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Implicit large-eddy simulation applied to turbulent channel flow with periodic constrictions

机译:隐性大涡模拟应用于周期性收缩湍流

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The subgrid-scale (SGS) model in a large-eddy simulation (LES) operates on a range of scales which is marginally resolved by discretization schemes. Accordingly, the discretization scheme and the subgrid-scale model are linked. One can exploit this link by developing discretization methods from subgrid-scale models, or the converse. Approaches where SGS models and numerical discretizations are fully merged are called implicit LES (ILES). Recently, we have proposed a systematic framework for the design, analysis, and optimization of nonlinear discretization schemes for implicit LES. In this framework parameters inherent to the discretization scheme are determined in such a way that the numerical truncation error acts as a physically motivated SGS model. The resulting so-called adaptive local deconvolution method (ALDM) for implicit LES allows for reliable predictions of isotropic forced and decaying turbulence and of unbounded transitional flows for a wide range of Reynolds numbers. In the present paper, ALDM is evaluated for the separated flow through a channel with streamwise-periodic constrictions at two Reynolds numbers Re = 2,808 and Re = 10,595. We demonstrate that, although model parameters of ALDM have been determined for isotropic turbulence at infinite Reynolds number, it successfully predicts mean flow and turbulence statistics in the considered physically complex, anisotropic, and inhomogeneous flow regime. It is shown that the implicit model performs at least as well as an established explicit model.
机译:大涡模拟(LES)中的子网格规模(SGS)模型在一定范围的尺度上运行,而离散化方案可以解决该问题。因此,离散化方案和子网格规模模型被链接在一起。可以通过开发子网格规模模型或相反模型的离散化方法来利用此链接。将SGS模型和数值离散完全合并的方法称为隐式LES(ILES)。最近,我们为隐式LES的非线性离散化方案的设计,分析和优化提出了一个系统框架。在此框架中,离散化方案固有的参数以数字截断误差充当物理激励SGS模型的方式确定。由此产生的所谓的隐式LES自适应局部反褶积方法(ALDM)可以对大范围雷诺数的各向同性强迫湍流和衰减湍流以及无界过渡流进行可靠的预测。在本文中,对通过两个具有雷诺数Re = 2,808和Re = 10,595的具有周期性周期性收缩的通道的分离流评估ALDM。我们证明,尽管已经为无限雷诺数下的各向同性湍流确定了ALDM的模型参数,但它成功地预测了所考虑的物理复杂,各向异性和非均匀流态下的平均流量和湍流统计量。结果表明,隐式模型的性能至少与已建立的显式模型一样。

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