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

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.

preprint2021arXivOpen access
Omstavan SamantJaya Kumar AlageshanSarveshwar SharmaAnimesh Kuley
Machine Learningphysics.flu-dyn
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Omstavan SamantJaya Kumar AlageshanSarveshwar SharmaAnimesh Kuley

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