The energy concentration on specific wavelet levels indicates a more organized particle motions under the effect of air turbulence induced by non-uniform soft fins. The correlation analysis suggests that the spatial correlation of wavelet component is associated with the contribution of wavelet component to the measured particle fluctuation energy. The oscillating soft fins modulate the air turbulence and promote the particle motions to be spatially correlated in a range of specific frequency.

Automated summary

This study investigates the multi-scale particle dynamics in a horizontal pneumatic conveying system with two types of soft fins. Measurements of particle velocity fields are conducted using high-speed particle image velocimetry for cases with and without fins. The particle fluctuation velocities are then decomposed into different scales using one-dimensional orthogonal wavelet decomposition. The results show that the non-uniform case of Fin260 yields the highest particle velocities and fluctuation energies, resulting in the lowest pressure drop and conveying air velocity. The energy distributions of wavelet components indicate that the particle fluctuation energies become more concentrated at wavelet levels 3 and 4 when using fins, especially for the non-uniform Fin260 case. Correlation analysis reveals that the spatial correlation of wavelet components is associated with their contribution to the measured particle fluctuation energy. Oscillating soft fins modulate the air turbulence and promote spatially correlated particle motions within a specific frequency range.