Optimization of a centrifugal compressor impeller using CFD: the choice of simulation model parameters

• Published in: IOP conference series. Materials Science and Engineering Vol. 232; no. 1; pp. 12037 - 12046
• Main Authors: Neverov, V V, Kozhukhov, Y V, Yablokov, A M, Lebedev, A A
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.08.2017
• Subjects: Centrifugal compressors; Computational fluid dynamics; Computing time; Domains; Finite element method; Fluid dynamics; Fluid flow; Impellers; Low pressure; Model accuracy; Optimization; Parameters; Shear stress; Topology; Turbomachinery; Turbulence models
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/232/1/012037

Nowadays the optimization using computational fluid dynamics (CFD) plays an important role in the design process of turbomachines. However, for the successful and productive optimization it is necessary to define a simulation model correctly and rationally. The article deals with the choice of a grid and computational domain parameters for optimization of centrifugal compressor impellers using computational fluid dynamics. Searching and applying optimal parameters of the grid model, the computational domain and solver settings allows engineers to carry out a high-accuracy modelling and to use computational capability effectively. The presented research was conducted using Numeca Fine/Turbo package with Spalart-Allmaras and Shear Stress Transport turbulence models. Two radial impellers was investigated: the high-pressure at ψT=0.71 and the low-pressure at ψT=0.43. The following parameters of the computational model were considered: the location of inlet and outlet boundaries, type of mesh topology, size of mesh and mesh parameter y+. Results of the investigation demonstrate that the choice of optimal parameters leads to the significant reduction of the computational time. Optimal parameters in comparison with non-optimal but visually similar parameters can reduce the calculation time up to 4 times. Besides, it is established that some parameters have a major impact on the result of modelling.