Multi-parameter analysis of aero-icing problems via proper orthogonal decomposition and multidimensional interpolation

Marco Fossati, Wagdi G. Habashi

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Steady and unsteady three-dimensional viscous turbulent aero-icing simulations are computationally expensive, especially for certification campaigns when broad parametric studies are needed. To overcome the computational effort of such investigations, a Reduced Order Modeling approach, based on Proper Orthogonal Decomposition and Kriging interpolation, is proposed. Using a database of high-fidelity numerical simulations, experimental data, or combinations of both, the proposed technique allows approximating solutions by linear combination of a limited number of eigenfunctions. Bayesian Kriging, a recent variant, is used to obtain the scalar coefficients for the expansion. The accuracy of the proposed method is assessed against reference solutions from two- and three-dimensional aero-icing simulations as well as against experimental data.
Original languageEnglish
Pages (from-to)946-960
Number of pages15
JournalAIAA Journal
Volume51
Issue number4
DOIs
Publication statusPublished - 2013

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