The influences of strain amplitude ranges and dwell time at peak strains on the low cycle fatigue (LCF) properties at 600℃ of a new near α high temperature titanium alloy containing rare earth Nd are investigated. ...The influences of strain amplitude ranges and dwell time at peak strains on the low cycle fatigue (LCF) properties at 600℃ of a new near α high temperature titanium alloy containing rare earth Nd are investigated. The creep fatigue interaction behavior is discussed in this paper in terms of a creep fatigue interaction cumulative law and fatigue crack propagation model. The results show that the creep fatigue interaction is largely dependent on the strain amplitude range, and the tensile dwell periods, as well as compressive dwell periods, have a great influence on the LCF life of this alloy.展开更多
To overcome the challenges of limited experimental data and improve the accuracy of empirical formulas,we propose a low-cycle fatigue(LCF)life prediction model for nickel-based superalloys using a data augmentation me...To overcome the challenges of limited experimental data and improve the accuracy of empirical formulas,we propose a low-cycle fatigue(LCF)life prediction model for nickel-based superalloys using a data augmentation method.This method utilizes a variational autoencoder(VAE)to generate low-cycle fatigue data and form an augmented dataset.The Pearson correlation coefficient(PCC)is employed to verify the similarity of feature distributions between the original and augmented datasets.Six machine learning models,namely random forest(RF),artificial neural network(ANN),support vector machine(SVM),gradient-boosted decision tree(GBDT),eXtreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost),are utilized to predict the LCF life of nickel-based superalloys.Results indicate that the proposed data augmentation method based on VAE can effectively expand the dataset,and the mean absolute error(MAE),root mean square error(RMSE),and R-squared(R^(2))values achieved using the CatBoost model,with respective values of 0.0242,0.0391,and 0.9538,are superior to those of the other models.The proposed method reduces the cost and time associated with LCF experiments and accurately establishes the relationship between fatigue characteristics and LCF life of nickel-based superalloys.展开更多
Low cycle fatigue tests were conducted on the single crystal nickel-based superalloy, DD6, with different crystallographic orientations （i.e., [001], [011], and [111]） and strain dwell types （i.e, tensile, compress...Low cycle fatigue tests were conducted on the single crystal nickel-based superalloy, DD6, with different crystallographic orientations （i.e., [001], [011], and [111]） and strain dwell types （i.e, tensile, compressive, and balanced types） at a certain high temperature. Given the material anisotropy and mean stress, both orientation factor and stress range were introduced to the Smith, Watson, and Topper （SWT） stress model to predict the fatigue life. Experimental results indicated that the fatigue properties of DD6 depend on both crystallographic orientation and loading types. The fatigue life of the tensile, compressive, and balanced strain dwell tests are shorter than those of continuous cycling tests without strain dwell because of the important creep effect. The predicted results of the proposed modified SWT stress method agree well with the experimental data.展开更多
文摘The influences of strain amplitude ranges and dwell time at peak strains on the low cycle fatigue (LCF) properties at 600℃ of a new near α high temperature titanium alloy containing rare earth Nd are investigated. The creep fatigue interaction behavior is discussed in this paper in terms of a creep fatigue interaction cumulative law and fatigue crack propagation model. The results show that the creep fatigue interaction is largely dependent on the strain amplitude range, and the tensile dwell periods, as well as compressive dwell periods, have a great influence on the LCF life of this alloy.
基金Financial support from the Fundamental Research Funds for the Central Universities(ZJ2022-003,JG2022-27,J2020-060,and J2021-060)Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance(GAMRC2021YB08)the Young Scientists Fund of the National Natural Science Foundation of China(No.52105417)is acknowledged.
文摘To overcome the challenges of limited experimental data and improve the accuracy of empirical formulas,we propose a low-cycle fatigue(LCF)life prediction model for nickel-based superalloys using a data augmentation method.This method utilizes a variational autoencoder(VAE)to generate low-cycle fatigue data and form an augmented dataset.The Pearson correlation coefficient(PCC)is employed to verify the similarity of feature distributions between the original and augmented datasets.Six machine learning models,namely random forest(RF),artificial neural network(ANN),support vector machine(SVM),gradient-boosted decision tree(GBDT),eXtreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost),are utilized to predict the LCF life of nickel-based superalloys.Results indicate that the proposed data augmentation method based on VAE can effectively expand the dataset,and the mean absolute error(MAE),root mean square error(RMSE),and R-squared(R^(2))values achieved using the CatBoost model,with respective values of 0.0242,0.0391,and 0.9538,are superior to those of the other models.The proposed method reduces the cost and time associated with LCF experiments and accurately establishes the relationship between fatigue characteristics and LCF life of nickel-based superalloys.
基金The financial support for this work from the National Natural Science Foundation of China （Grant No. 51341001） is appreciated.
文摘Low cycle fatigue tests were conducted on the single crystal nickel-based superalloy, DD6, with different crystallographic orientations （i.e., [001], [011], and [111]） and strain dwell types （i.e, tensile, compressive, and balanced types） at a certain high temperature. Given the material anisotropy and mean stress, both orientation factor and stress range were introduced to the Smith, Watson, and Topper （SWT） stress model to predict the fatigue life. Experimental results indicated that the fatigue properties of DD6 depend on both crystallographic orientation and loading types. The fatigue life of the tensile, compressive, and balanced strain dwell tests are shorter than those of continuous cycling tests without strain dwell because of the important creep effect. The predicted results of the proposed modified SWT stress method agree well with the experimental data.
