On the origin of frequency sparsity in direct numerical simulations of turbulent pipe flow
Author(s) -
Francisco Gómez,
H. M. Blackburn,
Murray Rudman,
Beverley McKeon,
Mitul Luhar,
Rashad Moarref,
A. S. Sharma
Publication year - 2014
Publication title -
physics of fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.188
H-Index - 180
eISSN - 1089-7666
pISSN - 1070-6631
DOI - 10.1063/1.4900768
Subject(s) - physics , resolvent , turbulence , direct numerical simulation , flow (mathematics) , dynamic mode decomposition , frequency domain , statistical physics , bounded function , domain decomposition methods , pipe flow , domain (mathematical analysis) , mathematics , mechanics , algorithm , classical mechanics , mathematical analysis , finite element method , reynolds number , thermodynamics
The possibility of creating reduced-order models for canonical wall-bounded turbulent flows based on exploiting energy sparsity in frequency domain, as proposed by Bourguignon et al. [Phys. Fluids26, 015109 (2014)], is examined. The present letter explains the origins of energetically sparse dominant frequencies and provides fundamental information for the design of such reduced-order models. The resolvent decomposition of a pipe flow is employed to consider the influence of finite domain length on the flow dynamics, which acts as a restriction on the possible wavespeeds in the flow. A forcing-to-fluctuation gain analysis in the frequency domain reveals that large sparse peaks in amplification occur when one of the possible wavespeeds matches the local wavespeed via the critical layer mechanism. A link between amplification and energy is provided through the similar characteristics exhibited by the most energetically relevant flow structures, arising from a dynamic mode decomposition of direct numerical simulation data, and the resolvent modes associated with the most amplified sparse frequencies. These results support the feasibility of reduced-order models based on the selection of the most amplified modes emerging from the resolvent model, leading to a novel computationally efficient method of representing turbulent flows.
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