Lagrangian network analysis of turbulent mixing
| Autor: | Johannes G.M. Kuerten, Giovanni Iacobello, Stefania Scarsoglio, Luca Ridolfi |
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| Přispěvatelé: | Power & Flow, Group Kuerten |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
mathematical foundations
turbulent flows turbulent mixing complex networks Computer science FOS: Physical sciences Network science 01 natural sciences 010305 fluids & plasmas Physics::Fluid Dynamics 0103 physical sciences Mean flow Statistical physics 010306 general physics ComputingMethodologies_COMPUTERGRAPHICS Turbulence Mechanical Engineering Fluid Dynamics (physics.flu-dyn) Particle swarm optimization Physics - Fluid Dynamics Complex network Condensed Matter Physics Mechanics of Materials Weighted network Lagrangian analysis Network analysis |
| Zdroj: | Journal of Fluid Mechanics, 865, 546-562. Cambridge University Press |
| ISSN: | 1469-7645 0022-1120 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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