文献
J-GLOBAL ID:202002241865162826
整理番号:20A0335293
機械学習により推定した熱力学データを用いた非平衡フェーズフィールドモデルによる凝固解析【JST・京大機械翻訳】
Solidification analysis by non-equilibrium phase field model using thermodynamics data estimated by machine learning
著者 (6件):
Nomoto Sukeharu
(Department of Materials Design Innovation Engineering, Nagoya University, Nagoya, Japan)
,
Nomoto Sukeharu
(Science & Engineering System Division, ITOCHU Techno-Solutions Corporation, Tokyo, Japan)
,
Wakameda Hiroshi
(Science & Engineering System Division, ITOCHU Techno-Solutions Corporation, Tokyo, Japan)
,
Segawa Masahito
(Science & Engineering System Division, ITOCHU Techno-Solutions Corporation, Tokyo, Japan)
,
Yamanaka Akinori
(Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo, Japan)
,
Koyama Toshiyuki
(Department of Materials Design Innovation Engineering, Nagoya University, Nagoya, Japan)
資料名:
Modelling and Simulation in Materials Science and Engineering
(Modelling and Simulation in Materials Science and Engineering)
巻:
27
号:
8
ページ:
084008 (15pp)
発行年:
2019年
JST資料番号:
W0484A
ISSN:
0965-0393
CODEN:
MSMEEU
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
イギリス (GBR)
言語:
英語 (EN)