The dynamic recrystallization behavior of 25CrMo4 steel was systematically investigated by compression deformation at different temperatures and strain rates on a Gleeble 1500 thermal mechanical simulation tester. The...The dynamic recrystallization behavior of 25CrMo4 steel was systematically investigated by compression deformation at different temperatures and strain rates on a Gleeble 1500 thermal mechanical simulation tester. The flow curves under different deformation conditions were obtained, and the effects of deformation temperature and strain rate on the appearance of the flow curves were discussed. Based on the experimental flow curves, the activation energy determined by regression analysis was Q = 337 kJ/mol, and the constitutive model was constructed. All the characteristic points of the flow curves were identified from the work hardening rate curves （θ= dσ/dε vs σ）, which were derived from the flow curves. Then, the kinetics model of dynamic recrystallization was determined by combining the Avrami equation with the stress loss resulted from the dynamic recrystallization. With the aid of the kinetics model, the effect of strain on the efficiency of power dissipation was discussed. Furthermore, the optimum parameters for the forging process were determined based on the processing maps.展开更多
基金financially supported by the National Basic Research Program of China(No.2011CB012903)
文摘The dynamic recrystallization behavior of 25CrMo4 steel was systematically investigated by compression deformation at different temperatures and strain rates on a Gleeble 1500 thermal mechanical simulation tester. The flow curves under different deformation conditions were obtained, and the effects of deformation temperature and strain rate on the appearance of the flow curves were discussed. Based on the experimental flow curves, the activation energy determined by regression analysis was Q = 337 kJ/mol, and the constitutive model was constructed. All the characteristic points of the flow curves were identified from the work hardening rate curves （θ= dσ/dε vs σ）, which were derived from the flow curves. Then, the kinetics model of dynamic recrystallization was determined by combining the Avrami equation with the stress loss resulted from the dynamic recrystallization. With the aid of the kinetics model, the effect of strain on the efficiency of power dissipation was discussed. Furthermore, the optimum parameters for the forging process were determined based on the processing maps.
