在Rans模拟中渐近范围的获取

L. Eça, M. Kerkvliet, S. Toxopeus
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摘要

在涉及湍流流动的工程模拟中,reynolds -average Navier-Stokes (RANS)方程仍然是最常用的数学模型。RANS方程要求使用湍流模型来计算由动量方程平均产生的雷诺应力。目前,最流行的湍流模型需要求解额外的输运方程,这些输运方程的范围从1个到7个不等。在本文中,我们说明了在网格细化研究中获得和识别所谓的渐近范围的困难,这些研究是为平板流动中的RANS方程的数值解进行的。测试了三种湍流模型:两方程、涡流粘度、k -ω SST和k- kl湍流模型以及七方程雷诺应力模型SSG/LRR -ω。用二阶和一阶迎风格式对湍流模型输运方程的对流项进行了测试。结果表明,即使在这种简单的流中,达到网格收敛的渐近阶需要不合理的网格细化水平。此外,即使在严格的几何相似网格中,观测到的网格细化顺序对湍流模型中使用的离散化方案和数据中的任何干扰都非常敏感。解决基于单项展开的误差估计质量的另一种更有效的方法是通过网格细化确定精确解估计的变化。
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Attaining the Asymptotic Range in Rans Simulations
In engineering simulations involving turbulent fluid flows, the Reynolds-averaged Navier-Stokes (RANS) equations are still the most common mathematical model. The RANS equations require the use of a turbulence model to calculate the Reynolds stresses generated by the averaging of the momentum equations. Nowadays, the most popular turbulence models require the solution of additional transport equations that can range from one to seven equations. In this paper we illustrate the difficulties in attaining and identifying the so-called asymptotic range in grid refinement studies performed for the numerical solution of the RANS equations in the flow over a flat plate. Three turbulence models are tested: two-equation, eddy-viscosity, k—ω SST and k-kL turbulence models and the seven-equation Reynolds stress model SSG/LRR—ω. The three turbulence models are tested with second and first-order upwind schemes applied to the convective terms of the turbulence models transport equations. The results show that even in this simple flow, attaining the asymptotic order of grid convergence requires unreasonable levels of grid refinement. Furthermore, even in strictly geometrical similar grids, the observed order of grid refinement can be extremely sensitive to the discretization schemes used in the turbulence model and to any disturbances in the data. An alternative and more efficient way to address the quality of an error estimation based on a single term expansion is to determine the change of the estimate of the exact solution with grid refinement.
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