Approximating space-time flow statistics from a limited set of known correlations

Aaron Towne, Xiang Yang, Adrian Lozano-Durán

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We apply a method recently developed by Towne1 for approximating space-time flow statistics from a limited set of measurements to a channel flow at friction Reynolds number Reτ = 187. The method uses the known data to infer the statistics of certain nonlinear terms that act as a forcing on the linearized Navier-Stokes equations, which in turn imply values for the unknown flow statistics through application of the resolvent operator. Using input data at a wall-normal position of y+ = 37, accurate predictions of the velocity energy spectra and autocorrelations are obtained in the near-wall region, while significant under-predictions are observed further from the wall. Additional work is required to analyze the impact of the wall-normal location of the known input data and assess the performance of the method at higher Reynolds numbers.

Original languageEnglish (US)
Title of host publication2018 Fluid Dynamics Conference
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105531
DOIs
StatePublished - 2018
Event48th AIAA Fluid Dynamics Conference, 2018 - Atlanta, United States
Duration: Jun 25 2018Jun 29 2018

Publication series

Name2018 Fluid Dynamics Conference

Other

Other48th AIAA Fluid Dynamics Conference, 2018
CountryUnited States
CityAtlanta
Period6/25/186/29/18

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Engineering (miscellaneous)

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