Microstructure Evolution Simulation During Metal Ring Blank-casting And Rolling Compound Forming Processes Using Cellular Automata Method

A short flow process of metal ring blank-casting and rolling compound precision forming is a breakthrough improvement process based on the traditional ring part production method. It has many significant advantages with respect to short process, energy saving, material saving, high efficiency, low cost, environmental protection, and so on. However, this process is a highly integrated problem which has three-dimensional continuous gradient, asymmetric, unsteady, macro to micro coupling and thermal mechanical coupling characteristics. Thus the traditional empirical model or phenomenological mathematical model is not enough to describe the microstructure evolution of the process. Under the support by the Key Program of National Natural Science Foundation of China(NO.51135007), this thesis makes as-cast 42 CrMo steel as the research object, the initial grain organization, dynamic recrystallization process, the meta-dynamic recrystallization and static recrystallization process cellular automata model are built. Combined the independent component analysis method, a grain topology deformation technology considering structural independence is put forward. The method which combines finite element analysis with the cellular automata method is explored. The whole ring and its different locations are modeled respectively from macroscale to microscale. The main research content of the thesis is as follows:(1) For the as-cast 42 CrMo steel after tempering treatment, single pass hot deformation experiments and two-pass hot deformation experiments are operated by Gleebe-1500 D hot simulation experiment machine, and as-cast 42 CrMo steel flow stress model is set up respectively to study as-cast 42 CrMo steel hot deformation behavior on the basis of work hardening-dynamic recovery, dynamic recrystallization. Cooperate with metallographic experiment at the same time, as-cast 42 CrMo steel microstructure morphologies under different deformation are observed by the VEX-600 E metallographic microscope. Thereby material parameters of the microstructure evolution cellular automata model and macroscopic finite element model are determined.(2) On the basis of the thermodynamic mechanism and energy dissipation mechanism, and introducing independent component analysis at the same time, the cellular transformation rules which meet austenitic grain growth mechanism are formulated, thus the initial grain topology which meets the dynamic recrystallization grain growth kinetics and the topological properties is obtained. The austenitic grain growth process is simulated by this model. The obtained grain topologies meet the topological morphology characteristics of grain growth, which lay the foundation for further establishing as-cast 42 CrMo steel dynamic recrystallization cellular automata model.(3) On the basis of studying recrystallization nucleation, dislocation density and grain growth theory model, taking the grain topology of overlapping problems into account, the optimized grain topology deformation technology is put forward and the dynamic recrystallization cellular transformation rules are developed. Then cellular automata model of as-cast 42 CrMo steel dynamic recrystallization is built to simulate dynamic recrystallization process. As-cast 42 CrMo steel dynamic recrystallization performances are simulated by the model at different strain, strain rate and deformation temperature. In addition, the predicted ability of the model to characteristics of material flow stress and microstructure morphology is validated(4) According to the meta-dynamic recrystallization behavior characteristics in thermal deformation process, the theory models of dynamic recrystallization and static recovery are studied. Combining grain topology deformation technology with a view to solving grain topological overlap problem, the cellular automata model of as-cast 42 CrMo steel meta-dynamic recrystallization is modeled. Through the model, the meta-dynamic recrystallization behaviors of as-cast 42 CrMo steel at different strain rate and deformation temperature are simulated and validated.(5) Static recrystallization cellular automata model has the same cellular transformation rules with the dynamic recrystallization cellular automata model. Taking static recrystallization behavior in the thermal deformation process as foundation, researching the theory models of static recrystallization, static response and grain coarsening, combining grain topology deformation technology in view of grain topological overlap problem, the cellular automata model of as-cast 42 CrMo steel static recrystallization is built. Through the model to simulate the static recrystallization behavior of as-cast 42 CrMo steel at different strain rate and deformation temperature, the description accuracy of the material microstructure evolution characteristics by static recrystallization cellular automata model is verified.(6) Macro to micro scale-span modeling method of metal ring casting and rolling compound forming process is explored. Combining the finite element analysis method with the cellular automata method from the two different dimensional administrative levels, the whole ring and its different locations are modeled respectively from macroscale to microscale. Not only the radial-axial ring rolling forming process can be macro described, but also the topology and distribution evolution of grain structure can be micro revealed and forecasted. Macro to micro scale-span boundary condition is defined. Secondary developing ABAQUS finite element software platform, the process parameters and material parameters of ring blank tracing points in the process of hot rolling are imported automatically to the microstructure evolution cellular automata model in MATLAB software platform. The as-cast 42 CrMo steel microstructure evolutions under different deformation are simulated by using this model. Furthermore, the accuracy of prediction ability in the material microstructure evolution characteristics of static recrystallization cellular automata model is verified by industrial experiment. The organizational performances of rolling bearing ring are measured and analyzed, and the process parameters are optimized based on the measured results and simulated results.