Constrained sparse Galerkin regression

The sparse identification of nonlinear dynamics (SINDy) is a recently proposed data-driven modelling framework that uses sparse regression techniques to identify nonlinear low-order models. With the goal of low-order models of a fluid flow, we combine this approach with dimensionality reduction tech...

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Vydáno v:	Journal of fluid mechanics Ročník 838; s. 42 - 67
Hlavní autoři:	Loiseau, Jean-Christophe, Brunton, Steven L.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cambridge, UK Cambridge University Press 10.03.2018 Cambridge University Press (CUP)
Témata:	Algorithms Artificial intelligence Cavity flow Circular cylinders Computational fluid dynamics Constraint modelling Cylinders Dynamical systems Dynamics Engineering Sciences Fluid Dynamics Fluid flow Fluids mechanics Frameworks Galerkin method Identification JFM Papers Mathematical models Mechanics Model accuracy Modelling Navier-Stokes equations Nonlinear dynamics Nonlinear systems Partial differential equations Physics Proper Orthogonal Decomposition Reduced order models Regression analysis Regression models Two dimensional flow nonlinear dynamical systems low-dimensional models
ISSN:	0022-1120, 1469-7645
On-line přístup:	Získat plný text
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