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Analytical grid generation and numerical assessment of tip leakage flows in sliding vane rotary machines

Ye, F., Bianchi, G., Rane, S. , Tassou, S. A. & Deng, J. (2021). Analytical grid generation and numerical assessment of tip leakage flows in sliding vane rotary machines. Advances in Engineering Software, 159, 103030. doi: 10.1016/j.advengsoft.2021.103030


The research presents a new analytical grid generation methodology for computational fluid dynamics studies in positive displacement sliding vane rotary machines based on the user defined nodal displacement approach. This method is more inclusive than state of the art ones since it enables the investigation of a broader range of design configurations, such as single, double and multiple-acting vane machines with non-circular housing, slanted blade and asymmetric blade tip profiles. Node number and radial divisions of blade tip are the parameters that affect most the mesh quality. The method was validated against indicated pressure measurements on a rotary vane expander resulting in a confidence interval within 4.31%. The benchmark analysis showed that the proposed method is as accurate as the manual ANSYS ICEM one but more than 1500 times faster (111s instead of 48h to generate 360 grids). The paper further proposes a novel method to track the leakage flows at the blade tip gaps of vane machines through a post-processing routine in ANSYS CFD-Post based on rotating monitoring planes. The leakage assessment on the vane expander case study showed that a 10 μm gap between blade tip and the 76 mm stator led to a 0.06 unit increase of the expander filling factor.

Publication Type: Article
Additional Information: © 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (
Publisher Keywords: Computational fluid dynamics, Analytical grid generation, Deforming grid, Sliding vane rotary machine, Tip leakage flow
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TJ Mechanical engineering and machinery
Departments: School of Science & Technology > Engineering
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Available under License Creative Commons: Attribution International Public License 4.0.

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