Volume 41 Issue 8
Aug.  2026
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Shi Lizhong, Zhang Qian. Load/environment spectrum driven hybrid life prediction approach for in-service HPT blades[J]. Journal of Aerospace Power, 2026, 41(8):20250318 doi: 10.13224/j.cnki.jasp.20250318
Citation: Shi Lizhong, Zhang Qian. Load/environment spectrum driven hybrid life prediction approach for in-service HPT blades[J]. Journal of Aerospace Power, 2026, 41(8):20250318 doi: 10.13224/j.cnki.jasp.20250318

Load/environment spectrum driven hybrid life prediction approach for in-service HPT blades

doi: 10.13224/j.cnki.jasp.20250318
  • Received Date: 2025-07-07
    Available Online: 2026-01-18
  • To address the difficulty in predicting the fatigue life of aero-engine high-pressure turbine blades during service, a stress- and temperature-correlated service load/environment spectrum was developed. The blade low-cycle fatigue life was assessed based on durability and damage tolerance theories. The stress-temperature time histories at critical fatigue locations were computed using a fluid-thermal-structural coupled simulation model combined with a random forest surrogate model. The load/environment spectrum was compiled via the multiaxial rain-flow counting method. The crack initiation life was evaluated using a semi-empirical approach based on the detail fatigue rating method. The crack propagation life was calculated by constructing a physical model on the Franc3D platform grounded in damage tolerance theory. The results demonstrated that the critical fatigue location of the blade was at the film-cooling hole near the leading-edge root. At this location, the prediction errors for stress and temperature were 0.4% and 0.71%, respectively, and their time histories exhibited a strong correlation, with a Pearson coefficient of 0.902. The established semi-empirical-physical hybrid model predicted the blade life with an error of about 8% compared with the average statistical life of actual blades. This approach could provide a valuable reference for predicting the life of aero-engine turbine blades and determining maintenance intervals.

     

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