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

机译:轴向压缩机级联的LES损耗预测在非自由流障碍的非设计意义下

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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,当在扫描发生的扫描时,轴向压缩机级联将表现出损耗系数的变化,作为损耗铲斗,并且较高水平的自由流湍流可能抑制分离气泡并导致早期的过渡(参见例如[23])。然而,使用数值模拟来实现对这些变化的准确定量预测仍然难以使用数值模拟,特别是在非设计条件下,而无需使用涡流解析技术的增加的计算费用。本研究的目的是在使用壁分辨的大涡模拟(LES)和RAN的情况下在这种条件下研究轴向压缩机中的轮廓损耗。该工作通过Leggett等人来延伸到以前的工作。 [11]目的是进一步了解我们对损失预测工具的理解,并改善我们对丧失产生的物理过程的量化。结果表明,虽然RAN预测良好准确性的损失,但这些损失的崩溃归因于不同的过程,这意味着压缩机级联轮廓完全基于RAN的优化可能很难实现。

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