Detection of dominant large-scale coherent structures in turbulent pipe flow

TL;DR

This paper identifies large-scale coherent structures in turbulent pipe flow at Re_tau=181 using a novel Dynamic Mode Decomposition approach, revealing key flow features with a low-dimensional model.

Contribution

It introduces the Characteristic Dynamic Mode Decomposition (CDMD) method to detect and analyze dominant flow structures in turbulent pipe flow, providing a low-rank physical space model.

Findings

Captured flow features with about 10 modes

Identified modes separated by axial length scale and isotropy

Reconstructed flow energy distribution and stresses

Abstract

Large-scale coherent structures are identified in turbulent pipe flow at $Re_\tau=181$ by having long lifetimes, living on large scales and travelling with a certain group velocity. A Characteristic Dynamic Mode Decomposition (CDMD) is used to detect events which meet these criteria. To this end, a temporal sequence of state vectors from Direct Numerical Simulations are rotated in space-time such that persistent dynamical modes on a hyper-surface are found travelling along its normal in space-time, which serves as the new time-like coordinate. Reconstruction of the candidate modes in physical space gives the low rank model of the flow. The modes within this subspace are highly aligned, but are separated from the remaining modes by larger angles. We are able to capture the essential features of the flow like the spectral energy distribution and Reynolds stresses with a subspace consisting of about 10 modes. The remaining modes are collected in two further subspaces, which distinguish themselves by their axial length scale and degree of isotropy.