Deterioration of axial compressors is in general a major concern in aircraft engine maintenance. Among other effects, roughness in high-pressure compressor reduces the pressure rise and thus efficiency, thereby increasing the specific fuel consumption of an engine. Therefore, it is important to improve the understanding of roughness on compressor blading and their impact on compressor performance. To investigate the surface roughness of rotor blades of a compressors, different stages of an axial high-pressure compressor and a first-stage blisk (BLade–Integrated–dISK) of a regional aircraft engine is measured by a three-dimensional laser scanning microscope. Fundamental types of roughness structures can be identified: impacts in different sizes, depositions as isotropically distributed single elements with steep flanks and anisotropic roughness structures direct approximately normal to the flow direction. To characterise and quantify the roughness structures in more detail, roughness parameters were determined from the measured surfaces. The quantification showed that the roughness height varies through the compressor depending on the stage, position and the blade side. Overall complex roughness structures of different shape, height and size are detected regardless of the type of the blades.
The objective of this study is to quantify the sensitivity of blade roughness on the overall performance of a 10-stage high-pressure compressor of the jet engine type V2500-A1. The Reynolds-Averaged Navier-Stokes flow solver TRACE is used to study the multistage compressor. The three-dimensional numerical setup contains all geometric and aerodynamic features such as bleed ports and the variable stator vanes system. In order to estimate the effect of stage roughness on overall compressor performance, compressor maps of the CFD-model are created by modeling the surface roughness separately for a single stage and combinations of stages. The surface roughness values are applied to the blade's suction side of the first, center and last stage in the CFD-model by setting an equivalent sand-grain value. This equivalent sand-grain roughness is determined from non-intrusive measurements of blade surfaces from an equivalent real aircraft engine for the first, center and last stage. In addition, further simulations are conducted to analyze the performance drop of a fully rough HPC due to surface roughness. The studies are performed at the operating conditions 'cruise' and 'take-off' to cover two different Reynolds number regimes. The results show that the models with roughness in a single stage already lead to significantly lower mass flow rates because of higher blockage compared to the smooth compressor. In fact, roughness at the first stage has the biggest effect on the overall performance with a drop in performance of about 0.1% while the effect of the last stage is the smallest. This behavior is mainly caused by enhanced instabilities through the compressor changing the stage-by-stage matching of the stages downstream. In addition to the displacement of the compressor maps to a lower mass flow, a reduction of stall and choke margins is noticeable.
Roughened aeroengine blade surfaces lead to increased friction losses and reduced efficiency of the individual blades. The surface roughness also affects the wake flow of the blade and thus the inflow conditions for the subsequent compressor or turbine stage. To investigate the impact of surface roughness on a turbulent blade wake, we conducted velocity field measurements by means of stereo particle image velocimetry in the wake of a roughened turbine blade in a linear cascade wind tunnel. The turbine blade was roughened at different chordwise locations. The influence of the chordwise location of the added surface roughness was examined by comparing their impact on the width and depth of the wake and, the positions and distribution of vortical structures in the wake. Additionally, the friction loss coefficients for different surface roughness positions were estimated directly from the velocity field.
Defects in the hot-gas path of aero engines have been shown to leave typical signatures in the density distribution of the exhaust jet. These signatures are superposed when several defects are present. For improved maintenance and monitoring applications, it is important to not only detect that there are defects present but to also identify the individual classes of defects. This diagnostic approach benefits both, the analysis of prototype or acceptance test and the preparation of Maintenance, Repair, and Overhaul.
Recent advances in the analysis of tomographic Background-Oriented Schlieren (BOS) data have enabled the technique to be automated such that typical defects in the hot-gas path of gas turbines can be detected and distinguished automatically. This automation is achieved by using Support Vector Machine (SVM) algorithms. Choosing suitable identification parameters is critical and can enable SVM algorithms to distinguish between different defect types. The results show that the SVM can be trained such that almost no defects are missed and that false attributions of defect classes can be minimized.
= normal distance to the chord line F s = wall shear stress force k = surface roughness height Ma = Mach number n p = number of roughness patches p = local static pressure p in = static pressure inlet p dyn = dynamic pressure Re c = Reynolds number based on chord length t = pitch x, y = linear cascade coordinates system x a , x n = wake coordinates system x c = chord coordinate system β = wake deflection angle ζ F s = loss coefficient due surface roughness λ = stagger angle
Roughened aeroengine blade surfaces lead to increased friction losses and reduced efficiency of the individual blades. Surface roughnesses on aeroengine blades in operation are complex and characterized by a non-uniform distribution of surface roughness elements of different dimensions. To investigate the resulting effect on the aerodynamic loss of combinations of localized surface roughness patches, we conducted velocity field measurements by means of stereo particle image velocimetry in the wake of a roughened turbine blade in a linear cascade wind tunnel. Four chord-wise locations were selected and every possible combination of surface roughness application at one to four of these positions was investigated. A loss coefficient was determined directly from the wake velocity field to quantify the aerodynamic loss allowing to compare the different roughness configurations. For a single roughness patch, the location has a strong influence on the induced loss. The friction loss coefficients for combinations of multiple roughness patches can be well described in function of a combined effective chord-normal location.
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