Gas kinetic scheme for turbulence simulation
Gas kinetic scheme for turbulence simulation
复制标题
湍流模拟的气体动力学方案
DOI：
10.1016/j.ast.2018.04.022
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发表时间：
2018-07-01
影响因子：
5.6
通讯作者：
Fu, Song
中科院分区：
文献类型：
--
作者：
Tan, Shuang;Li, Qibing;Fu, Song
基于带有效松弛时间的广义BGK方程，发展了湍流模拟的扩展气体动力学格式（GKS）。该弛豫时间可以从湍流粘度计算，通过该湍流粘度可以直接组合湍流模型。对于工程上低成本的高雷诺数流动模拟，采用了常用的RANS模型，而在高保真湍流模拟中采用了LES和混合RANS/LES（DES和IDDES）模型以及最小色散和可控耗散（MDCD）重建。此外，湍流输运方程的强耦合的方式，通过使用GKS标量输运。将扩展的GKS应用于典型湍流流动的数值模拟，包括高超声速压缩斜坡流的RANS模拟和低速圆柱流多尺度湍流结构的混合模型详细模拟。预测结果与已有的实验测量和数值研究结果吻合良好，表明了扩展GKS方法具有良好的精度、分辨率和鲁棒性，在不同模型尺度的湍流模拟中具有广阔的应用前景，包括RANS/LES混合方法等多尺度模型.此外，基于广义BGK模型的多尺度湍流模拟方法值得进一步研究。(C)2018年Elsevier Masson SAS。All rights reserved.
The extended gas-kinetic scheme (GKS) for turbulence simulations is developed based on the generalized BGK equation with the effective relaxation time. This relaxation time can be computed from the turbulent viscosity, through which turbulence models can be directly combined. For engineering low-cost simulations of high Reynolds number flows, common-used RANS models are applied, while the LES and hybrid RANS/LES (DES and IDDES) models as well as the minimized dispersion and controllable dissipation (MDCD) reconstruction are adopted in high fidelity turbulence simulations. In addition, the turbulent transport equations are solved in a strongly coupled way by using GKS with scalar transport. The extended GKS is applied in typical turbulent flow predictions including the RANS simulation of hypersonic compression ramp flow and the detailed simulation of multiscale turbulent structures in low speed cylinder flow with hybrid models. The predicted results agree well with existing experimental measurements and numerical studies, which shows the good accuracy, resolution and robustness of the extended GKS and reveals the wide prospects in turbulence simulations on different model scales, including the multiscale models such as hybrid RANS/LES methods. Furthermore, the multiscale turbulence simulation methods are worthy of further studies based on the generalized BGK model. (C) 2018 Elsevier Masson SAS. All rights reserved.