A simple experiment for observing clustering and dynamics of coalescing particles in air turbulence

TL;DR

This paper introduces a high-resolution experimental platform and methodology for observing and analyzing the clustering and collision dynamics of inertial particles in turbulent air flows, extending measurement capabilities to sub-Kolmogorov scales.

Contribution

The paper presents a novel experimental setup with advanced filtering techniques that enable reliable measurement of particle clustering and collision statistics at previously inaccessible small scales.

Findings

Clustering increases with Stokes number.

Validated workflow reduces spurious particle artifacts.

Measured near-contact collision rates are consistent across filtering methods.

Abstract

A novel experimental platform is developed to investigate the dynamics of inertial particles (micro-droplets) in air turbulence. The goal is to observe particle collision and coalescence in turbulent flows, focusing on its impact on the radial distribution function (RDF) and relative velocity statistics. The main tool is a three-dimensional Lagrangian particle tracking (LPT) system, designed for high-resolution measurements at sub-Kolmogorov scales. The system uses LED illumination with high-speed spinning-disk atomizers, enabling tracking of particles of approximately 10~$\mu$m and larger under controlled turbulence. A minimum resolvable particle separation of $r/\eta \approx 0.1$ is achieved. A central contribution is the identification and mitigation of three dominant sources of spurious particles: FMIS, IIS, and TIF. An angle-based geometric filtering criterion strongly suppresses FMIS artifacts on RDF. These procedures establish a validated workflow for reliable small-scale statistics. Using this framework, RDF and a normalized pseudo-collision rate are measured at near-contact separations for particles with Stokes numbers $St \approx 0.2$--$1.0$. Sub-Kolmogorov clustering increases with Stokes number, and near-contact statistics are consistent through the filtering strategy. This study extends LPT limits and provides a reliable methodology for investigating inertial-particle dynamics at previously inaccessible spatial scales.