Optimization analysis for louver fin heat exchangers

Ying Chi Tsai, Jiin-Yuh Jang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The present study is aimed at optimization of the geometers of the fin-and-tube heat exchanger with louver fin through numerical simulation. The optimization is carried out by using the simplified conjugate-gradient method (SCGM) is adopted for solving the optimal problem. Using the optimizer, the louver angle of louvered fin is adjusted toward the maximization of the performance of the heat exchanger. It is also shown that the maximum of area reduction ratios at the louver fin for Re Lp 100 - 400 with Lp = 1 mm. For the louver pitches, the following correlations for the optimal louver angle are derived, based on Reynolds number Re Lp ranging from 100 to 400. The results indicate the optimal louver angle applied in heat exchangers can effectively enhance the heat transfer performance. Thus, the correlations is derived that can be applied to the design of heat exchangers.

Original languageEnglish
Title of host publicationProceedings of the 2011 2nd International Congress on Computer Applications and Computational Science
Pages477-482
Number of pages6
EditionVOL. 1
DOIs
Publication statusPublished - 2012 Jun 29
Event2011 2nd International Congress on Computer Applications and Computational Science, CACS 2011 - Bali, Indonesia
Duration: 2011 Nov 152011 Nov 17

Publication series

NameAdvances in Intelligent and Soft Computing
NumberVOL. 1
Volume144 AISC
ISSN (Print)1867-5662

Other

Other2011 2nd International Congress on Computer Applications and Computational Science, CACS 2011
CountryIndonesia
CityBali
Period11-11-1511-11-17

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

Tsai, Y. C., & Jang, J-Y. (2012). Optimization analysis for louver fin heat exchangers. In Proceedings of the 2011 2nd International Congress on Computer Applications and Computational Science (VOL. 1 ed., pp. 477-482). (Advances in Intelligent and Soft Computing; Vol. 144 AISC, No. VOL. 1). https://doi.org/10.1007/978-3-642-28314-7_64