Abstract

The spatio-temporal features of the velocity field of a fully-developed turbulent channel flow are investigated through the natural visibility graph (NVG) method, which is able to fully map the intrinsic structure of the time-series into complex networks. Time-series of the three velocity components, (u,v,w), are analyzed at fixed grid-points of the whole three-dimensional domain. Each time-series was mapped into a network by means of the NVG algorithm, so that each network corresponds to a grid-point of the simulation. The degree centrality, the transitivity and the here proposed mean link-length were evaluated as indicators of the global visibility, inter-visibility, and mean temporal distance among nodes, respectively. The metrics were averaged along the directions of homogeneity (x,z) of the flow, so they only depend on the wall-normal coordinate, y+. The visibility-based networks, inheriting the flow field features, unveil key temporal properties of the turbulent time-series and their changes moving along y+. Although intrinsically simple to be implemented, the visibility graph-based approach offers a promising and effective support to the classical methods for accurate time-series analyses of inhomogeneous turbulent flows.

Highlights

  • One of the most challenging research topic in classical physics is represented by turbulent flows

  • The procedure described in the previous section is adopted to analyze the velocity time-series of the turbulent channel flow, starting from the streamwise component, u∗, and considering the other velocity components, v∗ and w∗

  • The global network-metrics { k ; T r; d1n }, computed for each of the Sx × Sz grid-point, have regular trends similar to the averaged ones shown in Fig. 3, which are representative of the global metrics measured along the wall-normal direction and in different (x, z) coordinates

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Summary

Introduction

One of the most challenging research topic in classical physics is represented by turbulent flows. Their great importance is evident through a number of natural phenomena (e.g., rivers, atmospheric and oceanic streams), industrial and civil applications (e.g., flow through pumps, heat exchangers, wake flows of vehicles and aircraft, wind-building interactions) in which turbulence is involved. The study of wall-bounded turbulent flows, in particular, is a very active research field, due to the great attention paid to the fluid-structure interaction. Deeply studied from a phenomenological and theoretical point of view, the turbulence dynamics, due to their complexity, are still not fully understood [1, 2]. Mainly relying on statistical techniques, are typically used to explore and analyze turbulent flows

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