Spatial characterization of turbulent channel flow via complex networks

TL;DR

This paper introduces a novel network-based method to analyze the spatial structure of turbulent channel flow, revealing persistent near-wall patterns and information flow pathways using complex network measures.

Contribution

It presents a new approach applying complex network analysis to turbulent flow data, providing deeper insights into spatial structures and dynamics beyond traditional correlation methods.

Findings

Long-range links are localized near the wall and associated with coherent streaks.

Long-range links facilitate kinematic information flow across the flow.

Network measures reveal the importance of indirect connections in turbulence structure.

Abstract

A network-based analysis of a turbulent channel flow numerically solved at $Re_\tau=180$ is proposed as an innovative perspective for the spatial characterization of the flow field. Two spatial networks corresponding to the streamwise and wall-normal velocity components are built, where nodes represent portions of volume of the physical domain. For each network, links are active if the correlation coefficient of the corresponding velocity component between pairs of nodes is sufficiently high, thus unveiling the strongest kinematic relations. Several network measures are studied in order to explore the interrelations between nodes and their neighbors. Specifically, long-range links are localized between near-wall regions and associated with the temporal persistence of coherent patterns, namely high and low speed streaks. Furthermore, long-range links play a crucial role as intermediary for the kinematic information flow, as emerges from the analysis of indirect connections between nodes. The proposed approach provides a framework to investigate spatial structures of the turbulent dynamics, showing the full potential of complex networks. Although the network analysis is based on the two-point correlation, it is able to advance the level of information, by exploiting the texture created by active links in all directions. Based on the observed findings, the current approach can pave the way for an enhanced spatial interpretation of the turbulence dynamics.