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Theoretical and Computational Fluid Dynamics

, Volume 27, Issue 6, pp 787–815 | Cite as

POD-spectral decomposition for fluid flow analysis and model reduction

  • A. Cammilleri
  • F. Gueniat
  • J. Carlier
  • L. Pastur
  • E. Memin
  • F. Lusseyran
  • G. ArtanaEmail author
Original Article

Abstract

We propose an algorithm that combines proper orthogonal decomposition with a spectral method to analyze and extract reduced order models of flows from time data series of velocity fields. The flows considered in this study are assumed to be driven by non-linear dynamical systems exhibiting a complex behavior within quasiperiodic orbits in the phase space. The technique is appropriate to achieve efficient reduced order models even in complex cases for which the flow description requires a discretization with a fine spatial and temporal resolution. The proposed analysis enables to decompose complex flow dynamics into modes oscillating at a single frequency. These modes are associated with different energy levels and spatial structures. The approach is illustrated using time-resolved PIV data of a cylinder wake flow with associated Reynolds number equal to 3,900.

Keywords

Reduced order modeling POD DMD Spectral analysis 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • A. Cammilleri
    • 1
  • F. Gueniat
    • 2
  • J. Carlier
    • 3
  • L. Pastur
    • 2
  • E. Memin
    • 3
  • F. Lusseyran
    • 2
  • G. Artana
    • 1
    Email author
  1. 1.LFD-F.I. Universidad de Buenos Aires-CONICETBuenos AiresArgentina
  2. 2.University Paris Sud 11-LIMSI-CNRSOrsayFrance
  3. 3.Fluminance-INRIARennesFrance

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