Machine learning-based prediction of heat transfer performance in annular fins with functionally gra...
Machine learning-based prediction of heat transfer performance in annular fins with functionally graded materials
About this item
Full title
Author / Creator
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
This paper presents a study investigating the performance of functionally graded material (FGM) annular fins in heat transfer applications. An annular fin is a circular or annular structure used to improve heat transfer in various systems such as heat exchangers, electronic cooling systems, and power generation equipment. The main objective of this...
Alternative Titles
Full title
Machine learning-based prediction of heat transfer performance in annular fins with functionally graded materials
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_c2985364304f42c299a3761a8b8be61b
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c2985364304f42c299a3761a8b8be61b
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-024-58595-6
