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Approximate Deconvolution Models of Turbulence [electronic resource] : Analysis, Phenomenology and Numerical Analysis / by William J. Layton, Leo Rebholz.

By: Layton, William J [author.].
Contributor(s): Rebholz, Leo [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Mathematics: 2042Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012Description: VIII, 184p. 22 illus., 11 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244094.Subject(s): Mathematics | Numerical analysis | Hydraulic engineering | Mathematics | Numerical Analysis | Engineering Fluid DynamicsDDC classification: 518 Online resources: Click here to access online
Contents:
1 Introduction -- 2 Large Eddy Simulation -- 3 Approximate Deconvolution Operators and Models -- 4 Phenomenology of ADMs -- 5 Time Relaxation Truncates Scales -- 6 The Leray-Deconvolution Regularization -- 7 NS-alpha- and NS-omega-Deconvolution Regularizations.
In: Springer eBooksSummary: This volume presents a mathematical development of a recent approach to the modeling and simulation of turbulent flows based on methods for the approximate solution of inverse problems. The resulting Approximate Deconvolution Models or ADMs have some advantages over more commonly used turbulence models – as well as some disadvantages. Our goal in this book is to provide a clear and complete mathematical development of ADMs, while pointing out the difficulties that remain. In order to do so, we present the analytical theory of ADMs, along with its connections, motivations and complements in the phenomenology of and algorithms for ADMs.
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1 Introduction -- 2 Large Eddy Simulation -- 3 Approximate Deconvolution Operators and Models -- 4 Phenomenology of ADMs -- 5 Time Relaxation Truncates Scales -- 6 The Leray-Deconvolution Regularization -- 7 NS-alpha- and NS-omega-Deconvolution Regularizations.

This volume presents a mathematical development of a recent approach to the modeling and simulation of turbulent flows based on methods for the approximate solution of inverse problems. The resulting Approximate Deconvolution Models or ADMs have some advantages over more commonly used turbulence models – as well as some disadvantages. Our goal in this book is to provide a clear and complete mathematical development of ADMs, while pointing out the difficulties that remain. In order to do so, we present the analytical theory of ADMs, along with its connections, motivations and complements in the phenomenology of and algorithms for ADMs.

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