Experimental investigation of adaptive Coanda jet control for performance improvement of a highly loaded compressor cascade
With the increase in the blade load of modern compressors for aircraft engines and gas turbines, flow separation generated in stator blade passages especially under transient flight maneuvers or off-design operating conditions is enhanced. This not only deteriorates the compressor efficiency but also blockages the flow path that may induce instability such as stall or surge. Due to this, an adaptive Coanda jet control (ACJC) system has been developed based on a compressor stator cascade. This system can execute real-time monitoring the flow condition of the stator via an incidence angle prediction model and can inject appropriate air to eliminate flow separation based on an optimal injection mass flow rate prediction model. In order to further validate the active control effects of the ACJC system, this article conducts detailed experimental tests for the stator cascades. Inflow condition matrix is elaborately arranged by considering a wide range of inlet Mach number [0.4, 0.6] and incidence angle [−3°, 5°]. Results indicate that the incidence angle predicted by the ACJC system is nearly the same as the set value. Also, the total pressure loss is dramatically decreased due to the Coanda jet with a mass flow rate predicted by the ACJC system. In addition, compared to the cascade without ACJC under the incidence angel of 5°, the total pressure loss coefficient is reduced by 14.3%, 12.9%, and 17.8% at inflow Mach number being 0.4, 0.5, and 0.6, respectively.
Authors
- Chaoqun Nie
- Juan Du (ORCID: https://orcid.org/0000-0001-8927-2667)
- Min Zhang (ORCID: https://orcid.org/0009-0003-8645-9954)
- Jian Zhang (ORCID: https://orcid.org/0000-0001-9822-3023)
Institutions
- Chinese Academy of Sciences (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Physics of Fluids
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1063/5.0212873
- Citations
- 3
- Primary Topic
- Turbomachinery Performance and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 9.99