A Combined Method to Model Dynamic Recrystallization Based on Cellular Automaton and a Phenomenological (CAP) Approach

Abstract

Titanium alloys with high stacking-fault energy show continuous dynamic recrystallization (CDRX) instead of discontinuous dynamic recrystallization (DDRX) during high-temperature deformation. During the CDRX mechanism, new recrystallized grains are generated by the progressive increasing of the low-angle boundary misorientations. In the present work, the CDRX phenomenon was modeled by using a cellular automaton (CA)-based method. The size of seeds was determined based on a phenomenological approach, and then the number and distribution of recrystallized grains as well as the topological changes were applied by utilizing the CA approach. In order to verify the capacity of the proposed model for predicting the microstructural characteristics, the experimental data of the hot-compressed TiNiFe alloy were used. Results showed that the presented model can accurately estimate the fraction of the recrystallized area. Moreover, the macroscopic flow curves of the alloy were well predicted by the present model.