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Optimization of bump and blowing to control the flow through a transonic compressor blade cascade

Mazaheri, K ; Sharif University of Technology | 2018

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  1. Type of Document: Article
  2. DOI: 10.1007/s00193-017-0729-5
  3. Publisher: Springer New York LLC , 2018
  4. Abstract:
  5. Shock control bump (SCB) and blowing are two flow control methods, used here to improve the aerodynamic performance of transonic compressors. Both methods are applied to a NASA rotor 67 blade section and are optimized to minimize the total pressure loss. A continuous adjoint algorithm is used for multi-point optimization of a SCB to improve the aerodynamic performance of the rotor blade section, for a range of operational conditions around its design point. A multi-point and two single-point optimizations are performed in the design and off-design conditions. It is shown that the single-point optimized shapes have the best performance for their respective operating conditions, but the multi-point one has an overall better performance over the whole operating range. An analysis is given regarding how similarly both single- and multi-point optimized SCBs change the wave structure between blade sections resulting in a more favorable flow pattern. Interactions of the SCB with the boundary layer and the wave structure, and its effects on the separation regions are also studied. We have also introduced the concept of blowing for control of shock wave and boundary-layer interaction. A geometrical model is introduced, and the geometrical and physical parameters of blowing are optimized at the design point. The performance improvements of blowing are compared with the SCB. The physical interactions of SCB with the boundary layer and the shock wave are analyzed. The effects of SCB on the wave structure in the flow domain outside the boundary-layer region are investigated. It is shown that the effects of the blowing mechanism are very similar to the SCB. © Springer-Verlag Berlin Heidelberg 2017
  6. Keywords:
  7. Axial compressor ; Blowing ; Flow control ; Multi-point optimization ; Shock control bump
  8. Source: Shock Waves ; Volume 28, Issue 2 , 2018 , Pages 285-297 ; 09381287 (ISSN)
  9. URL: https://link.springer.com/article/10.1007/s00193-017-0729-5