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Ninth International Symposium on Turbulence and Shear Flow Phenomena
June 30 - July 3, 2015, University of Melbourne, Australia

DOI: 10.1615/TSFP9

A SCALE SELF-RECOGNITION MIXED SGS MODEL BASED ON THE UNIVERSAL REPRESENTATION OF KOLMOGOROV LENGTH BY GS VARIABLES

pages 49-54
DOI: 10.1615/TSFP9.90
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ABSTRACT

Direct numerical simulation of homogenous isotropic turbulence (HIT) have been conducted at relatively high Reynolds numbers. By analyzing the DNS database, characteristics of GS-SGS energy transfer are investigated in detail. Especially, dependences of GS-SGS energy transfer by Leonard, cross and Reynolds terms, and the total GS-SGS energy transfer on filter-width to Kolmogorov scale, Δ/η, are revealed. The characteristics of conventional eddy viscosity models and scale similarity model are investigated in terms of the GS-SGS energy transfer. It is found that Smagorinsky model can predict energy transfer by Reynolds term well for large Δ where Reynolds term is dominant and Bardina model has a potential to predict cross term well especially for small Δ where cross term is dominant. Based on the assumption of local equilibrium and the fact that the Smagorinsky coefficient is the function of Δ/η, a new method to predict Δ/η by using only resolved scale and a new subgrid-scale (SGS) model, a scale self-recognition mixed SGS model, are proposed. Superiority of the scale self-recognition mixed SGS model has been demonstrated through static and dynamic tests in HIT and turbulent channel flow. The correlation coefficient between the total GS-SGS energy transfer obtained from filtered DNS data and statically predicted by the proposed model is very high with any size of Δ in HIT. Compared with the conventional SGS models, the present model dynamically gives the best prediction of both instantaneous and statistical characteristics of the turbulent flows.

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