Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : November 23, 2018 - November 25, 2018
We have proposed the data assimilation (DA) methodology based on the ensemble Kalman filter (EnKF) to estimate the unmeasurable state and the unknown parameters used in multi-phase-field (MPF) simulations. In this study, we apply the EnKF-based DA method to estimate the anisotropic grain boundary properties of Coincidence Site Lattice (CSL) grain boundaries and the driving force for the growth of recrystallized nucleus assumed in the three-dimensional MPF simulation of the static recrystallization. In order to validate the DA method, we perform the numerical experiments called twin experiments where the unknown parameters are estimated based on synthetic observational data. The results of the twin experiments demonstrate that the proposed DA method can estimate the ∑7 CSL grain boundary mobility peak, grain boundary energy cusp and the distribution of the stored energy in the deformed grains.
