Fatigue Damage Prediction Model Improved with Manson-Halford Model
To predict the auto parts'fatigue damage under multi-stage stress loading,the study proposed an improved fatigue damage prediction model based on Manson-Halford model.First,the structural forms and constituent elements of Gao model nonlinear interaction coefficients were analyzed based on the relation equation of material S-N characteristic curve.As the compositions of acting coefficients in the nonlinear fatigue damage model,three parameters were introduced,i.e.,ratio of adjacent stress amplitudes,slope of material S-N logarithmic characteristic line,and accumulated fatigue damage from previous stress stage.Based on the original advantages of Manson-Halford model,the improved version was proposed.Second,to verify the new model's predictive performance,the fatigue test data from 2 to 5 stress stages of four materials were utilized.The study compared the predictive results of 7 models(i.e.,Miner model,Manson-Halford model,Gao model,YG model,Yue model,Haghgouei model,and the proposed new model)with the maximum absolute error and maximum relative error of fatigue damage.The test data covered both high-cycle fatigue and the combination of high-cycle fatigue and low-cycle fatigue.Finally,the differences between predicted and experimental fatigue damage results from 2 to 5 stress stages were statistically analyzed.The superiority and inferiority of each model were evaluated by using the minimum,maximum,and standard deviation values.The result indicates that the proposed new model aligns closely with the experimental outcomes,especially when predicting mixed stress conditions involving both high-cycle fatigue stress and low-cycle fatigue stress.The predictive performance of the new model is superior to that of other models,demonstrating higher accuracy and robustness in predicting fatigue damage.
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