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Assessment of two-parameter mixed models for large eddy simulations of transitional and turbulent flows
Authors:Lee  Young Mo  Hwang   Hyeon Gyu  Lee   Jae Hwa  Lee   Jungil  Park   Jae Sung
Affiliation:1.Department of Mechanical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Korea
;2.Department of Mechanical Engineering, Ajou University, Suwon, 16499, Korea
;3.Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA
;
Abstract:

In the present study, improved two-parameter mixed models for large eddy simulations are proposed based on previous two-parameter mixed models of Salvetti and Banerjee [1] and Horiuti [2]. The subgrid-scale (SGS) stress in our models is decomposed into the modified Leonard stress, modified cross stress and modified SGS Reynolds stress terms. Although the modified Leonard stress term is explicitly calculated based on the scale-similarity, the modified cross stress term is built using an extension of the filtered Bardina model proposed by Horiuti [3] for better predictions of the interaction between resolved and unresolved scales (i.e., energy exchange). The modified SGS Reynolds stress is modeled by the dynamic Smagorinsky model or by a dynamic global model, leading to two unknown model coefficients for the modified cross stress and the modified SGS Reynolds stress terms. In order to demonstrate the reliability of the proposed SGS models, large eddy simulations of two types of flows (i.e., a fully developed turbulent channel flow and a transitional boundary layer flow) are performed. It is shown that the modified cross stress term makes an important contribution to the accurate predictions of such flows because the emergence of negative SGS dissipation (backward scatter) by the modified cross stress term decreases the excessive positive SGS dissipation (forward scatter). A direct comparison of the turbulent statistics with those from previous SGS models shows that the proposed SGS models result in better prediction performance both in transitional and turbulent flows.

Keywords:
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