Matthew F. Barone

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With the increasing role of computational modeling in engineering design, performance estimation, and safety assessment , improved methods are needed for comparing computational results and experimental measurements. Traditional methods of graphically comparing computational and experimental results, though valuable, are essentially qualitative. Computable(More)
Keywords: Reduced order models Galerkin projection Energy method Linearized Euler equations a b s t r a c t The Galerkin projection procedure for construction of reduced order models of compress-ible flow is examined as an alternative discretization of the governing differential equations. The numerical stability of Galerkin models is shown to depend on the(More)
Discrete-optimal model-reduction techniques such as the Gauss–Newton with Approximated Tensors (GNAT) method have shown promise, as they have generated stable, accurate solutions for large-scale turbulent, compressible flow problems where standard Galerkin techniques have failed. However, there has been limited comparative analysis of the two approaches.(More)
Keywords: Reduced order model (ROM) Proper orthogonal decomposition (POD)/ Galerkin projection Linear hyperbolic/incompletely parabolic systems Linear time-invariant (LTI) systems Numerical stability Lyapunov equation a b s t r a c t An approach for building energy-stable Galerkin reduced order models (ROMs) for linear hyperbolic or incompletely parabolic(More)
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