Reconstruction of deformed microstructure using cellular automata method

Abstract

The kinetics of microstructural evolution phenomena like recrystallization, grain growth, and phase transformation of deformed materials is affected by the characteristics of deformed microstructure. In fact, average grain size, grain morphology, texture and grain boundary properties of the deformed material determine the microstructure characteristics. In this paper, the reconstruction of deformed microstructure and changes in the microstructure in mesoscale are studied. Accordingly, the normal growth, topology deformation, and reconstruction of texture and grain boundary misorientation techniques are used to reconstruct the deformed microstructure. Therefore, probabilistic cellular automata method with hexagonal cells is used to create a microstructure with equiaxed grain morphology followed by a new modified topology deformation technique. In this technique, the quality and the quantity of the plastic deformation are considered by applying the deformation gradient tensor to the undeformed microstructure. Finally, a set of crystal orientations is created using a probabilistic algorithm relevant to the real texture of the material and then the crystal orientations are assigned to the deformed grains in such a way that satisfy the misorientation angle distribution. The accuracy of the numerical approaches is verified by comparing the experimental and the simulated results.