Prediction of very-high-cycle fatigue life of TC17 alloy based on machine learning
Based on the challenges of the fatigue life of TC17,a titanium alloy compressor blade material for aero-engines,which is difficult to predict due to the large dispersion of fatigue life and the limitations of high test cost and long test period.Machine learning(ML)has powerful data processing ability,this paper uses Monte Carlo simulation(MCS)to extend and enhance the fatigue life of TC17 at very-high-cycle fatigue life,and uses machine learning to verify the accuracy of fatigue life prediction.The prediction results for the stress ratioR=0.1 show that the prediction accuracy of the ML model after data enhancement has improved by 63.05%,and also those predictions are all within the scatter band of 5.0.
NETL
NSTL
万方数据
