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Broadband reconstruction of inhomogeneous turbulence using spectral proper orthogonal decomposition and Gabor modes

Published online by Cambridge University Press:  06 February 2020

A. S. Ghate Open the ORCID record for A. S. Ghate [Opens in a new window] ,
A. Towne Open the ORCID record for A. Towne [Opens in a new window]  and
S. K. Lele
A. S. Ghate
Affiliation:
Department of Aeronautics and Astronautics, Stanford University, Stanford, CA 94305, USA
A. Towne
Affiliation:
Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
S. K. Lele*
Affiliation:
Department of Aeronautics and Astronautics, Stanford University, Stanford, CA 94305, USA Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
*
†Email address for correspondence: lele@stanford.edu
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Abstract

A new methodology to construct three-dimensional, temporally stationary but spatially inhomogeneous, incompressible turbulence is presented. The method combines use of the data-driven spectral proper orthogonal decomposition (SPOD) to identify and isolate large-scale coherent motions of the flow, together with a physics-based enrichment algorithm using spatiotemporally localized Gabor modes that capture the inertial subrange turbulence. This fusion of data-driven and physics-based methods enables a statistically correct reconstruction of broadband turbulent flows using fewer modes than would be required using SPOD alone. To demonstrate the approach, we consider the problem of reconstructing wake turbulence on a plane downstream of a dragging actuator disk impinged by homogeneous isotropic turbulence. The reconstructed flow has single- and two-point correlations that are consistent with the reference high-resolution simulation data and could be used to generate statistically consistent inflow boundary conditions for subsequent simulations.

JFM classification

Turbulent Flows: Shear layer turbulence
Type
JFM Rapids
Information
Journal of Fluid Mechanics , Volume 888 , 10 April 2020 , R1
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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