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Aerodynamic investigation and flow loss control on a newly designed leading edge fillet in a high-load turbine

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  • Li, Yue
  • Xue, Weipeng
  • Luo, Lei
  • Yan, Han
  • Du, Wei
  • Luo, Qiao

Abstract

To mitigate the secondary flow within the hub endwall region, this research introduces a leading-edge fillet (LEF) as a solution. The LEF reduces the strength of the passage vortex (PV) by organizing airflow around the rotor blade's leading edge. Additionally, the LEF alters the pressure gradient distribution within the passage, delaying the formation of the PV. This study investigates the effects of the length and thickness of forward and reverse-bending LEFs on the efficiency of high-load turbine stages. Before conducting the numerical investigation, the numerical method is validated. The SST (Shear Stress Transport) γ-θ turbulence model is chosen, with boundary conditions set as total pressure at the inlet and static pressure at the outlet. The numerical simulations show that the efficiency increases with the length of the LEF, with maximum efficiency being achieved at a thickness of 3.75. The reverse bending LEF performs better than the forward bending LEF. Implementation of the LEF decreases the total pressure loss coefficient and fosters a more even pressure gradient distribution along the passage, contributing to improved flow uniformity and lower flow losses. The vorticity contour map near the outlet of the rotor passage shows that PV on the hub endwall is distributed around 30 % span in the base case passage. In the passage with the LEF, the height of the PV on the hub endwall is less than 30 %. A like-leakage vortex is generated due to the LEF, reducing the intensity of the pressure-side (PS) leg of the horseshoe vortex (HV), and suppressing the suction-side leg of the HV.

Suggested Citation

  • Li, Yue & Xue, Weipeng & Luo, Lei & Yan, Han & Du, Wei & Luo, Qiao, 2025. "Aerodynamic investigation and flow loss control on a newly designed leading edge fillet in a high-load turbine," Energy, Elsevier, vol. 328(C).
    • Handle: RePEc:eee:energy:v:328:y:2025:i:c:s0360544225022595
    DOI: 10.1016/j.energy.2025.136617
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    References listed on IDEAS

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    1. Chen, Mingsheng & Chen, Jiang & Xiang, Hang & Liu, Yi & Guo, Yixuan, 2024. "Integrated optimization method for transonic turbine based on direct free-form deformation and prescreening differential evolutionary optimizer," Energy, Elsevier, vol. 291(C).
    2. Wang, Xiaojing & Zou, Zhengping, 2019. "Uncertainty analysis of impact of geometric variations on turbine blade performance," Energy, Elsevier, vol. 176(C), pages 67-80.
    3. Huang, Jingwei & He, Qingfu & Chi, Zhongran & Yue, Guoqiang & Dong, Ping, 2024. "Experimental and numerical study on the impact of inlet temperature inhomogeneity on the aerodynamic performance of a three-stage turbine," Energy, Elsevier, vol. 312(C).
    4. Chenguang Song & Guoqing Wu & Weinan Zhu & Xudong Zhang & Jicong Zhao, 2019. "Numerical Investigation on the Effects of Airfoil Leading Edge Radius on the Aerodynamic Performance of H-Rotor Darrieus Vertical Axis Wind Turbine," Energies, MDPI, vol. 12(19), pages 1-14, October.
    5. Li, Lei & Jiao, Jiangkun & Sun, Shouyi & Zhao, Zhenan & Kang, Jialei, 2019. "Aerodynamic shape optimization of a single turbine stage based on parameterized Free-Form Deformation with mapping design parameters," Energy, Elsevier, vol. 169(C), pages 444-455.
    6. Yonezawa, Koichi & Nakai, Genki & Takayasu, Masahiro & Sugiyama, Kazuyasu & Sugita, Katsuhiko & Umezawa, Shuichi & Ohmori, Shuichi, 2021. "Influence of blade corrosion on aerodynamic characteristics of a gas turbine," Energy, Elsevier, vol. 230(C).
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