Development of a general numerical methodology for CFD analyses in sliding vane machines and application on a mid-size oil injected air compressor
Bianchi, G., Kovacevic, A., Cipollone, R. , Murgia, S. & Contaldi, G. (2016). Development of a general numerical methodology for CFD analyses in sliding vane machines and application on a mid-size oil injected air compressor. Paper presented at the 23rd International Compressor Engineering Conference, 11-14 Jul 2016, Indiana, USA.
Abstract
The current work presents the development of a numerical methodology to investigate sliding vane rotary machines by means of advanced design tools such as the Computational Fluid Dynamics ones. Although highly limited in this topic, literature shows that the major constraint for the employment of such approaches is the deformation and motion of the rotor mesh, i.e. the computational grid related to the fluid volume between stator, rotor and blades of the positive displacement vane device. To address these issues, a novel grid generation approach is herein proposed and accomplished through a series of steps: geometrical 2D modeling of the machine cross section profile, boundary generation of the rotor mesh and, eventually, distribution of computational nodes using algebraic algorithms with transfinite interpolation, post orthogonalization and smoothing. This methodology was subsequently tested on an industrial vane compressor comparing the results of oil free and oil injected simulations set up in the ANSYS CFX solver. Results show angular pressure evolution inside the compressor vanes, a recirculation region induced by the clearance between the vane tip and the stator as well as the cooling effects of the oil entrained in the cells during the compression phase.
Publication Type: | Conference or Workshop Item (Paper) |
---|---|
Additional Information: | Copyright Authors 2016 |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Departments: | School of Science & Technology > Engineering |
Download (947kB) | Preview
Export
Downloads
Downloads per month over past year