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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
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
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基于EBSD数据,采用考虑各向异性效应的改进蒙特卡罗模型对冷轧超薄晶粒取向硅钢的再结晶过程进行了模拟

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

Abstract: 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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