Dynamic Mode Decomposition of inertial particle caustics in Taylor-Green flow

TL;DR

This paper uses dynamic mode decomposition to analyze inertial particle caustics in a Taylor-Green flow, revealing how particle behavior varies with Stokes number and providing insights applicable to more complex flows.

Contribution

It introduces a DMD-based method to characterize inertial particle dynamics and caustic formation in a 2D flow, linking flow structures to particle Stokes number.

Findings

DMD identifies caustic structures in particle flow

Particle Stokes number can be estimated from DMD modes

Method applicable to experimental and turbulent flows

Abstract

Inertial particles advected by a background flow can show complex structures. We consider inertial particles in a 2D Taylor-Green (TG) flow and characterize particle dynamics as a function of the particle's Stokes number using dynamic mode decomposition (DMD) method from particle image velocimetry (PIV) like-data. We observe the formation of caustic structures and analyze them using DMD to (a) determine the Stokes number of the particles, and (b) estimate the particle Stokes number composition. Our analysis in this idealized flow will provide useful insight to analyze inertial particles in more complex or turbulent flows. We propose that the DMD technique can be used to perform a similar analysis on an experimental system.