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LES LOSS PREDICTION IN AN AXIAL COMPRESSOR CASCADE AT OFF-DESIGN INCIDENCES WITH FREE STREAM DISTURBANCES

机译:轴流压缩机级联在无设计干扰的情况下的失误预测

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It is well known that an axial compressor cascade will exhibit variation in loss coefficient, described as a loss bucket, when run over a sweep of incidences, and that higher levels of free stream turbulence are likely to suppress separation bubbles and cause earlier transition (see e.g. [23]). However, it remains difficult to achieve accurate quantitative prediction of these changes using numerical simulation, particularly at off-design conditions, without the added computational expense of using eddy-resolving techniques. The aim of the present study is to investigate profile losses in an axial compressor under such conditions using wall-resolved Large Eddy Simulation (LES) and RANS. The work extends on previous work by Leggett et al.[11] with the intention of furthering our understanding of loss prediction tools and improving our quantification of the physical processes involved in loss generation. The results show that while RANS predicts losses with good accuracy the breakdown of these losses are attributed to different processes, meaning that optimisation of a compressor cascade profile, based solely on RANS, may be hard to achieve.
机译:众所周知,轴向压缩机叶栅在掠过入射波时会表现出损失系数的变化,称为损失铲斗,而较高水平的自由流湍流很可能会抑制分离气泡并引起更早的过渡(请参见例如[23])。但是,使用数值模拟,特别是在设计外的条件下,要获得准确的定量预测这些变化仍然很困难,而又不增加使用涡旋分辨技术的计算费用。本研究的目的是使用壁分辨大涡模拟(LES)和RANS研究在这种条件下的轴流压缩机的轮廓损失。该工作是对Leggett等人[11]先前工作的扩展。旨在加深我们对损失预测工具的理解,并改善对损失产生所涉及的物理过程的量化。结果表明,尽管RANS可以很好地预测损失,但这些损失的归因归因于不同的过程,这意味着仅凭RANS可能难以实现压缩机叶栅轮廓的优化。

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