Assessment of Sub-Grid Scale Tensors in the context of Coarse Large Eddy Simulations

Pranav Chandramouli 1 Dominique Heitz 2 Sylvain Laizet 3 Etienne Memin 1
1 FLUMINANCE - Fluid Flow Analysis, Description and Control from Image Sequences
IRMAR - Institut de Recherche Mathématique de Rennes, IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture, Inria Rennes – Bretagne Atlantique
Abstract : Large Eddy Simulations (LES) are effectively used as reduced cost alternative to Direct Numerical Simulations (DNS). However, LES are still computationally expensive for complex flows. This brings into the forefront the concept of Coarse Large Eddy Simulations (cLES) involving coarser meshes and hence cheaper computations. An associated limitation with cLES is the accuracy and stability of the sub-grid scale (SGS) model to be used. This is the focus of this poster wherein several SGS models have been compared for the simple case of channel flow at coarse resolution. The development of LES SGS models has been an area of scientific research for many decades starting with Smagorinsky [6]. Recent developments in this field have produced many modern SGS models which have been shown to work better than classical models [3, 2]. In this study, the classical models namely, classic Smagorinsky as well as its dynamic version along with the Wall Adaptive Local-Eddy Viscosity (WALE) model, have been compared with the newly developed uncertainty based models of [3] and the implicit LES version of [2] in the context of cLES. The accuracy of the statistics have been analysed by comparison with the channel flow data of [4].
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UK Fluids Conference 2016, Sep 2016, London, United Kingdom
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Soumis le : jeudi 14 décembre 2017 - 12:05:19
Dernière modification le : jeudi 15 novembre 2018 - 11:58:56


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  • HAL Id : hal-01663756, version 1


Pranav Chandramouli, Dominique Heitz, Sylvain Laizet, Etienne Memin. Assessment of Sub-Grid Scale Tensors in the context of Coarse Large Eddy Simulations. UK Fluids Conference 2016, Sep 2016, London, United Kingdom. 〈hal-01663756〉



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