文献
J-GLOBAL ID:202202250251657495
整理番号:22A1082686
人工ニューラルネットワークを用いた種々のエネルギー貯蔵材料のためのガラス太陽熱蒸留器の性能解析【JST・京大機械翻訳】
Performance analysis of glass solar still for different energy storage materials using artificial neural network
著者 (8件):
Charlest M. Martin
(Department of Mechanical Engineering. Loyola ICAM College of Engineering and Technology, Chennai, India)
,
Kumar S. Lakshmana
(Department of Mechanical Engineering. Sona College Technology, Salem, India)
,
Magesh M.
(Department of Aerospace Engineering, B S Abdur Rahman Crescent Institute of Science and Technology, Chennai, India)
,
Arul K.
(Department of Mechanical Engineering, Jeppiaar SRR Engineering College, Chennai, India)
,
Thiyagu M.
(Department of Mechanical Engineering, Saveetha School of Engineering, Thandalam, Chennai, India)
,
Jawahar Raj
(Department of Mechanical Engineering, Dynamech Design Solutions, Chennai, India)
,
Saranya S. N.
(Department of Chemical Engineering. Coimbatore Institute of Technology, Coimbatore, India)
,
Mohanavel V.
(Centre for Materials Engineering and Regenerative Medicine, Bharath Institute of Higher Education and Research, Chennai, India)
資料名:
AIP Conference Proceedings
(AIP Conference Proceedings)
巻:
2405
号:
1
ページ:
050006-050006-15
発行年:
2022年
JST資料番号:
D0071C
ISSN:
0094-243X
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)