Galerkin v. least-squares Petrov–Galerkin projection in nonlinear model reduction

Least-squares Petrov–Galerkin (LSPG) 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....

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Bibliographic Details
Published in:Journal of computational physics 2017-02, Vol.330, p.693-734
Main Authors: Carlberg, Kevin, Barone, Matthew, Antil, Harbir
Format: Article
Language:English
Subjects:
CFD
Compressible flow
Computational fluid dynamics
Computational physics
Computer simulation
Errors
Finite element analysis
Galerkin method
Galerkin projection
GNAT
Integrators
Least squares
Least-squares Petrov–Galerkin projection
Mathematical models
Model reduction
Nonlinear systems
Numerical analysis
Optimization
Reduced order models
Runge-Kutta method
Simulation
Tensors
Turbulent flow
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