Grain growth prediction based on data assimilation by implementing 4DVar on multi-phase-field model-Reference-Cited by-同舟云学术

Grain growth prediction based on data assimilation by implementing 4DVar on multi-phase-field model

Published:2017-10-30 Issue:1 Volume:18 Page:857-868
ISSN:1468-6996
Container-title:Science and Technology of Advanced Materials
language:en
Short-container-title:Science and Technology of Advanced Materials

Author:

Ito Shin-ichi¹,Nagao Hiromichi¹²,Kasuya Tadashi³,Inoue Junya³⁴

Affiliation:

1. Earthquake Research Institute, The University of Tokyo, Tokyo, Japan.

2. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan.

3. Graduate School of Engineering, The University of Tokyo, Tokyo, Japan.

4. Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan.

Funder

Council for Science, Technology and Innovation (CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP), ``Structural Materials for Innovation''

Publisher

Informa UK Limited

Subject

General Materials Science

Link

https://tandfonline.com/doi/pdf/10.1080/14686996.2017.1378921

Reference29 articles.

1. Grain Growth Predictions in Microalloyed Steels.

2. Prediction Model for the Austenite Grain Size in the Coarse Grained Heat Affected Zone of Fe-C-Mn Steels: Considering the Effect of Initial Grain Size on Isothermal Growth Behavior

3. Prediction of austenite grain growth during austenitization of low alloy steels

4. Modeling and numerical simulations of dendritic crystal growth

5. A phase field concept for multiphase systems

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