Open AccessNumerical prediction of aerodynamic performance for open geometry centrifugal compressor
Author(s) -
Toshio Kawahara,
Nobuhiko Yamasaki
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1509/1/012025
Subject(s) - reynolds averaged navier–stokes equations , centrifugal compressor , impeller , aerodynamics , turbulence , computational fluid dynamics , mechanics , diffuser (optics) , gas compressor , overall pressure ratio , engineering , mechanical engineering , physics , light source , optics
Numerical prediction of aerodynamic performance of compressors has been widely performed by the RANS model, but there is the tendency to overestimate the work and efficiency of the impeller of a centrifugal compressor. In the RANS, we cannot analyze unsteady phenomena such as tip leakage flow. On the other hand, the LES models universal region of turbulence by performing spatial filtering operations. Since it does not include the concept of time averaging, it can be applied to unsteady calculations. In this paper we perform numerical prediction of aerodynamic performance by the RANS with the Spalart-Allmaras turbulence model and the LES with the Smagorinsky model, and reveal the unsteady phenomena, which cannot be analyzed by the RANS, by comparing each result. The CFD solver that we use is “UPACS”, which JAXA (Japan Aerospace Exploration Agency) has developed. We clarify its prediction accuracy and problem points of UPACS. The geometry data of the centrifugal compressor that we analyze is published in the papers written by Krain. The compressor is equipped with impeller with 24 full blades and vaneless diffuser. Comparing computed characteristic curves of mass-averaged total pressure, using the LES improves the overestimation of the total pressure ratio by the RANS by 10%. It seems that the LES can analyze the unsteady phenomena which the RANS cannot.