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Influence of blade corrosion on aerodynamic characteristics of a gas turbine

Author

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  • Yonezawa, Koichi
  • Nakai, Genki
  • Takayasu, Masahiro
  • Sugiyama, Kazuyasu
  • Sugita, Katsuhiko
  • Umezawa, Shuichi
  • Ohmori, Shuichi

Abstract

Gas turbine blades, such as nozzle guide vanes and rotor blades, corrode over time and thus deteriorate, becoming thinner and shorter. In the present study, influences of blade corrosion on aerodynamic characteristics were examined numerically. The purposes of this study were to understand the influence of the blade deterioration on aerodynamic characteristics quantitatively under the same conditions with that in a power plant, and to clarify how to detect severe deterioration during gas turbine operation. Blade geometries before and after use were obtained from a real gas turbine using a 3-D scanner. Two parametric CFD simulations were carried out: one simulation was conducted with various turbine expansion ratios and a fixed turbine inlet temperature, and the other was conducted with various inlet temperatures and a fixed expansion ratio. According to the results of both simulations, a change in the throat area of the first-stage nozzle affected the aerodynamic characteristics significantly. The expansion ratio was found to be more useful. Numerical results obtained under actual operating conditions confirmed that the difference in the expansion ratio was about 3% between the new and old blades in the examined gas turbine.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:230:y:2021:i:c:s0360544221009142
    DOI: 10.1016/j.energy.2021.120665
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    Citations

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    Cited by:

    1. 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).
    2. Park, Yeseul & Choi, Minsung & Choi, Gyungmin, 2022. "Fault detection of industrial large-scale gas turbine for fuel distribution characteristics in start-up procedure using artificial neural network method," Energy, Elsevier, vol. 251(C).
    3. Nakhchi, M.E. & Naung, S. Win & Rahmati, M., 2022. "Influence of blade vibrations on aerodynamic performance of axial compressor in gas turbine: Direct numerical simulation," Energy, Elsevier, vol. 242(C).

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