Li Meng, Jun-ming Liu, Ning Zhang, Hao Wang, Yu Han, Cheng-xu He, Fu-yao Yang, and Xin Chen, Simulation of recrystallization based on EBSD data using a modified Monte Carlo model that considers anisotropic effects in cold-rolled ultra-thin grain-oriented silicon steel, Int. J. Miner. Metall. Mater., 27(2020), No. 9, pp.1251-1258. https://dx.doi.org/10.1007/s12613-020-2102-4
Cite this article as: Li Meng, Jun-ming Liu, Ning Zhang, Hao Wang, Yu Han, Cheng-xu He, Fu-yao Yang, and Xin Chen, Simulation of recrystallization based on EBSD data using a modified Monte Carlo model that considers anisotropic effects in cold-rolled ultra-thin grain-oriented silicon steel, Int. J. Miner. Metall. Mater., 27(2020), No. 9, pp.1251-1258. https://dx.doi.org/10.1007/s12613-020-2102-4

Simulation of recrystallization based on EBSD data using a modified Monte Carlo model that considers anisotropic effects in cold-rolled ultra-thin grain-oriented silicon steel

  • A Monte Carlo Potts model was developed to simulate the recrystallization process of a cold-rolled ultra-thin grain-oriented silicon steel. The orientation and image quality data from electron backscatter diffraction measurements were used as input information for simulation. Three types of nucleation mechanisms, namely, random nucleation, high-stored-energy site nucleation (HSEN), and high-angle boundary nucleation (HABN), were considered for simulation. In particular, the nucleation and growth behaviors of Goss-oriented (011<100>) grains were investigated. Results showed that Goss grains had a nucleation advantage in HSEN and HABN. The amount of Goss grains was the highest according to HABN, and it matched the experimental measurement. However, Goss grains lacked a size advantage across all mechanisms during the recrystallization process.
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