Validation and predictions of coupled finite element and cellular automata model: Influence of the degree of deformation on static recrystallization kinetics case study

Digital/virtual microstructures in application to metals engineering – A review

“…static or dynamic recrystallization modeling, however this topic is not addressed within the present work. For more details on that matter refer to [23,56,57].…”

Importance of Non-uniform Boundary Migration for Recrystallization Kinetics

“…[5]) or variations of local stored energy (e.g. [4,[48][49][50][51]) has been frequently used to explain the decrease of the average boundary migration velocity during annealing. Our quantitative analysis based on the ex-situ characterization shows that after two steps of annealing, the recovery of the deformed matrix is very minor, which excludes the possibility of concurrent recovery for slowing down boundary migration.…”

Simulation of CP-Ti Recrystallization and Grain Growth by a Cellular Automata Algorithm: Simulated Versus Experimental Results

“…In most cases, possible solutions to such equations are only obtained numerically, with the differential formulation transformed, for example, into a finite difference scheme to be implemented computationally using an appropriate algorithm. Alternatively, it is possible to describe the spatiotemporal evolution of complex systems by models that are implemented using algorithms involving cellular automata 1,2 . A cellular automaton consists of a grid of cells, also called sites, which is arranged in one, two or three dimensions and may present various geometric shapes such as squares, rectangles, hexagons or cubes.…”

“…Among the several possibilities for defining the neighborhood of a given cell, the ones most commonly used are those proposed by von Neumann and Moore, which consider, respectively, the 4 and 8 nearest neighbors for a lattice of square cells. Transformation rules, which may be deterministic or probabilistic, are applied simultaneously to all the cells of the grid at each level in time 1,2 . With these characteristics, cellular automata provide a discrete method to directly simulate the evolution of complex dynamic systems that contain large numbers of similar components, based on short or long-range local interactions among their elements.…”

“…Stiko 2 and Davies 6 modified the rules of transition between neighboring cells using growth models related to a realistic time scale. Others researchers investigated the influence of initial microstructure topologies on the kinetics of static recrystallization in simulations by CA 1,2,7 , and static recrystallization in cold-worked copper 8 and in iron 9 were recently simulated by a CA algorithm. Dynamic recrystallization models using cellular automata were proposed by Goetz and Seetharaman 10 , Qian…”