Nonlinear model reduction: A comparison between POD-Galerkin and POD-DEIM methods

Denis Sipp, Miguel Fosas de Pando, Peter J. Schmid

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Several nonlinear model reduction techniques are compared for the three cases of the non-parallel version of the Kuramoto-Sivashinsky equation, the transient regime of flow past a cylinder at Re=100 and fully developed flow past a cylinder at the same Reynolds number. The linear terms of the governing equations are reduced by Galerkin projection onto a POD basis of the flow state, while the reduced nonlinear convection terms are obtained either by a Galerkin projection onto the same state basis, by a Galerkin projection onto a POD basis representing the nonlinearities or by applying the Discrete Empirical Interpolation Method (DEIM) to a POD basis of the nonlinearities. The quality of the reduced order models is assessed as to their stability, accuracy and robustness, and appropriate quantitative measures are introduced and compared. In particular, the properties of the reduced linear terms are compared to those of the full-scale terms, and the structure of the nonlinear quadratic terms is analyzed as to the conservation of kinetic energy. It is shown that all three reduction techniques provide excellent and similar results for the cases of the Kuramoto-Sivashinsky equation and the limit-cycle cylinder flow. For the case of the transient regime of flow past a cylinder, only the pure Galerkin techniques are successful, while the DEIM technique produces reduced-order models that diverge in finite time.
Original languageEnglish (US)
JournalComputers and Fluids
Volume208
DOIs
StatePublished - Aug 15 2020
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science(all)

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