文献
J-GLOBAL ID:202102282427463294
整理番号:21A0769829
半経験的および機械学習モデルに基づくタングステンナノ粒子で強化したポリクロロプレンゴム(CR)の多軸疲れ寿命予測【JST・京大機械翻訳】
Multiaxial fatigue life prediction of polychloroprene rubber (CR) reinforced with tungsten nano-particles based on semi-empirical and machine learning models
著者 (5件):
Choi Joeun
(Net Shape Manufacturing Laboratory, Department of Mechanical Engineering, Sogang University, Republic of Korea)
,
Quagliato Luca
(Net Shape Manufacturing Laboratory, Department of Mechanical Engineering, Sogang University, Republic of Korea)
,
Lee Seungro
(Net Shape Manufacturing Laboratory, Department of Mechanical Engineering, Sogang University, Republic of Korea)
,
Shin Junghoon
(DongWon EN-Tec, 56-13 Hoehak-ro, 44992 Ulsan, Republic of Korea)
,
Kim Naksoo
(Net Shape Manufacturing Laboratory, Department of Mechanical Engineering, Sogang University, Republic of Korea)
資料名:
International Journal of Fatigue
(International Journal of Fatigue)
巻:
145
ページ:
Null
発行年:
2021年
JST資料番号:
D0802B
ISSN:
0142-1123
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)