Lagrangian network analysis of turbulent mixing

Giovanni Iacobello (Corresponding author), Stefania Scarsoglio, J.G.M. Kuerten, Luca Ridolfi

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)

Abstract

A temporal complex network-based approach is proposed as a novel formulation to investigate turbulent mixing from a Lagrangian viewpoint. By exploiting a spatial proximity criterion, the dynamics of a set of fluid particles is geometrized into a time-varying weighted network. Specifically, a numerically solved turbulent channel flow is employed as an exemplifying case. We show that the time-varying network is able to clearly describe the particle swarm dynamics, in a parametrically robust and computationally inexpensive way. The network formalism enables us to straightforwardly identify transient and long-term flow regimes, the interplay between turbulent mixing and mean flow advection and the occurrence of proximity events among particles. Thanks to their versatility and ability to highlight significant flow features, complex networks represent a suitable tool for Lagrangian investigations of turbulent mixing. The present application of complex networks offers a powerful resource for Lagrangian analysis of turbulent flows, thus providing a further step in building bridges between turbulence research and network science.

Original languageEnglish
Pages (from-to)546-562
Number of pages17
JournalJournal of Fluid Mechanics
Volume865
DOIs
Publication statusPublished - 25 Apr 2019

Keywords

  • mathematical foundations
  • turbulent flows
  • turbulent mixing

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