The globularization behavior and mechanism of TC17 alloy with basketweave microstructure were investigated, and the models of dynamic and static globularization kinetics were established. The quantitative and metallog...The globularization behavior and mechanism of TC17 alloy with basketweave microstructure were investigated, and the models of dynamic and static globularization kinetics were established. The quantitative and metallographic results show that the globularization of α phase is sensitive to the parameters of deformation and heat treatment. By EBSD analysis, the formation and evolution mechanisms of intra-α boundaries are related to discontinuous dynamic recrystallization and continuous dynamic recrystallization, which can form α grains with high and low misorientations between neighbour grains after the heat treatment, respectively. Based on the globularization behavior and mechanism, two modified JMAK models are developed to predict the dynamic and static globularization kinetics, and the mean absolute relative errors(MARE) of 10.67% and 13.80% indicate the accuracy of the dynamic and static globularization kinetics models. The results of this work can provide guidance for controlling microstructure of titanium alloy.展开更多
The bulk TC17was subjected to the high energy shot peening(HESP)at the air pressures ranging from0.35to0.55MPa and processing durations ranging from15to60min.The microhardness(HV0.02)from topmost surface to matrix of ...The bulk TC17was subjected to the high energy shot peening(HESP)at the air pressures ranging from0.35to0.55MPa and processing durations ranging from15to60min.The microhardness(HV0.02)from topmost surface to matrix of the HESP processed TC17was measured,which generally decreases with the increase of depth from topmost surface to matrix and presents different variation with air pressure and processing duration at different depths.A fuzzy neural network(FNN)model was established to predict the surface layer microhardness of the HESP processed TC17,where the maximum and average difference between the measured and the predicted microhardness were respectively8.5%and3.2%.Applying the FNN model,the effects of the air pressure and processing duration on the microhardness at different depths were analyzed,revealing the significant interaction between the refined layer shelling and the continuous grain refinement.展开更多
基金the support from the Science Fund for Distinguished Young Scholars from Shaanxi Province, China (No. 2020JC-17)the National Natural Science Foundation of China (No. 51705425)+1 种基金the Research Fund of the State Key Laboratory of Solidification Processing (NWPU), China (No. 2019-QZ-04)the Fundamental Research Funds for the Central Universities, China (No. 3102019PY007)。
文摘The globularization behavior and mechanism of TC17 alloy with basketweave microstructure were investigated, and the models of dynamic and static globularization kinetics were established. The quantitative and metallographic results show that the globularization of α phase is sensitive to the parameters of deformation and heat treatment. By EBSD analysis, the formation and evolution mechanisms of intra-α boundaries are related to discontinuous dynamic recrystallization and continuous dynamic recrystallization, which can form α grains with high and low misorientations between neighbour grains after the heat treatment, respectively. Based on the globularization behavior and mechanism, two modified JMAK models are developed to predict the dynamic and static globularization kinetics, and the mean absolute relative errors(MARE) of 10.67% and 13.80% indicate the accuracy of the dynamic and static globularization kinetics models. The results of this work can provide guidance for controlling microstructure of titanium alloy.
基金Project (51475375) supported by the National Natural Science Foundation of China
文摘The bulk TC17was subjected to the high energy shot peening(HESP)at the air pressures ranging from0.35to0.55MPa and processing durations ranging from15to60min.The microhardness(HV0.02)from topmost surface to matrix of the HESP processed TC17was measured,which generally decreases with the increase of depth from topmost surface to matrix and presents different variation with air pressure and processing duration at different depths.A fuzzy neural network(FNN)model was established to predict the surface layer microhardness of the HESP processed TC17,where the maximum and average difference between the measured and the predicted microhardness were respectively8.5%and3.2%.Applying the FNN model,the effects of the air pressure and processing duration on the microhardness at different depths were analyzed,revealing the significant interaction between the refined layer shelling and the continuous grain refinement.
