Reliable reduced-order models for time-dependent linearized Euler equations

doi:10.1016/j.jcp.2012.04.019

Reliable reduced-order models for time-dependent linearized Euler equations

2012-06-01

27

PRE

AI

G

Gilles Serre *

P

PruskiMarek (Philippe Lafon)

DOI：10.1016/j.jcp.2012.04.019

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Abstract

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Development of optimal reduced-order models for linearized Euler equations is investigated. Recent methods based on proper orthogonal decomposition (POD), applicable for high-order systems, are presented and compared. Particular attention is paid to the link between the choice of the projection and the efficiency of the reduced model. A stabilizing projection is introduced to induce a stable reduced-order model at finite time even if the energy of the physical model is growing. The proposed method is particularly well adapted for time-dependent hyperbolic systems and intrinsically skew-symmetric models. This paper also provides a common methodology to reliably reduce very large nonsymmetric physical problems. (C) 2012 Elsevier Inc. All rights reserved.

Keywords:

Reduced-order models (ROMs)

Nonsymmetric systems

Compressible flows

Proper orthogonal decomposition (POD)

Balanced-POD

Symmetrizer

Stabilizing projection

Reliable reduced-order models for time-dependent linearized Euler equations

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