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contributor authorJiang, Boyan
contributor authorYang, Xiaopei
contributor authorWang, Jun
contributor authorLin, Zhiliang
contributor authorHu, Jinkang
date accessioned2024-04-24T22:50:33Z
date available2024-04-24T22:50:33Z
date copyright1/16/2024 12:00:00 AM
date issued2024
identifier issn0889-504X
identifier otherturbo_146_5_051007.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4295971
description abstractAn improved passage-flow turning model (IPTM) was developed in this study to design high-performance forward-curved blades for squirrel-cage fans. The flow separation in blade passages and the corresponding fan performance were compared between IPTM and traditional methods through computational fluid dynamics (CFD). The results show that correcting the blade inlet angle, based on the zero-incidence design, is crucial to prevent separation of the passage mainstream from the blade pressure surface. The blade shape with second-order smoothness also exhibits the thinnest separation and highest efficiency when other design parameters remain constant. Considering these findings, the blades designed by IPTM outperform traditional blades with the same inlet and outlet angles. The optimal values of the turning radius R¯T and the decelerating factor of the leading half blade ɛ were determined based on the CFD results. The designed blade achieves high pressure when these two parameters satisfy R¯T=−0.185ε+0.29175, while achieving high efficiency when they satisfy R¯T=−0.31ε+0.4425. To confirm the advantages of IPTM, an optimal IPTM-based blade was manufactured and measured. The results indicated that the maximum increase in fan pressure and efficiency reaches 10% and 6%, respectively.
publisherThe American Society of Mechanical Engineers (ASME)
titleAn Improved Passage-Flow Turning Model for Forward-Curved Blades of Squirrel-Cage Fan
typeJournal Paper
journal volume146
journal issue5
journal titleJournal of Turbomachinery
identifier doi10.1115/1.4064309
journal fristpage51007-1
journal lastpage51007-16
page16
treeJournal of Turbomachinery:;2024:;volume( 146 ):;issue: 005
contenttypeFulltext


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