Combined high and low cycle fatigue (CCF) generally induces the failure of aircraft gas turbine attachments. Based on the aero-engine load spectrum, accurate assessment of fatigue damage due to the interaction of high cycle fatigue (HCF) resulting from high frequency vibrations and low cycle fatigue (LCF) from ground-air-ground engine cycles is of critical importance for ensuring structural integrity of engine components, like turbine blades. In this paper, the influence of combined damage accumulation on the expected CCF life are investigated for turbine blades. The CCF behavior of a turbine blade is usually studied by testing with four load-controlled parameters, including high cycle stress amplitude and frequency, and low cycle stress amplitude and frequency. According to this, a new damage accumulation model is proposed based on Miner’s rule to consider the coupled damage due to HCF-LCF interaction by introducing the four load parameters. Five experimental datasets of turbine blade alloys and turbine blades were introduced for model validation and comparison between the proposed Miner, Manson-Halford, and Trufyakov-Kovalchuk models. Results show that the proposed model provides more accurate predictions than others with lower mean and standard deviation values of model prediction errors.

Establishment of damage accumulation models for reflecting the combined damage mechanism on the fatigue behavior of aero-engine turbine blades is crucial for their safety. In this work, a novel combined high and low cycle fatigue (CCF) life prediction methodology is presented as a basis of that to consider the interaction between low and high cycle fatigues. Accordingly, a dynamic reliability model is proposed to study the operational reliability of turbine blades under CCF loadings. Moreover, experimental data of materials along with the collected field data from the actual turbine blades are applied to validate the CCF life prediction model and the dynamic reliability model. The validation of the results is conducted by a comparison analysis, which indicates that the proposed life prediction method yields better accuracy, while the dynamic reliability model is proved to be more in line with the outcomes derived by the Monte Carlo simulation.

Fatigue life estimation of aero-engine turbine components under combined high and low cycle fatigue (CCF) is of significance for guaranteeing the structural reliability during operation. According to the investigations on damage evolution process, a nonlinear damage accumulation method is proposed for life prediction under CCF loadings, and the interaction effect between high cycle fatigue (HCF) and low cycle fatigue (LCF) is considered by integrating the interaction factor and stress ratio of CCF. Furthermore, experimental results of alloys and turbine blades are utilized to validate the proposed method and conduct a comparative analysis among Miner’s rule and other two typical nonlinear cumulative damage methods under combined loading conditions. Comparative results demonstrate that the developed model holds better prediction robustness and accuracy than those of others.