LNS - An approach towards embedded LES
LNS - An approach towards embedded LES
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DOI：
10.2514/6.2002-427
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发表时间：
2002-01
期刊：
影响因子：
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通讯作者：
P. Batten;U. Goldberg;S. Chakravarthy
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文献类型：
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作者：
P. Batten;U. Goldberg;S. Chakravarthy
本文考虑了混合湍流模型的现状和未来可能的发展趋势，该模型将统计平均纳维尔-斯托克斯（RANS）封闭与大涡模拟（LES）方法相结合。从现有的混合公式中收集的经验开始证实它们在高雷诺数分离流的非定常模拟中桥接近壁区的能力。然而，不同的空间分辨率的区域之间的动能转移的问题仍然限制了当前一代的混合方法的适用范围。更大的通用性的潜力存在，从而局部网格细化将自动导致一个详细的处理选定的流动区域的成本低于传统的LES，或LES与近壁RANS。构建一个通用的混合方法，RANS和LES（反之亦然）之间的无缝接口需要额外的考虑有关的空间/时间分辨率和建模湍流动能到可分辨的结构转移。本文报告了这方面的一些进展。名称湍流动能，m/s长度尺度，m湍流产生，m/s雷诺数应变张量，Sy应变量级=（2SijSij）速度尺度，m/s LNS延迟参数湍流耗散率，m/s动力粘度系数，kg/（m.s）运动粘度系数，（m/s）湍流涡动粘度，kg/（m.s）涡度张量，Qj。由于直接数值模拟（DNS）和传统的大涡模拟（LES）的持续高成本，湍流的工程预测继续由简单的（单点，各向同性）雷诺平均纳维尔-斯托克斯（RANS）模型主导。尽管在非定常RANS的实践中存在公认的不确定性，但这些模型经常被赋予预测k L Pk Re S S V
This paper considers the present and possible future state of hybrid turbulence models, which blend statistical Reynolds-Averaged Navier-Stokes (RANS) closures with Large-Eddy Simulation (LES) methods. Experience gathered from existing hybrid formulations is beginning to confirm their ability to bridge the near-wall region in unsteady simulations of high-Reynolds number, separated flow. However, the issue of kinetic energy transfer between regions of differing spatial resolution still limits the range of applicability of the current generation of hybrid methods. A potential for greater generality exists, whereby local grid refinement would automatically lead to a detailed treatment of selected flow regions at a cost lower than that of either conventional LES, or LES with near-wall RANS. Constructing a general hybrid method that interfaces seamlessly between RANS and LES (and vice versa) requires additional considerations relating to spatial/temporal resolution and the transfer of modeled turbulence kinetic energy into resolvable structures. This paper reports some progress in this area. NOMENCLATURE Turbulence kinetic energy, m/s Length scale, m Turbulence production, m/s Reynolds number Strain tensor, Sy Strain magnitude = (2SijSij)Velocity scale, m/s LNS latency parameter Turbulence dissipation rate, m/s Dynamic viscosity coeff., kg/(m.s) Kinematic viscosity coeff., (m/s) Turbulence eddy viscosity , kg/(m.s) Vorticity tensor, Qj . Vorticity magnitude = (2£1^ Qq)' Density, (kg/m) Favre-average of fy Time-average of <j) INTRODUCTION Due to the continued high cost of direct numerical simulation (DNS) and traditional large eddy simulation (LES), engineering predictions of turbulent flow continue to be dominated by simple (single-point, isotropic) ReynoldsAveraged Navier-Stokes (RANS) models. Despite acknowledged uncertainties over the practice of unsteady RANS, these models are frequently entrusted with the task of predicting k L Pk Re S S V