期刊
ENGINEERING OPTIMIZATION
卷 42, 期 4, 页码 305-323出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/03052150903143935
关键词
heat sink optimum design; multi-objective evolutionary algorithm; finite volume method; shape optimization; computational fluid dynamics
资金
- Thailand Research Fund (TRF)
This article demonstrates the practical applications of a multi-objective evolutionary algorithm (MOEA) namely population-based incremental learning (PBIL) for an automated shape optimization of plate-fin heat sinks. The computational procedure of multi-objective PBIL is detailed. The design problem is posed to find heat sink shapes which minimize the junction temperature and fan pumping power while meeting predefined constraints. Three sets of shape design variables used in this study are defined as: vertical straight fins with fin height variation, oblique straight fins with steady fin heights, and oblique straight fins with fin height variation. The optimum results obtained from using the various sets of design variables are illustrated and compared. It can be said that, with this sophisticated design system, efficient and effective design of plate-fin heat sinks is achievable and the best design variables set is the oblique straight fins with fin height variation.
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