Machine learning based frost thickness prediction of carbon fiber-reinforced polymer composite fin for potential heat pump application-Reference-Cited by-同舟云学术

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Machine learning based frost thickness prediction of carbon fiber-reinforced polymer composite fin for potential heat pump application

Published:2024-04 Issue: Volume:153 Page:107333
ISSN:0735-1933
Container-title:International Communications in Heat and Mass Transfer
language:en
Short-container-title:International Communications in Heat and Mass Transfer

Author:

Abbas Saleem,Park Chan Woo

Funder

Ministry of SMEs and Startups

Ministry of Trade, Industry and Energy

National Research Foundation of Korea

Publisher

Elsevier BV

Reference37 articles.

1. A novel design method for ASHPs considering output heating capacity and frosting suppression;Liang;Energ. Build.,2020

2. Defrost improvement by heat pump refrigerant charge compensating;Zhiyi;Appl. Energy,2008

3. Recent progress on developing anti-frosting and anti-fouling functional surfaces for air source heat pumps;Heu;Energ. Build.,2020

4. Analysis of frost thickness and roughness growth from the perspective of frost crystal structure;Zhang;Int. J. Refrig.,2020

5. Effective thermal conductivity of frost during the crystal growth period;Şahin;Int. J. Heat Mass Transf.,2000

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Carbon Fiber and Its Composites: Synthesis, Properties, Applications;Sinop Üniversitesi Fen Bilimleri Dergisi;2024-06-29

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