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Modelling Separation from Curved Surfaces with Anisotropy-Resolving Turbulence Closures

...and related observations on Large Eddy Simulation

  • Chapter
Modelling Fluid Flow

Abstract

Notwithstanding recent progress in Large Eddy Simulation, statistical modelling continues to be the principal approach to representing the effects of turbulence in CFD for engineering flows. This is likely to remain the case, at least for several decades, especially in relation to flows that are strongly affected by viscous near-wall processes. Flows featuring separation from curved surfaces fall into this category, and these are among the most difficult to model accurately because of their high sensitivity to the details of the turbulence field. This paper reviews some recent experience and current work on predicting separation from continuous surfaces with non-linear eddy-viscosity models and second-moment closure. Reasons for successes as well as failures are discussed by reference to several flows. The paper concludes with a brief discussion of the challenges facing Large Eddy Simulation in relation to separated high-Reynolds-number near-wall flows.

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Author information

Authors and Affiliations

  1. Department of Aeronautics, Imperial College London, UK

    Michael Leschziner

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  1. Michael Leschziner
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Editors and Affiliations

  1. Department of Fluid Mechanics, Budapest University of Technology and Economics, Bertalan Lajos u. 4-6, H-1111, Budapest, Hungary

    János Vad  & Tamás Lajos  & 

  2. Lehrstuhl für Fluidmechanik, Abteilung Hydraulische Maschinen, Technische Universität München, Boltzmannstr. 15, D-85748, Garching, Germany

    Rudolf Schilling

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Leschziner, M. (2004). Modelling Separation from Curved Surfaces with Anisotropy-Resolving Turbulence Closures. In: Vad, J., Lajos, T., Schilling, R. (eds) Modelling Fluid Flow. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-08797-8_2

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  • DOI: https://doi.org/10.1007/978-3-662-08797-8_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-06034-2

  • Online ISBN: 978-3-662-08797-8

  • eBook Packages: Springer Book Archive

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