Study of preferential concentration in turbulent flows using combined graph theory and Voronoi analysis

Collisions between particles in turbulent flows may he enhanced by the formation of clusters due to the preferential concentration effect. However, the internal sub-structure of the clusters remains unclear. This paper describes using the degree of a node and the shortest path length from graph theory, in combination with Voronoi analysis, to gain further insight into both the structure and internal sub-structure of a cluster. This is demonstrated on experimental measurements obtained from a confined counter-flow/jet system. A minority of the particles, which comprise large clusters, are found to have a significantly large number of neighboring particles for collisions. However, particles which comprise small clusters typically have a random number of neighbors. Published under an exclusive license by AIP Publishing.

Automated summary

This study uses a combination of graph theory and Voronoi analysis to investigate the structure and internal sub-structure of clusters. Experimental results show that large clusters have a significantly large number of neighboring particles for collisions, while small clusters have a random number of neighbors.