Abstract
The aim of this paper is to assess the impact of the mutual positioning of the turbine stage stator and rotor blades on noise generation. The Ansys CFX commercial software package and the Scale-Adaptive Simulation (SAS) hybrid turbulence model are used for numerical analyses. The paper is focused on an analysis that the pressure wave generation resulting from unsteady flow phenomena. In order to present the problem, the Fast Fourier Transformation (FFT) analysis of pressure fluctuation is carried out at selected points of the turbine stage computational domain. A comparison of values of individual components for subsequent control points allows an approximate determination of the place of generation of pressure waves, the direction of their propagation and the damping rate. Moreover, the numerical analyses make it possible to evaluate the justification for the use of the SAS model, which is rather demanding in terms of equipment, in simulations of unsteady flow fields where generation and propagation of noise waves occur.
Highlights
The rapid development of numerical methods and techniques in the last two decades has made it possible to carry out more and more complex analyses using the Computational Fluid Dynamics (CFD) tools
This paper presents the methodology and the results of CFD analyses comprising the flow in the turbine stage of an engine
This paper presents an analysis of the unsteady flow field in a turbine stage operating under a high load
Summary
The rapid development of numerical methods and techniques in the last two decades has made it possible to carry out more and more complex analyses using the Computational Fluid Dynamics (CFD) tools. Owing to the use of computer software in flow analyses, it is possible to avoid high costs related to the construction of test stations and reduce the time needed to obtain the optimum structure. It is significant that simulation results contain full information on the flow medium properties which under experimental conditions often cannot be measured (e.g. density or entropy). These advantages contribute to the fact that numerical analyses are gaining popularity in industries such as power engineering or aviation.
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