Reconstruction of large-scale structures and acoustic radiation from a turbulent M = 0.9 jet using proper orthogonal decomposition

Abstract

The Proper Orthogonal Decomposition (POD) uses data to generate an optimal set of basis functions that represent the "energy" of the data, defined by a user-selected norm. This basis is optimal in the sense that a finite number of these modes represent more of the energy than any other set of orthogonal modes. The POD can be seen, on one hand, as a way to define energetic structures in a flow, essentially a generalization of the traditional Fourier-based spectrum to treat data that is inhomogeneous in one or more coordinate directions. But the POD modes are perhaps more useful in quantitatively modeling the dynamics of the flow, via Galerkin projection of the governing equations onto a relatively small number of modes in order to generate a reduced-order model.

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