Structure of a turbulent flow through plane channels with smooth and rough walls: An analysis based on high resolution DNS results
Structure of a turbulent flow through plane channels with smooth and rough walls: An analysis based on high resolution DNS results
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通过具有光滑和粗糙壁的平面通道的湍流结构：基于高分辨率 DNS 结果的分析
DOI：
10.1016/j.compfluid.2014.10.012
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发表时间：
2014
影响因子：
2.8
通讯作者：
H. Herwig
中科院分区：
文献类型：
--
作者：
Y. Jin;M.F. Uth;H. Herwig
两种不同的DNS方法（湍流的直接数值模拟，即没有湍流建模）用于确定通过具有光滑和粗糙壁的通道的湍流的详细结构。它们是一个有限体积法（FVM）与网格细化的墙壁和格子玻尔兹曼方法（LBM）与均匀网格。使用LBM方法，可以实现高达3亿个网格点的高分辨率。与具有较少网格点和朝向壁的网格细化的FVM方法相比，远离壁的高得多的分辨率出现在LBM解决方案中。由于这些高分辨率发夹涡可以清楚地识别这些流量。它们被认为是边界层的重要组成部分。然而，在槽道流动中，它们的密集存在仅通过实验研究检测到，而数值计算仍然没有清楚地可视化，特别是在粗糙壁槽道流动中。我们的LBM结果表明，发夹涡和他们的组织在大尺度和超大尺度运动（LSM，VLSM）在光滑壁和粗糙壁槽道流动盛行。光滑壁面和目前k型粗糙壁面上的涡结构的相似性支持了汤森的壁面相似性假说。
Two different DNS-approaches (direct numerical simulation of turbulent flow, i.e. without turbulence modeling) are used to determine the detailed structure of turbulent flow through channels with smooth and rough walls. They are a finite volume method (FVM) with grid refinement toward the walls and a Lattice Boltzmann method (LBM) with a uniform grid. With the LBM-approach high resolutions with up to 300 million grid points are possible. Compared to the FVM-approach with less grid points and grid refinement toward the wall much higher resolutions away from the walls occur in the LBM solutions. Due to these high resolutions hairpin vortices can be clearly identified for these flows. They are known to be important building blocks in boundary layers. In channel flows, however, their dense existence has only been detected by experimental studies, whereas numerically it still has not been clearly visualized, especially in rough wall channel flows. Our LBM results show that hairpin vortices and their organizations in large scale and very large scale motions (LSM, VLSM) prevail in both smooth wall and rough wall channel flows. The similarity of the vortical structures in the outer layers over smooth walls and over the present k-type rough walls supports Townsend’s wall similarity hypothesis.