Simulation of dynamic recrystallization using irregular cellular automata

Computer simulation is a powerful tool to predict microstructure and its evolution during dynamic recrystallization. Cellular Automata (CA), as one of the most efficient methods proposed to simulate recrystallization and grain growth. In this work, recrystallization and grain growth phenomena were modelled by using a two dimensional irregular CA method. Initial grain size, nuclei density and orientation of each grain were variables which have been used as entering data to the CA model. Final grain size, orientation of each grain, dislocation density and stress-strain curve were the results which have been resulted to validate the current model. Considering the model assumptions, it is shown that the CA can successfully simulate dynamic recrystallization

Structure-property relations of metallic materials with multiscale microstructures

Nanostructured metals have higher strength than those of the coarse grained metals but suffer from the extremely limited ductility. Development of the multiscale microstructures can improve the ductility of these high strength materials due to the introduction of a specific range of grain sizes in micro level. The present work relates the multiscale microstructures in metals to their overall structure properties using a fractal theory and the modified mean-field method, where three microstructural parameters are introduced and thus mechanical properties such as strength and ductility are presented as a function of these microstructural parameters. Meanwhile, with the applications of the finite element method, the multiscale unit cell approach is also critically developed and applied with a focus on predicting the related stress-strain relations of the metals with multiscale microstructures. For verification of these proposed theoretical and numerical algorithms, the mechanical properties of the pure copper with three-grain microstructures are investigated and the results from FEA and theoretical solutions have a reasonable agreement

Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy

Microstructural evolution and plastic flow characteristics of a Ni-based superalloy were investigated using a simulative model that couples the basic metallurgical principle of dynamic recrystallization (DRX) with the twodimensional (2D) cellular automaton (CA). Variation of dislocation density with local strain of deformation is considered for accurate determination of the microstructural evolution during DRX. The grain topography, the grain size and the recrystallized fraction can be well predicted by using the developed CA model, which enables to the establishment of the relationship between the flow stress, dislocation density, recrystallized fraction volume, recrystallized grain size and the thermomechanical parameters

Simulation of dynamic recrystallization using random grid cellular automata

Computer simulation is a powerful tool to predict microstructure and its evolution in dynamic and post-dynamic recrystallization. CAFE proposed as an appropriate approach by combining finite element (FE) method and cellular automata (CA) for recrystallization simulation. In the current study, a random grid cellular automaton (CA), as micro-scale model, based on finite element (FE), as macro-scale method, has been used to study initial and evolving microstructural features; including nuclei densities, dislocation densities, grain size and grain boundary movement during dynamic recrystallization in a C-Mn steel. An optimized relation has been established between mechanical variables and evolving microstructure features during recrystallization and grain growth. In this model, the microstructure is defined as cells located within grains and grain boundaries while dislocations are randomly dispersed throughout microstructure. Changes of dislocation density during deformation are described considering hardening, recovery and recrystallization. Recrystallization is assumed to initiate near grain boundaries and nucleation rate was considered constant (site-saturated condition). The model produced a mathematical formulation which captured the initial and evolving microstructural entities and linked their effects to measurable macroscopic variables (e.g. stress).<br /

Modelling post-deformation softening kinetics of 304 austenitic stainless steel using cellular automata

The softening mechanisms after hot deformation of an austenitic stainless steel under different thermomechanical conditions were modelled using a 2D cellular automaton (CA) model. The input data to the CA model included stored energy during deformation, different levels of dynamically recrystallized (DRX) microstructures, temperature, strain and strain rate. The effects of the parameters were studied on the static and meta-dynamic recrystallization (SRX and MDRX, respectively) kinetics using the CA model. As in reality, it is not possible to abandon DRX episode from the experimental procedure and obtain SRX or MDRX, it would not be practical to study the effect of DRX on the consequent SRX and MDRX. To study the explicit effect of DRX on the post-deformation softening kinetics, deformation was simulated with and without the occurrence of DRX. Comparison of the results for the two different deformation conditions revealed that DRX and the partial recrystallized austenitic microstructure affected the post-deformation softening mechanisms by a deceleration of the post-deformation recrystallization kinetics and that the time for 50% recrystallization (t50) decreased with increasing strain, strain rate and temperature for a given initial grain size

Microstructural modeling of dynamic recrystallization using irregular cellular automata

Cellular automaton (CA) was used to simulate dynamic recrystallization (DRX) during thermomechanical deformation. Initial grain size, initial grain orientation and dislocation density were used as input data to the CA model. Flow curve, dislocation density, final grain size and orientation, and DRX volume fraction were the output data which were compared with experimental data to validate the model. The model proposed in this work considered the thermomechanical parameters (e.g., temperature and strain rate) and their role on the nucleation and growth kinetics during DRX. It was shown that the CA model can predict the final microstructure and flow curve to a high degree of accuracy and was able to successfully simulate the volume fraction of DRX as a function of strain for a wide range of deformation conditions.<br /

Numerical simulation of the static recrystalization at micro shear bands

The main aim of this work is application of the developed cellular automata (CA) model to investigate influence of the micro shear bands that are present in the heavily deformed material on the static recrystallization. This initial work is the results of recent experimental analyses indicating that the micro shear bands are preferred sites for nucleation of the recrystallization. The procedure of creation of the initial microstructure with features such as grains and micro shear bands as well as basis of the developed CA code for the static recrystallization are also presented in the paper. Finally, the simulation results obtained from different recrystallization temperatures for the microstructures with and without micro shear bands are compared with each other and differences are discussed.<br /