文献
J-GLOBAL ID:202102281277956074
整理番号:21A2606256
相変化材料を用いた熱エネルギー貯蔵プラットフォームの性能と信頼性強化のための機械学習(人工ニューラルネットワーク)の利用【JST・京大機械翻訳】
Leveraging Machine Learning (Artificial Neural Networks) for Enhancing Performance and Reliability of Thermal Energy Storage Platforms Utilizing Phase Change Materials
著者 (3件):
Chuttar Aditya
(J. Mike Walker ‘66, Department of Mechanical Engineering, Texas A&M University, MS 3123 TAMU, College Station, TX 77843-3123)
,
Thyagarajan Ashok
(J. Mike Walker ‘66, Department of Mechanical Engineering, Texas A&M University, MS 3123 TAMU, College Station, TX 77843-3123)
,
Banerjee Debjyoti
(J. Mike Walker ‘66, Department of Mechanical Engineering, Harold Vance Department of Petroleum Engineering, Engineering-Medicine Program, College of Engineering, Department of Medical Education, College of Medicine, Mary Kay O’Connor Process Safety Center, Gas and Fuels Research Center, E...)
資料名:
Journal of Energy Resources Technology
(Journal of Energy Resources Technology)
巻:
144
号:
2
ページ:
Null
発行年:
2022年
JST資料番号:
A0797B
ISSN:
0195-0738
CODEN:
JERTD2
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)