A low-cost, goal-oriented ‘compact proper orthogonal decomposition’ basis for model reduction of static systems

Kevin Carlberg, Charbel Farhat

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

A novel model reduction technique for static systems is presented. The method is developed using a goal-oriented framework, and it extends the concept of snapshots for proper orthogonal decomposition (POD) to include (sensitivity) derivatives of the state with respect to system input parameters. The resulting reduced-order model generates accurate approximations due to its goal-oriented construction and the explicit 'training' of the model for parameter changes. The model is less computationally expensive to construct than typical POD approaches, since efficient multiple right-hand side solvers can be used to compute the sensitivity derivatives. The effectiveness of the method is demonstrated on a parameterized aerospace structure problem. © 2010 John Wiley & Sons, Ltd.
Original languageEnglish (US)
Pages (from-to)381-402
Number of pages22
JournalInternational Journal for Numerical Methods in Engineering
Volume86
Issue number3
DOIs
StatePublished - Dec 10 2010
Externally publishedYes

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