Experimental study of swirling flow pneumatic liquid-carrying characteristics in the vortex tool inserted tube under liquid loading conditions

Abstract

Liquid unloading by vortex tool is one of the most important applications of swirling flow pneumatic conveying. However, due to swirl decay, the evolution of gas–liquid flow patterns and the dynamic characteristics of pressure drop downstream of the vortex tool are much more complex than those in non-swirling flow. In this study, the gas–liquid flow patterns and pressure drop inside the vortex tool inserted tube (ID = 60 mm) under liquid loading conditions were experimentally studied and compared with those of the plain tube. With the superficial gas velocities ranging from 0.5 to 6.0 m/s and superficial liquid velocities of 0.01, 0.02, and 0.04 m/s, the effects of the structural parameters and stages of vortex tools on the pressure drop were discussed. The experimental results reveal that three distinct swirling flow patterns can be identified downstream of the vortex tool, namely swirling gas column flow, swirling churn flow and swirling annular flow. The insertion of vortex tool facilitates an earlier transition of the churn flow to the annular flow, and the induced swirling flow can restrain the liquid from falling back. The helix angle of the corkscrew deflector has a more significant effect on the pressure drop than its length. By reducing the helix angle from 54° to 45°, the total pressure drop and downstream pressure gradient are significantly decreased, even lower than those of the plain tube. But the series combination of 54° and 45° vortex tools results in a significant increase in the downstream pressure gradient. Additionally, at low gas flow rate, negative frictional pressure drop occurs in both plain tube and vortex tool inserted tube. Hence, the new friction factor correlations were established respectively for the positive and negative friction regions in the cases of the tube with and without vortex tool, and most of the frictional pressure gradient predictions are within an error band less than 20%.