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Statistical evaluation of performance impact of flow variations for a transonic compressor rotor blade

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  • Xia, Zhiheng
  • Luo, Jiaqi
  • Liu, Feng

Abstract

The effects of flow variations to the aerodynamic performance of turbomachinery blades are considerable in the real world. Uncertainty quantification of aerodynamic performance is useful for evaluating the mean performance change, robust design, etc. The paper studies the performance impact of inlet and outlet flow variations for transonic compressor rotor blades using polynomial chaos. An adaptive sparse grid technique is employed to construct the model of adaptive non-intrusive polynomial chaos (ANIPC). Through statistical evaluation of performance changes for NASA Rotor 67, the response performance of ANIPC is firstly verified. Then the ANIPC is used to evaluate the changes of adiabatic efficiency and mass flow rate of Rotor 67 considering the variations of inlet total pressure and outlet back pressure at different operation conditions. The results reveal that the performance changes exhibit evident nonlinear dependence on the inlet and outlet pressure variations. Moreover, performance changes of the rotor blade in the whole operation range are evaluated and illustrated. Finally, by Monte Carlo simulation, the flow solutions along span and in the blade passage are statistically analyzed to demonstrate the impact mechanisms of inlet and outlet pressure variations to the performance changes.

Suggested Citation

  • Xia, Zhiheng & Luo, Jiaqi & Liu, Feng, 2019. "Statistical evaluation of performance impact of flow variations for a transonic compressor rotor blade," Energy, Elsevier, vol. 189(C).
    • Handle: RePEc:eee:energy:v:189:y:2019:i:c:s0360544219319802
    DOI: 10.1016/j.energy.2019.116285
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    References listed on IDEAS

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    1. Daróczy, László & Janiga, Gábor & Thévenin, Dominique, 2016. "Analysis of the performance of a H-Darrieus rotor under uncertainty using Polynomial Chaos Expansion," Energy, Elsevier, vol. 113(C), pages 399-412.
    2. Liu, ZhiYi & Wang, XiaoDong & Kang, Shun, 2014. "Stochastic performance evaluation of horizontal axis wind turbine blades using non-deterministic CFD simulations," Energy, Elsevier, vol. 73(C), pages 126-136.
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    Cited by:

    1. Cheng, Hongzhi & Zhou, Chuangxin & Lu, Xingen & Zhao, Shengfeng & Han, Ge & Yang, Chengwu, 2023. "Robust aerodynamic optimization and design exploration of a wide-chord transonic fan under geometric and operational uncertainties," Energy, Elsevier, vol. 278(PB).
    2. Wang, Kun & Chen, Fu & Yu, Jianyang & Song, Yanping & Ghorbaniasl, Ghader, 2023. "Effect of uncertain operating conditions on the aerodynamic performance of high-pressure axial turbomachinery blades," Energy, Elsevier, vol. 283(C).
    3. Li, Jinxing & Liu, Tianyuan & Zhu, Guangya & Li, Yunzhu & Xie, Yonghui, 2023. "Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods," Energy, Elsevier, vol. 273(C).

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