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IMPROVED PREDICTION OF LABYRINTH SEAL PERFORMANCE THROUGH SCALE ADAPTIVE SIMULATION AND STREAM ALIGNED GRIDS

机译:通过尺度自适应模拟和流对齐网格改进了迷宫式密封性能的预测

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The accurate prediction of cavity flows is of importance to the turbomachinery design process. However, cavity flows are complex. It is known, that RANS models tend to struggle with the prediction of cavity flows and the flow phenomena associated with them. At the same time, scale-resolving methods are more accurate and give a more detailed view on the turbulent structure of the flow. This is accompanied by an inherent dependency on the computational grid, the timestep, and the size of the domain. Therefore, an experimentally validated comparison of RANS, URANS and SAS simulations for a stepped labyrinth seal is given in the paper at hand to demonstrate the individual methods capabilities, limitations, and requirements. It was shown that an alignment of the grid with the local flow direction can save about 40% of computational resources, while simultaneously reducing the discretization error by 25%. RANS and time averaged URANS results in comparison to measurements showed that the swirl development in the cavity is overpredicted and the cavity vortex is underpredicted. A distinct grid dependency was noticed for the SAS-SST turbulence model. The intermediate grid enhances the results in comparison to RANS and URANS. URANS-SST and SAS-SST simulations capture the same dominant frequencies of the velocity spectra, when the same sector size is used. Furthermore, the prediction of dominant frequencies depends strongly on the circumferential size of the domain. The time-averaged results are more sensitive to the grid refinement and turbulence model than to the size of the domain.
机译:腔流的精确预测对涡轮机械设计过程具有重要性。然而,腔流量是复杂的。众所周知,RAN模型倾向于与腔流量的预测和与它们相关联的流动现象的预测斗争。同时,缩放分辨方法更准确,并在流动的湍流结构上提供更详细的视图。这伴随着对计算网格,时间步骤和域的大小的固有依赖。因此,RAN的一个实验验证比较,URANS和SAS模拟为一个阶梯形迷宫式密封件在纸手头说明了该方法的个体的能力,限制和要求。结果表明,网格与局部流动方向的对齐可以节省约40%的计算资源,同时将离散化误差减少25%。 Rans and Time平均urans与测量相比,结果表明,腔体中的漩涡开发均为覆盖,并且腔涡体不足。对于SAS-SST湍流模型,注意到了不同的网格依赖性。中间网格与Rans和urans相比增强了结果。 urans-SST和SAS-SST仿真捕获相同的速度光谱的主导频率,当使用相同的扇区大小时。此外,主导频率的预测在域的圆周尺寸上强烈地取决于域的圆周尺寸。时间平均结果对网格细化和湍流模型比到域的大小更敏感。

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