3D modelling of ferrite and austenite grain coarsening using real-valued cellular automata based on transition function

Abstract

A new extended technique for 3D modelling of normal grain growth in low carbon steels is presented in this paper. This technique is based on real-valued cellular automata with the use of a local transition function that allows it to be applied to materials with both fcc and bcc lattices with the grain growth being easily simulated in ferrite as well as in austenite cases. The simulated data were calibrated with four sets of experimental data for isothermal grain coarsening in austenite, alpha- and delta-ferrites. The obtained results cogently demonstrate that there is a good agreement between simulated and experimental data across a wide range of temperatures. The new model developed in this paper, allows for the identification of two different mechanisms of grain growth in austenite. It is also shown in this paper that the newly presented approach can be used to extract additional parameters from the grain growth process, such as grain boundary velocity, mobility and driving force, which are hardly accessible even via real-time experiments.