Probabilistic LCF life prediction framework for turbine discs considering random load history

• Published in: Quality and reliability engineering international Vol. 40; no. 6; pp. 3161 - 3172
• Main Authors: Bai, Song, Zeng, Ying, Huang, Tudi, Li, Yan‐Feng, Huang, Hong‐Zhong
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 01.10.2024
• Subjects: Computational efficiency; Fatigue life; fatigue life prediction; Life prediction; Load history; Low cycle fatigue; Probability theory; Random loads; Randomness; turbine disc; Turbine disks; uncertainty
• ISSN: 0748-8017; 1099-1638
• DOI: 10.1002/qre.3582

The load history exerts a considerable impact on the low cycle fatigue (LCF) life of turbine discs. Thus, oversimplifying the load history leads to substantial errors in fatigue life prediction. This study introduces a probabilistic fatigue life prediction method for turbine discs, accounting for the randomness inherent in LCF load history. The method involves quantifying the randomness of load history through numerical simulation and employing a surrogate model enhanced with learning functions to balance computational efficiency and accuracy. The probabilistic LCF life prediction of full‐scale turbine disc was conducted, demonstrating that the fatigue life scatter predicted by the proposed method more closely aligns with experimental data compared to the original approach. By refining the numerical simulation process, the proposed method better accounts for uncertainties in load history while maintaining computational efficiency, offering significant insights for the fatigue reliability design of turbine discs.