Grain growth prediction based on data assimilation by implementing 4DVar on multi-phase-field model
We propose a method to predict grain growth based on data assimilation by using a four-dimensional variational method (4DVar). When implemented on a multi-phase-field model, the proposed method allows us to calculate the predicted grain structures and uncertainties in them that depend on the quality...
Main Authors: | Shin-ichi Ito, Hiromichi Nagao, Tadashi Kasuya, Junya Inoue |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2017-12-01
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Series: | Science and Technology of Advanced Materials |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/14686996.2017.1378921 |
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