文献
J-GLOBAL ID:202202235281460890
整理番号:22A1096092
内面2フランジ負荷下の穴あきロール成形アルミニウム合金非滑りチャネルのウェブクリッピング挙動を研究するための新しい機械学習法【JST・京大機械翻訳】
A novel machine learning method to investigate the web crippling behaviour of perforated roll-formed aluminium alloy unlipped channels under interior-two flange loading
著者 (7件):
Fang Zhiyuan
(Department of Civil and Environmental Engineering, The University of Auckland, New Zealand)
,
Roy Krishanu
(School of Engineering, The University of Waikato, New Zealand)
,
Xu Jinzhao
(Department of Civil and Environmental Engineering, The University of Auckland, New Zealand)
,
Dai Yecheng
(Department of Civil and Environmental Engineering, The University of Auckland, New Zealand)
,
Paul Bikram
(Department of Civil Engineering, National Institute of Technology, India)
,
Lim James B.P.
(Department of Civil and Environmental Engineering, The University of Auckland, New Zealand)
,
Lim James B.P.
(School of Engineering, The University of Waikato, New Zealand)
資料名:
Journal of Building Engineering
(Journal of Building Engineering)
巻:
51
ページ:
Null
発行年:
2022年
JST資料番号:
W3072A
ISSN:
2352-7102
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)