Analyzing and Extending Cellular Automaton Simulations of Dynamic Recrystallization
R. S. Subramanian
R. S. Shree
P. G. Kubendran Amos*
Theoretical Metallurgy Group
Department of Metallurgical and Materials Engineering
National Institute of Technology Tiruchirappalli
Tamil Nadu, India
*corresponding author, prince@nitt.edu
Abstract
A polycrystalline system corroborating experimentally observed microstructure is developed in this paper by employing cellular automata techniques. Moreover, through appropriate transition functions, microstructural changes accompanying dynamic recrystallization, a manufacturing technique associated with the production of a wide range of components, are simulated. The grain growth that characterizes this change is analyzed to explicate the trend in the temporal evolution of mean grain size and its kinetics. As opposed to a progressive increase in mean grain size, which generally typifies a conventional grain growth, in dynamic recrystallization it is observed that the mean grain size increases and decreases sequentially, thereby rendering an oscillating pattern. A perceptive investigation of the fluctuating trend unravels individual growth events, characterized by monotonic increase in mean grain size, whose kinetics follows the third-order power law. Additionally, the existing approach of modeling dynamic recrystallization is extended to facilitate unrestricted yet energetically favored growth of defect-free nuclei across their neighboring grains.
Keywords: dynamic recrystallization; grain growth; kinetics; cellular automata
Cite this publication as:
R. S. Subramanian, R. S. Shree and P. G. Kubendran Amos, “Analyzing and Extending Cellular Automaton Simulations of Dynamic Recrystallization,” Complex Systems, 32(2), 2023 pp. 189–209.
https://doi.org/10.25088/ComplexSystems.32.2.189
