Modeling Research On Microstructure Simulation During Hot Plastic Forming Based On Flow Curve

Geometry and mechanical properties are two major standards to judge the quality of products in metal forming. Those who consume lots of steel such as automobile and construction industry ask to reduce the structural weight with the development of science and technology in recent years. That makes the iron and steel enterprises have to create new steel. Effective control for microstructure and structure is necessary in production, especially hot rolling. Changes in microstructure and mechanical properties can be predicted using mathematical models of various metals under different conditions based on physical metallurgy. Determination of the mathematical model for metallurgical behaviors (such as dynamic recrystallization) is necessary in order to make precise analysis of microstructure evolution. The products meet requirements can be obtained in delivery time only in this way.Many researchers get the recrystallization kinetics using metallography approach, squandering time and vigour. Hot deformation process is complicated. It consists of work hardening, dynamic recovery and dynamic recrystallization, which interacts each other. It is difficult to distinguish the microstructure caused by softening or work hardening, accurate measurement of the kinetics with quantitative metallographic analysis is impossible And the kinetics are less well understood for most of the alloys formed by hot metal forming. It is necessary to find a quick and accurate method to evaluate the kinetics of recrystallization during the hot rolling.Plastic deformation of metals and the evolution of microstructure are closely related to the motion of dislocations. The volume fraction of dynamic recrystallization, which is regarded as a function of plastic strain, is coupled with the average dislocation density by a mathematical formulation in this paper. The increment in dynamic recrystallized volume fraction is used to estimate the dislocation density of the recrystallized volume. Then, the average dislocation density is calculated by using the flow curves obtained from the single-hit hot compression tests carried out on Gleeble-3500. A quick method different from conventional approach to evaluate the kinetics of dynamic recrystallization is obtained. The proposed method can replace the traditional metallographic analysis, which often includes inevitable errors. The change of dislocation density during inter-pass is related to the static recrystallization volume fraction, which can be seen as a function of time. Dislocation density decreases is related to the static recovery and static recrystallization. Based on the inverse analysis of the flow curves, a new method to estimate the kinetics for static recrystallization is proposed. The average dislocation density is calculated by using the flow curves obtained from the double-hit hot compression tests carried out on Gleeble-3500.Then the static recrystallization kinetics model is got.The methods are applied to the hot compression tests of plain carbon steel Q235A and the kinetics of dynamic and static recrystallization are gained successfully for some conditions at elevated temperature. The results are clarified by comparing them with those reported in previous investigations.Microstructure evolution (dynamic resystallization, static resystallization, meta-dynamic resystallization, etc.) could cause the change of the dislocation density during the hot plastic forming of C steel. Then that has a great influence on the shape of flow curves. A coupled mathematical model consists of development of dislocations and microstructure evolution is presented in the paper. The model for microstructure evolution does not distinguish different kinds of recrystallization, which are considered as the same process rooted in nucleation and grain growth according to KJMA theory. Flow stress is calculated by the average dislocation density, which is calculated by the dislocation density model taking into accounts hardening and recovery during the hot deformation process, and the recrystallization volume fraction. Model parameters are defined by inverse ananlysis of flow curves obtained from hot compression tests. That is finished through solving the nonlinear least-squares problem with constrains using optimization methods. Finally, in order to validate the obtained parameters, the kinetics recrystallization and average grain size obtained by the proposed model were compared with that in the literature obtained using other approach and experiment results.