open access

https://hdl.handle.net/2115/75380

Prediction of Microsegregation Behavior in Fe-based Alloys Based on Machine Learning

日本語

simulation

2017-12-01

日本鉄鋼協会

鉄と鋼

103(12)

711-719

A prediction method for microsegregation in Fe-based alloys was developed based on an approach of machine learning called Deep Learning. A set of model and algorithm of Deep Learning suitable for description of microsegregation was constructed by employing training data obtained by one-dimensional finite difference calculations for interdendritic microsegregation. It is shown that the developed method enables accurate prediction of the microsegregation behavior in Fe-based binary and ternary alloys with the solute atoms of C, Si, Mn, P and S. The present results demonstrate that Deep Learning offers a promising way of constructing an easy-to-use approach for prediction of microsegregation with high accuracy. Importantly, it is expected that the present method can be extended to describe effects of microstructural processes on microsegregation behavior.

学術雑誌論文

Version of Record

著作権は日本鉄鋼協会にある

0021-1575

1883-2954

AN00151251