Dynamic mode decomposition of numerical and experimental data

The description of coherent features of fluid flow is essential to our understanding of fluid-dynamical and transport processes. A method is introduced that is able to extract dynamic information from flow fields that are either generated by a (direct) numerical simulation or visualized/measured in...

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Vydáno v:	Journal of fluid mechanics Ročník 656; číslo August; s. 5 - 28
Hlavní autor:	SCHMID, PETER J.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cambridge, UK Cambridge University Press 10.08.2010 Cambridge University Press (CUP)
Témata:	Channel flow Computational fluid dynamics Computational methods in fluid dynamics Dynamical systems Dynamics Engineering Sciences Exact sciences and technology Fluid dynamics Fluid flow Fluid mechanics Fluids mechanics Fundamental areas of phenomenology (including applications) Instability Mathematical models Mechanics Physics Stability Transport processes Computational fluid dynamics Orthogonal function Digital simulation Eigenfunctions Coherent structures Data processing Flow pattern Modelling Domain decomposition Dynamical systems
ISSN:	0022-1120, 1469-7645
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	The description of coherent features of fluid flow is essential to our understanding of fluid-dynamical and transport processes. A method is introduced that is able to extract dynamic information from flow fields that are either generated by a (direct) numerical simulation or visualized/measured in a physical experiment. The extracted dynamic modes, which can be interpreted as a generalization of global stability modes, can be used to describe the underlying physical mechanisms captured in the data sequence or to project large-scale problems onto a dynamical system of significantly fewer degrees of freedom. The concentration on subdomains of the flow field where relevant dynamics is expected allows the dissection of a complex flow into regions of localized instability phenomena and further illustrates the flexibility of the method, as does the description of the dynamics within a spatial framework. Demonstrations of the method are presented consisting of a plane channel flow, flow over a two-dimensional cavity, wake flow behind a flexible membrane and a jet passing between two cylinders.
AbstractList	The description of coherent features of fluid flow is essential to our understanding of fluid-dynamical and transport processes. A method is introduced that is able to extract dynamic information from flow fields that are either generated by a (direct) numerical simulation or visualized/measured in a physical experiment. The extracted dynamic modes, which can be interpreted as a generalization of global stability modes, can be used to describe the underlying physical mechanisms captured in the data sequence or to project large-scale problems onto a dynamical system of significantly fewer degrees of freedom. The concentration on subdomains of the flow field where relevant dynamics is expected allows the dissection of a complex flow into regions of localized instability phenomena and further illustrates the flexibility of the method, as does the description of the dynamics within a spatial framework. Demonstrations of the method are presented consisting of a plane channel flow, flow over a two-dimensional cavity, wake flow behind a flexible membrane and a jet passing between two cylinders. © 2010 Cambridge University Press. The description of coherent features of fluid flow is essential to our understanding of fluid-dynamical and transport processes. A method is introduced that is able to extract dynamic information from flow fields that are either generated by a (direct) numerical simulation or visualized/measured in a physical experiment. The extracted dynamic modes, which can be interpreted as a generalization of global stability modes, can be used to describe the underlying physical mechanisms captured in the data sequence or to project large-scale problems onto a dynamical system of significantly fewer degrees of freedom. The concentration on subdomains of the flow field where relevant dynamics is expected allows the dissection of a complex flow into regions of localized instability phenomena and further illustrates the flexibility of the method, as does the description of the dynamics within a spatial framework. Demonstrations of the method are presented consisting of a plane channel flow, flow over a two-dimensional cavity, wake flow behind a flexible membrane and a jet passing between two cylinders. The description of coherent features of fluid flow is essential to our understanding of fluid-dynamical and transport processes. A method is introduced that is able to extract dynamic information from flow fields that are either generated by a (direct) numerical simulation or visualized/measured in a physical experiment. The extracted dynamic modes, which can be interpreted as a generalization of global stability modes, can be used to describe the underlying physical mechanisms captured in the data sequence or to project large-scale problems onto a dynamical system of significantly fewer degrees of freedom. The concentration on subdomains of the flow field where relevant dynamics is expected allows the dissection of a complex flow into regions of localized instability phenomena and further illustrates the flexibility of the method, as does the description of the dynamics within a spatial framework. Demonstrations of the method are presented consisting of a plane channel flow, flow over a two-dimensional cavity, wake flow behind a flexible membrane and a jet passing between two cylinders. [PUBLICATION ABSTRACT]
Author	SCHMID, PETER J.
Author_xml	– sequence: 1 givenname: PETER J. surname: SCHMID fullname: SCHMID, PETER J. email: peter@ladhyx.polytechnique.fr organization: Laboratoire d'Hydrodynamique (LadHyX), CNRS-École Polytechnique, 91128 Palaiseau, France
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23071745$$DView record in Pascal Francis https://polytechnique.hal.science/hal-01020654$$DView record in HAL
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SubjectTerms	Channel flow Computational fluid dynamics Computational methods in fluid dynamics Dynamical systems Dynamics Engineering Sciences Exact sciences and technology Fluid dynamics Fluid flow Fluid mechanics Fluids mechanics Fundamental areas of phenomenology (including applications) Instability Mathematical models Mechanics Physics Stability Transport processes
Title	Dynamic mode decomposition of numerical and experimental data
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