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...

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Detalles Bibliográficos
Autores principales: Ito, Shin-ichi, Nagao, Hiromichi, Kasuya, Tadashi, Inoue, Junya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2017
Materias:
Focus on Future leaders in structural materials research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678441/
https://www.ncbi.nlm.nih.gov/pubmed/29152018
http://dx.doi.org/10.1080/14686996.2017.1378921

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678441/
https://www.ncbi.nlm.nih.gov/pubmed/29152018
http://dx.doi.org/10.1080/14686996.2017.1378921

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