Spatial characterization of turbulent channel flow via complex networks

Abstract

A network-based analysis of a turbulent channel flow numerically solved at $R{e}_{\tau }=180$ 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.

References in corpus (22)

• Statistical mechanics of complex networks
• The structure and function of complex networks
• Characterization of complex networks: A survey of measurements
• Hierarchical Structure in Financial Markets
• The complex network of global cargo ship movements
• A tool for filtering information in complex systems
• Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods
• Coherent structures in wall-bounded turbulence
• Combining complex networks and data mining: why and how
• Statistical properties of visibility graph of energy dissipation rates in three-dimensional fully developed turbulence
• Network Structure of Two-Dimensional Decaying Isotropic Turbulence
• Flow networks: A characterization of geophysical fluid transport
• Non-linear dependence and teleconnections in climate data: sources, relevance, nonstationarity
• Node-weighted measures for complex networks with spatially embedded, sampled, or differently sized nodes
• Space-time correlations in turbulent flow: A review
• How complex climate networks complement eigen techniques for the statistical analysis of climatological data
• Visibility graph analysis of wall turbulence time-series
• Correlation networks from flows. The case of forced and time-dependent advection-diffusion dynamics
• Complex Networks Unveiling Spatial Patterns in Turbulence
• Fully Developed Turbulence in the view of Horizontal Visibility Graphs
• From time-series to complex networks: Application to the cerebrovascular flow patterns in atrial fibrillation
• Spatio-temporal organization of dynamics in a two-dimensional periodically driven vortex flow: a Lagrangian flow network perspective

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