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Theoretical and experimental evaluations of pre-swirl rotor-stator system with inner seal bypass configuration for turbine performance improvement

Author

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  • Lin, Aqiang
  • Liu, Gaowen
  • Li, Pengfei
  • Zhang, Zhiyuan
  • Feng, Qing

Abstract

Pre-swirl system has strong potential to improve the cooling performance and service life of high-pressure turbine rotor blades in gas turbine engines. This study is to evaluate and improve the temperature drop and power consumption characteristics of the pre-swirl system with multi-in and multi-out seal flow by theoretical and experimental analysis. Then, a high-speed rotating test rig of the pre-swirl rotor-stator system is established, considering the inner seal by-pass configuration to prevent the flow of hot gas into the pre-swirl cavity. In addition, the rotor-stator domain parameters in the pre-swirl system test rig are accurately measured at high-speed operating conditions. Three experimental schemes of pre-swirl systems are proposed for comparison under different operating conditions. The experimental results show that the temperature drop of the prototype pre-swirl system is in the range of 9.28–20.78 K, with the power consumption of the system ranging between −0.23 and −6.67 kW and the system pressure ratios being around 1.3–1.9. Because of the inner seal inflow ratio ranging within 0–15%, the system temperature drops for the improved pre-swirl system built-in inner seal by-pass passages notably reach a value between 12.12 K and 25.54 K with an average system power consumption within −0.41 to −8.21 kW. Thus, the improved pre-swirl system arrangement has dual advantages of a higher cooling effect and lower power consumption.

Suggested Citation

  • Lin, Aqiang & Liu, Gaowen & Li, Pengfei & Zhang, Zhiyuan & Feng, Qing, 2022. "Theoretical and experimental evaluations of pre-swirl rotor-stator system with inner seal bypass configuration for turbine performance improvement," Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:energy:v:258:y:2022:i:c:s0360544222016632
    DOI: 10.1016/j.energy.2022.124760
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    References listed on IDEAS

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    1. Tahan, Mohammadreza & Tsoutsanis, Elias & Muhammad, Masdi & Abdul Karim, Z.A., 2017. "Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review," Applied Energy, Elsevier, vol. 198(C), pages 122-144.
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    Cited by:

    1. Choi, Seungyeong & Bang, Minho & Park, Hee Seung & Heo, Jeonghun & Cho, Myung Hwan & Cho, Hyung Hee, 2024. "Machine learning-assisted effective thermal management of rotor-stator systems," Energy, Elsevier, vol. 299(C).
    2. Gong, Wenbin & Lei, Zhao & Nie, Shunpeng & Liu, Gaowen & Lin, Aqiang & Feng, Qing & Wang, Zhiwu, 2023. "A novel combined model for energy consumption performance prediction in the secondary air system of gas turbine engines based on flow resistance network," Energy, Elsevier, vol. 280(C).

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