Performance evaluation and entropy generation of chevron-type plate-fin equipped with ribs and holes

Abstract

The complexity caused by an enhanced technique may significantly enhance the heat transfer along with a penalty in the pressure drop. Thus, it is needed to assess the counteracting effects between the enhanced heat transfer and the augmented pressure drop in practical applications. In order to comprehensively evaluate the hydrothermal performance of the chevron-type plate-fin (CTPF) equipped with ribs and holes, this study focuses on the relationship between hydraulic and thermal characteristics. Firstly, the relationship between the Colburn factor and the friction factor is presented, then two performance indexes are applied using these factors to evaluate the use of ribs and holes in the CTPIt F is found that the simultaneous use of ribs and holes shows better overall performances as compared with the use of ribs or holes individually. At the same geometrical parameters, the highest values of 1.52 and 1.07 are recorded for these performance indexes. In order to further improve the overall performance of the CTPF, the effects of geometrical parameters are also investigated. With the decrease of corrugation amplitude ( a) and the increase of corrugation length ( l), rib height ( h), and rib thickness ( t), the CTPF performs better overall performances. And, for the models with different levels of hole width ( w), the better performance is seen when this parameter is at the middle level. However, in the studied models, the best overall hydrothermal performance is detected for the model with a = 2.5 mm, l = 60 mm, h = 2.5 mm, t = 10 mm, and w = 10 mm, and highest performance indexes of 2.52 and 1.15 are reported for this model. Likewise, an entropy generation analysis is carried out, and the obtained results are discussed based on the Bejan number and entropy generation number. The results show that the increase of Reynolds number can lead to decrease of Bejan number and to increase of entropy generation number. For Reynolds number ranging from 4000 to 10000, the best model, which is described above, shows 17% decrease in the entropy generation number comparing with the reference model. Finally, two correlations are developed to predict the Bejan number and entropy generation number of the current study.