Surface structures with excellent aerodynamic performance can reduce the flow loss of aero-engine caused by the harsh working environment to a certain extent. Inspired by the dentate micro-texture over shark skin, micro-texture surface has been proposed as an emerging and effective means to reduce the flow loss of aero-engine. However, for a realistic compressor cascade configuration with micro-texture, using massive grids to describe the flow within the boundary layer makes the simulation of multi-scale flow field unfeasible. This paper presents an innovative numerical simulation method for compressor cascade with micro-textured surface using a machine learning wall modification model. The wall modification model is trained based on the near-wall microflow data obtained by LBM, which can reproduce the flow effects of micro-textured surface. The mechanism of reducing the total pressure loss of the compressor cascade is that the micro-textured surface structure delays the laminar transition and decreases the intensity of the turbulent region. In addition, wake measurements through experiment are performed to validate the proposed multi-scale numerical simulation method in the high-speed linear cascade wind tunnel. This paper demonstrates the flow loss reduction effect of micro-textured surface on compressor cascade through numerical and experimental study.
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Wang et al. (2024) studied this question.
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