Effect of tempering temperature on strain hardening exponent and flow stress curve of 1000 MPa grade steel for construction machinery
Yang Yun1,Qing-wu Cai1,2,Bao-sheng Xie2,*,Shuang Li1
1 National Engineering Research Center of Advanced Rolling, University of Science and Technology Beijing, Beijing 100083, China 2 Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
Effect of tempering temperature on strain hardening exponent and flow stress curve of 1000 MPa grade steel for construction machinery
Yang Yun1,Qing-wu Cai1,2,Bao-sheng Xie2,*,Shuang Li1
1 National Engineering Research Center of Advanced Rolling, University of Science and Technology Beijing, Beijing 100083, China 2 Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
ժҪ To study the effect of tempering temperature on strain hardening exponent and flow stress curve, one kind of 1000 MPa grade low carbon bainitic steel for construction machinery was designed, and the standard uniaxial tensile tests were conducted at room temperature. A new flow stress model, which could predict the flow behavior of the tested steels at different tempering temperatures more efficiently, was established. The relationship between mobile dislocation density and strain hardening exponent was discussed based on the dislocation-stress relation. Arrhenius equation and an inverse proportional function were adopted to describe the mobile dislocation, and two mathematical models were established to describe the relationship between tempering temperature and strain hardening exponent. Nonlinear regression analysis was applied to the Arrhenius type model, hence, the activation energy was determined to be 37.6 kJ/mol. Moreover, the square of correlation coefficient was 0.985, which indicated a high reliability between the fitted curve and experimental data. By comparison with the Arrhenius type curve, the general trend of the inverse proportional fitting curve was coincided with the experimental data points except of some fitting errors. Thus, the Arrhenius type model can be adopted to predict the strain hardening exponent at different tempering temperatures.
Abstract��To study the effect of tempering temperature on strain hardening exponent and flow stress curve, one kind of 1000 MPa grade low carbon bainitic steel for construction machinery was designed, and the standard uniaxial tensile tests were conducted at room temperature. A new flow stress model, which could predict the flow behavior of the tested steels at different tempering temperatures more efficiently, was established. The relationship between mobile dislocation density and strain hardening exponent was discussed based on the dislocation-stress relation. Arrhenius equation and an inverse proportional function were adopted to describe the mobile dislocation, and two mathematical models were established to describe the relationship between tempering temperature and strain hardening exponent. Nonlinear regression analysis was applied to the Arrhenius type model, hence, the activation energy was determined to be 37.6 kJ/mol. Moreover, the square of correlation coefficient was 0.985, which indicated a high reliability between the fitted curve and experimental data. By comparison with the Arrhenius type curve, the general trend of the inverse proportional fitting curve was coincided with the experimental data points except of some fitting errors. Thus, the Arrhenius type model can be adopted to predict the strain hardening exponent at different tempering temperatures.
Yang Yun,Qing-wu Cai,,Bao-sheng Xie,*,Shuang Li. Effect of tempering temperature on strain hardening exponent and flow stress curve of 1000 MPa grade steel for construction machinery[J]. �й������ڿ���, 2017, 24(9): 950-956.
Yang Yun,Qing-wu Cai,,Bao-sheng Xie,*,Shuang Li. Effect of tempering temperature on strain hardening exponent and flow stress curve of 1000 MPa grade steel for construction machinery. Chinese Journal of Iron and Steel, 2017, 24(9): 950-956.
2017, Vol. 24 
