International Journal of Gas Turbine, Propulsion and Power Systems

Procedure for Analyzing, Manipulating and Meshing of CompressorBlades to Simulate their Flow

Gerald Reitz1 and Jens Friedrichs1

1Institute of Jet Propulsion and Turbomachinery, Technische Universitat Braunschweig,Hermann-Blenk-Straße 37, 38108 Braunschweig, Germany

ABSTRACTDuring on-wing time of a jet engine deterioration occurs and

leads to decreasing component efficiencies. This results in increas-ing Exhaust Gas Temperature (EGT) and Specific Fuel Consump-tion (SFC). Thereby, the condition of the High Pressure Compres-sor (HPC) has a comparatively large influence on these parametersdefining overall engine performance. This can be explained by achanging flow field in the HPC due to geometric deviations whichmay occur during operation. The geometries are influenced by ero-sion which results in thinner airfoils, changed leading- and trailingedge geometries, shortened airfoils and increasing tip clearance.

The objective for future maintenance strategies is to determinethe influence of the different wear mechanisms. This can be done byexperiments and Computational Fluid Dynamics (CFD). Because ofthe high number of different mechanisms and locations of deteriora-tion, CFD-calculations seem to be necessary to give a detailed viewof the influence of deterioration. In this regard, the following paperwill present a developed procedure for analyzing, manipulating andmeshing HPC-blades to simulate their flow. Therefore, three dif-ferent software-routines for the mentioned steps will be shown andexplained.

Additionally, an example blade will pass through the process andwill be manipulated for max. deviation caused by deterioration. Atthe end, a CFD-calculation of these blades will be carried out andanalyzed for its aerodynamic behavior.

NOMENCLATUREBLISK Blade Integrated DiskCFD Computational Fluid DynamicsEGT Exhaust Gas TemperatureFOD Foreign Object DamageGMC General Mesh ConnectorGUI Graphical User InterfaceHPC High Pressure CompressorLE Leading EdgeN2 High Pressure ShaftSFC Specific Fuel ConsumptionTE Trailing EdgeTKE Turbulence Kinetic EnergyTu Turbulent IntensityTLM Turbulent Length ScaleTRACE Turbomachinery Research Aerodynamics

Computational Environment

cp Isobar Heat Coefficientl Chord LengthH Absolut Duct Heighth Heightk Turbulence Kinetic EnergyMa Mach Number

n Rotational Speed of N2p Pressurept Total PressurerLE Leading Edge RadiusrT E Trailing Edge RadiusTt Total TemperaturetLE Leading Edge Thicknesstmax Max. Profile ThicknesstT E Trailing Edge ThicknessU Circumfential SpeedVax Axial Velocityy+ Dimensionless Wall Distance

α Absolut Circumferential Flow Angleβ Absolut Radial Flow Angleηis Isentropic Efficiencyε Pressure Coefficientκ1 Metal Angle at Leading Edgeκ2 Metal Angle at Trailing Edgeκ Isentropic Exponentλ Stagger Angleϕ Flow Coefficientπtt Pressure Riseτtt Temperature Riseψ Work Coefficientω Dissipation Rate per Unit of TKE

1 Rotor Entry Plane2 Rotor Exit Plane / Stator Entry Plane3 Stator Exit Plane

INTRODUCTIONThe HPC of a civil jet engine has a strong influence to its overall

efficiency. Because of deterioration, the HPC loses performanceand efficiency over its operation time, which leads to a decreasingengine performance. To ensure a constant thrust, the engine controlwill increase the fuel flow, resulting in an increasing SFC and EGT.Upon reaching a defined EGT limit, the engine has to be overhauledto prevent an excessive occurrence of over-temperature events.

At the beginning of the overhaul process, the ex-service bladeswill be appraised and classified in serviceable, repairable and non-repairable. The former ones are cleaned and get no further treatmentother than polishing, whereby the latter ones are to be discarded.Repairable blades can be recycled, for example by build-up weldingand recontouring the tip or leading- and trailing edges.

At the end of the overhaul, repaired, new and non-repaired bladesare aligned at random across the circumference. Thereby, these dif-ferent geometries will influence each other and their flow. So, thedetailed knowledge of the combinations of different geometries, theachieved efficiencies and surge limits is of great interest.

International Journal of Gas Turbine, Propulsion and Power Systems May 2016, Volume 8, Number 1

Presented at International Gas Turbine Congress 2015 Tokyo November 15-20, Tokyo, Japan Manuscript Received on December 2, 2015 Review Completed on April 18, 2016

Copyright © 2016 Gas Turbine Society of Japan

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To determine the possible deterioration levels, Marx et al. [8] an-alyzed the geometries of two complete jet engine HPC bladings. Indoing so, the blades were digitized by a structured-light 3D scan-ner in conjunction with a photogrammetric system. Afterwards,the measured point clouds were analyzed on different blade heightsfor their geometric properties, such as stagger angle and a varietyof thickness-related parameters. To determine manufacturing toler-ances Marx analyzed 300 new blades in equal measure. Marx couldshow higher deviations caused by operational effects than manufac-turing tolerances. He figured out a decreasing leading edge thick-ness of 25 % in a front stage and an increasing leading edge thick-ness of 40 % in the aft stage referenced to the new blade values.Furthermore, he could show changes in stagger angle up to ±1◦.

Based on Marx’ results, Reitz et al. [11] analyzed the behaviorof deteriorated HPC blades. The objective of his research was toorder different deterioration effects independently from each other.Therefore, three deterioration effects were investigated: Changesin leading edge thickness, max. profile thickness and stagger an-gle. These deterioration effects have been generated in differentstrengths. The range of change was given by Marx’ results andcovered the spread of determined deterioration. For the blade gen-eration an internal software was used, which allowed an indepen-dent change of geometric properties. As a result, noticeable ef-fects on stage performance caused by deterioration could be shown.Thereby, the changes of leading edge thickness had the highest im-pact, followed by max. profile thickness and stagger angle.

Further investigations have been done by Krone et al. [5], whoanalyzed the influence of deterioration on the efficiency of a HPC.Krone investigated a new, two deteriorated and a repaired blade of aHPC mid stage. Even though the changes in leading edge thicknessare smaller than those identified by Marx, the influence on perfor-mance is noticeable. A full blading with identical setup leads to adecrease in peak efficiency of 1.2 % and an offset towards higherloadings.

Kellersmann et al. [4] analyzed deterioration effects of a bladeintegrated disk (BLISK), where blades cannot be rearranged duringoverhaul. Thereby, his researches focused on the interactions be-tween blades changed in stagger angle and leading edge thickness.He confirms the trends found out by Reitz [11]. In addition, an in-terdependency of deterioration effects could be observed. At highflow coefficients, the throttle lines of the coupled deterioration ef-fects lay in between their standalone ones. Nevertheless, the staggerangle shows a higher influence at low flow coefficients, caused bythe closing and opening of the cascade.

Further investigations to compressor deterioration have beendone by Tabakoff et al. [13], who showed an increase in SFCof 0.38 % caused by blunted leading edges and additional 0.13 %caused by a higher surface roughness.

The high influence of leading edge geometry to blade perfor-mance could also be shown by Giebmanns et al. [3]. She com-pared blades with blunted leading edges; blunted leading edges andshortened chord length; reduced chord length with reshaped lead-ing edges. Thereby, she determined the leading edge geometry asa main factor for stage performance, because a properly reshapedbut shortened blade showed a comparable behavior as the new one.Such a blade was found to perform unfavourably only in terms ofstability (surge margin).

The aerodynamic influence of fan blades damaged by foreign ob-ject damage (FOD) was investigated by Bohari et al. [2]. Therefore,Bohari changed the geometry of one blade in row by rotating itsleading edge. A followed CFD-simulation for three different rota-tional speeds showed the impact of the damage to fan performance:The changes of pressure rise and mass flow rates were negligible.Nevertheless, a significantly influence on stall margin could be no-ticed. The stall margin was decreasing at all rotational speeds forthe damaged blade.

Summarized, a multitude of investigations has been carried outin the area of compressor deterioration. Nevertheless, an accurateknowledge of changed stage performance caused by different ge-ometrically deteriorations and their aerodynamic interaction is notavailable. In order to fill this knowledge gap, a semi-automatedprocess of generating deteriorated digital blades, meshing them andperforming CFD-calculations is necessary. This process would al-low for analyses of a wide range of geometric deviations, as it couldcover the whole range of realistically deteriorated blades in a jet en-gine compressor.

Such a process will be presented and demonstrated in this paper.In the first part, the designed software modules are shown. Theycomprise an analyzer, modifier and a meshing tool. The second partof the paper includes a demonstration and the CFD-results of anexample geometry.

SOFTWARE MODULESThe presented process can be split up into four sub-routines. The

first one is the Analyzer, which evaluates a given point cloud ofa blade. This point cloud can be provided by a structured-light3D scanner in conjunction with a photogrammetric system. Withthe Analyzer it is possible to extract the geometric informations ofthe selected blade. Additionally, the Analyzer provides the neces-sary input data for a reference-blade-model in the following subrou-tine: The Modifier. With the Modifier it is possible to manipulatethe reference geometry to simulate different deterioration effects.Thus, no physical blade is necessary to investigate different bladegeometries. The Modifier provides the geometry for the followingMesher. This subroutine generates scripts for the meshing-tool Au-togrid from NUMECA. These scripts are created and adapted to thepresent case, so that effects like bleeds and cavities can be meshedor not. The generated mesh is the input for the following CFD-calculations, done by TRACE [1] [6] [9] [10]. At the end, the CFD-results can be analyzed e.g. throttle lines or exit flows.

AnalyzerThe first sub-routine in the presented process is the Analyzer.

The Analyzer is able to evaluate the geometric properties of a 3D-point cloud or just of a 2D-profile. In the presented case, a 3D-pointcloud is given. For the analyzed HPC stages, the Analyzer ensuresthe right point cloud orientation with an integrated alignment algo-rithm. Therefore, the alignment algorithm uses the blade root toorientate the blade in space.

Fig.1 Interpolation of profile points

Now, the Analyzer places cones on the wished heights throughthe 3D-point cloud and projects the surrounding points on the cones.These cones are representing streamlines through the channel. Theextracted points form the profile, but are still in disorder and showa high inhomogeneity in their distribution. A process is necessaryto sort the points clockwise to each other. Additionally, the pro-cess ensures a maximum distance from one point to its neighbourfor a homogeneous point distribution. Is the distance higher than

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allowed, new points were fitted with an interpolation into the gap(see FIG. 1). Now, the data has the right format and point density,to start the actual analysis of the profile.

First, circles were fitted into the edges to get the leading andtrailing edge radii. It is a simplified process, because the deterio-rated geometry will not have an ideal round edge. A deeper lookon the edges will be done later in the process. There, the stretching,asymmetry and metal angle of the leading and trailing edges will becalculated. After fitting circles in the edges, the profile is grosslycut into the pressure and suction side. Following, on each point ofthe pressure side, a circle is set and enlarged until it reaches the suc-tion side (rolling-ball-method). The midpoints of the circles formthe mean line of the profile (see FIG. 2). To identify the leading andtrailing edge point, the mean line has to be extended, until it cuts theprofile at its ends. This is done by a sixth order fitting curve throughthe circle midpoints. The gradient of the curve at the leading andtrailing edge point is the metal angle at leading and trailing edge.The chord is defined as the closest connection of leading and trail-ing edge point. The angle between chord and machine axis is calledstagger angle. The distance between chord and circle-midpoints isdefined as camber and the diameter of the circles results in the thick-ness distribution. Figure 3 shows a simplified definition of some ge-ometric parameters. However, more parameters are analyzed, suchas center of gravity, edge asymmetry and stretching. Additionally,blade specific parameters like blade height can be calculated, too.

Fig.2 Forming of mean line by rolling-ball-method

Fig.3 Definition of geometric properties

At the end of the analysis, the Analyzer returns the results in anappropriate format for further statistical analysis. Furthermore, theAnalyzer provides the input data for the following Modifier. Withthe Modifier, a reference geometry will be distorted to simulate dif-ferent deterioration effects and levels. For this purpose a suitablereference geometry is necessary. Because of this, it is reasonable touse a new part as reference for following blade-modifications.

ModifierPrevious publications already addressed parameter based com-

pressor blade models (see [7]). Lange et al. developed an algo-rithm to reproduce geometric differences caused by manufacturingtolerances. In contrast, the Modifier is able to alter and distort thegeometry of a reference blade to simulate different deterioration ef-fects. Therefore, the geometry data set has to be provided by theAnalyzer, explained above. It is possible to manipulate the geo-metric properties independently or in conjunction, so each deteri-oration combination can be simulated, without having a physicalcomponent. During the airfoil modification, profiles in 5 % ductheight distances were generated and aligned together to a 3D-airfoilmodel.

The first step of the Modifier is forming the chord and turningit on the desired stagger angle. Subsecuently, the camber distribu-tion has to be distorted, to fullfill the specified requirements. Theuser can define new metal angles at leading and trailing edge, themax. camber and its position (see FIG. 4). Afterwards, the camberdistribution is added to the chord to get the new mean line. Thefinal profile is created by adding the thickness distribution to themean line. The thickness distribution can be distorted as well as thecamber distribution. Thereby, leading and trailing edge radii andthicknesses as well as maximum profile thickness and its chordwiseposition can be manipulated (see FIG. 4). Giebmanns et al. [3]showed the strong impact of edge geometry. In order to meet theserequirements, the egde geometry is defined by five parameters: Ra-dius, thickness, stretching, asymmetry and metal angle.

After finishing the 2D-profiles, the Modifier aligns each profileby a chosen alignment method (e.g. by its center of gravity and astored stacking line). At the end, a 3D-airfoil model is generatedwith evenly distributed points over the profiles and a higher reso-lution at the edges (see FIG. 5 a). Figure 5 b shows the deviationbetween the reference blade and its replica. As can be seen, mostof the airfoil has deviations below 25µm. The area averaged de-viations are 6µm. Thus, they are of the same order as measuringaccuracy of the structured-light 3D scanner.

Fig.4 Thickness and camber distribution

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(a) Output from airfoil modi-fier

(b) Deviations between reference andcomposed blade

Fig.5 Reproduced reference rotor blade

A further example for the flexibility of the presented process isshown in FIG. 6, where a FOD was reproduced. In order to inves-tigate the performance after a possible repair, a blending was done.As can be seen, a wide area in tip range was repaired by blendingthe blade. Additionally, the blade has a bump in this region, causedby changed stagger angles.

The meshing-tool Autogrid is used for the following meshing ofthe geometry. Autogrid requires airfoils, which intersect with thehub and shroud contour. So, the Modifier delivers extended airfoilsand the final blade height and, therefore, tip clearances are adjustedduring the meshing process. Additonally, geometric properties likefillets or partial gaps are included during the meshing, too.

Fig.6 Reproduced blended FOD damage on blade

MeshingThe Meshing of the HPC geometry is realized with Autogrid.

Autogrid is a semi-automatic meshing tool which can either be op-erated using a GUI or through scripts. In the presented process, theautomatic preparation of these scripts is one part. Normally, thescripts are using stored default values. If other properties are re-quired, the user is able to change some major grid properties in aGUI, for example the first cell width at walls to adjust the dimen-sionless wall distance y+. Additionally, it is possible to mesh justa single row, multiple rows or the whole HPC as well as circum-

ferential effects like cavities or bleeds. During the meshing, bladespecific parameters like gaps or fillets are also taken into account.

At the end of the process, the mesh will be prepared for the CFD-calculations. This is done by the TRACE preprocessing-tool GMC.In GMC mixing planes were set and combined with their partners,bleed massflows, rotational speeds, etc. were set. Additionally,solver settings like turbulence or transition models can be chosen.A deeper look into the simulation setup is given in the next partof the paper. There, the whole process has been executed from anexample geometry point cloud to a final CFD-calculation.

SIMULATION SETUPIn the presented test case, a HPC front stage of a civil jet engine,

consisting of rotor and stator row has been chosen. For the simula-tions, just the rotor with its geometric properties has been changedin different deterioration levels. Subsequently, these deteriorationlevels have been paired with a stator blade, representing a new part.

To determine the range of geometric changes, 120 blades of thechosen stage have been measured and analyzed. Afterwards, rep-resentative geometric properties of a blade with minimal, maximaland mean values have been generated. Of course, possible corre-lations between some parameters like edge parameters, have beentaken into consideration to achieve the most accurate result. Finally,the rotors were created by varying leading edge geometry, staggerangle, chord length, profile camber and thickness.

The variances for chosen parameters are shown in FIG. 7. Theplot shows deviations of leading edge thickness tLE and stagger an-gle λ referenced to a new blade (black vertical line). As can beseen, blademin has an approx. 20% thinner airfoil compared to thenew blade. Blademax has nearly reference thickness, except for thetip region, where its leading edge thickness is approx. 20% higher.The values of blademean are located in the middle of blademin andblademax. The stagger angle of blademin is approx. 0.5◦ smallerthan reference. In hub region blademax has a 0.25◦ higher staggerangle than the new blade and in tip region about 0.5◦. Addition-ally, blademin has sharper edges than the new blade and blademaxhas blunted edges.

Fig.7 Exemplary varied geometric properties referenced to a newblade

A false color image of blademax and blademin is presented in FIG.8. This plot shows the suction side. Red or yellow contours indi-cate a positive distance of blademax to blademin and blue contours anegative one. First of all, a clear trend from leading to trailing edgeis noticeable. This trend can be explained by the stagger angle de-viation. Because of the change of blade twist between blademax andblademin the edges have the highest distances to each other. Never-theless, the influence of changes in profile thickness can be identi-

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Fig.8 Deviations between blades with min. and max. geometricproperties

fied: The increased distance values in the tip region are caused bythe higher deviations between blademax and blademin (see FIG. 7).

Please take note that some deterioration effects, like roughnessor changing tip clearances, have not been taken into account. Therotor and stator tip clearances were adjusted to 1% channel height.Additionally, fillets have been added during the meshing.

Now, the geometries went through the meshing process. Theresult of the meshing process is a one pitch periodic mesh for rotorand stator geometries (see FIG. 9). In the CFD-calculations, theboundary layer was simulated with wall functions and no transitionmodel. The area averaged y+ was therefore set to a value below 3for the airfoil and to 10 on hub as well as shroud. With a previouslydone mesh study, the whole mesh has about 3.6 million nodes.

Fig.9 Domain setup

Realistic boundary conditions are of great importance for repre-sentative results. The chosen operating point is cruise and the cor-responding inlet distributions were extracted from a full HPC cal-culation with design blade geometry. The compressor is installedin a conventional civil jet engine with medium thrust class. Thisfull HPC calculation includes the whole compressor geometries likeHPC stages and bleed ports. On the corresponding interfaces, theradial distributions of the flow properties were extracted. Theseproperties are the total pressure pt , total temperature Tt , flow anglesα and β , Ma number, turbulent intensity Tu and turbulent lengthscale T LM. Using the boundary conditions from the full HPC cal-culation, the influence of the previous rows can be taken into ac-

count to achieve stage operating conditions as realistic as possible.Though, the gap flow of the upstream row is considered as well asthe boundary layer thickening. Using this procedure, the resultingposition of the inlet as well of the outlet corresponds the position ofthe stage interfaces inside the full HPC calculations. Therefore, theinlet and outlet is comparatively short and makes a non-reflectingintlet and outlet necessary. For the non-reflecting inlet and outletthe method of Saxer and Giles is used [12].

The following CFD-calculations were realized with TRACE. Theobjetive was to calculate the stage characteristics like work coeffi-cient ψ and pressure coefficient ε . The solver settings were sum-marized in TAB. 1.

Table 1 Boundary conditions

Setting Commentpt1(h/H), Tt1(h/H), α1(h/H), Extracted from fullβ1(h/H), Ma1(h/H), Tu1(h/H), HPC calculationsT LM1(h/H)Rotational speed n = nCruiseWalls No slip walls

(hydraulically smooth)Blade to vane interface Mixing planeTurbulence model Wilcox k-ωAnalysis type Steady stateBlade / vane mesh One pitch periodicOutlet Radial static pressure equilibirium

with non reflecting outlet

RESULTSSingle Stage Performance

The calculated throttle lines are shown in FIGS. 10 and 11. In thefollowing diagrams, the work coefficient ψ and pressure coefficientε are plotted over the flow coefficient ϕ .

The flow coefficient ϕ is defined as ratio of axial velocity Vaxover circumferential speed U :

ϕ =Vax

U(1)

The work coefficient ψ combines the total temperature rise andthe circumferential speed U :

ψ =2 · cp(Tt3 −Tt1)

U2 (2)

The pressure coefficient ε is defined as product of work coeffi-cient ψ and isentropic efficiency ηis.

ε = ψ ·ηis (3)

Thereby, the isentropic efficiency ηis can be calculated by thetotal to total pressure rise πtt

πtt =pt3

pt1(4)

and the total to total temperature rise τtt

τtt =Tt3

Tt1(5)

with following equation.

ηis =π

κ−1κ

tt −1τtt −1

(6)

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Please note, that the operating point with lowest flow coefficientdoes not represent the physical point of stall. With a steady stateCFD-calculation it is not possible to determine the exact point ofstall with its instationary behavior. The operating point with lowestflow coefficient is just the last converged solution. A further reduc-tion in mass flow did not lead to a converged solution.

Figure 10 shows the work coefficients of the simulated stage.The black vertical dotted line represents the ref. flow coefficient forthe HPC design point. First of all, it can be mentioned, that geo-metric changes caused by deterioration result in noticeable changesin stage performance. It can be seen, that blademax delivers nearlythe same work coefficient as the new blade. Both graphs are on topof each other. This can be explained by the small geometric differ-ence of both blades. The only difference is the earlier blocking ofblademax caused by the little thicker airfoil. The thicker airfoil hasa stronger acceleration and reaches the Mach Number of one overthe whole passage earlier than the new blade.

However, the situation appears to be different for blademean andblademin. Here, the work coefficients show noticeable differencesto the new blade over the whole range. This is caused by thehigher discrepancies between the geometric properties, comparedto blademax. Thereby, the work coefficients seem to be positivelyinfluenced by deterioration and are increasing. Because of the de-creasing stagger angle, the curves are shifted towards lower load-ings. For blademin this shifting leads to an earlier stall, representedby an earlier divergence of the calculation. Furthermore, blademeanand blademin have a weaker acceleration compared to the new bladeand reach choking condition at higher mass flows.

Fig.10 Work coefficients

Figure 11 presents the pressure coefficients of the simulatedstage. Similar to the work coefficients, the pressure coefficientsshow noticable changes caused by deterioration. Again, the blackvertical dotted line represents the ref. flow coefficient for the HPCdesign point. It should be remembered, that the pressure coefficientis the product of work coefficient ψ and the isentropic efficiency ηis.So, the pressure coefficient represents the efficiency of the stage. Itcan be seen, that blademax shows a decreased pressure coeffienctover the whole range. In contrast, blademean and blademin have in-creased pressure coefficients. Comparable with work coefficients,the pressure coefficients show an offset towards lower loadings withdecreasing geometric values as stagger angle. Nevertheless, peakefficiency of blademin, i.e. maximum deterioration, shows highervalues.

Fig.11 Pressure coefficients

Fig.12 Deviations between Mamin and Mamax at 95% span

To give an answer to the question why deterioration can resultin higher efficiencies, the contour plot in FIG. 12 illustrates the dif-ference between the Mach Number distributions of blademin andblademax. The contour plot shows a profile in blade tip range and,therefore, a transonic flow regime. The chosen operating point isat peak efficiency mass flow of the new blade. Because of the cho-sen rotational speed and inlet temperature, respectively, no shock ispresent. Blademin has a higher averaged deceleration than blademax(∆Ma < 0). Only near leading edge, blademin shows a higher accel-eration. The higher deceleration of blademin is in accordance withits higher work coefficient ψ . Additionally, the increased MachNumber distribution, especially in mid-passage, of blademax con-firms the prior explanation of its earlier blocking.

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Table 2 summarizes the deviations between operating points, rep-resenting respective peak efficiency, for work and pressure coeffi-cients and isentropic efficiency. The given values are referenced tothe new blade. Even though blademin has a higher value of peakefficiency than the new blade, the associated pressure coefficient ε

is lower. This can be explained by the curve shifting towards lowerloadings and, therefore, lower pressure ratios at peak efficiency. So,the product of work coefficient ψ and isentropic efficiency ηis isdecreasing.

Table 2 Analysis of changes in performance for front stage bladegeometry deviations, extracted from single stage calculations

Variant ∆ϕ ∆ψ ∆ε ∆ηis[ - ] [ % ] [ % ] [ % ]

Min 0.016 -0.61 -0.16 0.40Mean 0.005 0.64 0.68 0.03Max -0.001 0.48 -0.05 -0.45

Overall Compressor PerformanceFurther calculations shall evaluate the influence of a deteriorated

front stage for the entire compressor. Therefore, the analyzed frontstage variations, shown in the section above, have been integratedinto the full compressor model. This model is equal to the modelof boundary condition extraction and includes all compressor rows,bleed ports, etc.. Besides the front stage variations, the model con-sists of a newly blading. Because of the model dimensions, just oneoperating point for each deterioration level was calculated. This op-erating point represents cruise condition and is illustrated in FIGs.10 and 11 by the black vertical dotted line.

Table 3 summarizes the deviations of the front stage aerodynamicperformance, extracted from the full HPC model. Please remember,that just one operating point for each deterioration level has beencalculated. So, table 3 represents one outlet pressure and thereby, apractically constant massflow for each point. This is the mass flowfor the HPC design point, illustrated by the black vertical dottedline in FIGs. 10 and 11. Thus, table 3 shows the aerodynamicperformance for the front stage at design mass flow, but applied tothe full HPC model. Similiar to the trends shown in figure 10 and11, where the front stage was calculated separately, the changes ofthe front stage aerodynamic performance can be observed in the fullHPC calculation, as well.

Table 3 Analysis of changes in performance for front stage bladegeometry deviations, extracted from full HPC calculations

Variant ∆ϕ ∆ψ ∆ε ∆ηis[ - ] [ % ] [ % ] [ % ]

Min 0.001 1.55 0.64 -0.76Mean 0.000 1.08 0.62 -0.39Max -0.001 0.36 -0.09 -0.38

Table 4 summarizes the deviations of the full HPC aerodynamicperformance between the calculated deterioration levels. Eventhough only the front stage of the compressor has been systemati-cally altered, its influence on overall work coefficient ψ of the HPCcan be easily noticed. The negligible change of flow coefficient ϕ ,or massflow, indicates that the deviations are not evoked by chang-ing the throttling of the compressor. Furthermore, the compressorshows changes in efficiency: Although the work coefficient ψ is in-creasing, the pressure coefficient ε is not changing. Consequently,the isentropic efficiency ηis has to be decreased.

Table 4 Analysis of changes of overall compressor performancecaused by a varied front stage

Variant ∆ϕ ∆ψ ∆ε ∆ηis[ - ] [ % ] [ % ] [ % ]

Min 0.000 0.26 -0.01 -0.21Mean 0.000 0.14 0.00 -0.11Max 0.000 0.12 -0.01 -0.10

CONCLUSIONSIn this paper, a process for analyzing, manipulating and mesh-

ing of deteriorated compressor blades was shown and demonstratedwith an example blade geometry. The chosen example was a HPCfront stage of a modern civil jet engine. Its geometry was digitizedby a structured-light 3D scanner in conjunction with a photogram-metric system. The obtained point cloud was analyzed for its geo-metric properties, such as thickness distribution and stagger angle.The extracted information is subsequently distorted and composedto an artificially deteriorated blade. Thereby, the geometric valuesof the composed rotor blades represent typical geometric changescaused by jet engine deterioration. The next algorithm creates andprovides the scripts for the meshing tool Autogrid. Then, CFD-calculations were realized with TRACE. The complete process chaincan be briefly summarized as follows:

1. Digitized airfoils can be analyzed for their geometric proper-ties by the presented software.

2. The software is able to create any artificially deteriorated air-foils by manipulating the geometry of a reference blade.

3. A downstream process creates and provides the scripts for afully automatic meshing of the geometry.

4. The performance map is automatically calculated by TRACE.

At the end, the CFD-results have to be analyzed. In the presentedcase, three different deterioration levels have been compared to anew blading. Therefore, a single stage was calculated as well asthe entire HPC. The chosen rotational speed and entry boundaryconditions are representing cruise condition. The results of singlestage calculations can be summarized as follows:

1. Deterioration induces noticeable changes in stage perfor-mance.

2. Changing stagger angles result in a shifting of characteristiccurves.

3. Blademax has comparable geometric properties as the newblade. So, the pressure and work coefficient is equal over awide operation range. Just at low loadings the curves fan out.This can be explained by slightly increased thicknesses whichresult in an earlier blocking of the passage.

4. Blademean and blademin show an increased averaged decelera-tion, which results in higher peak efficiencies.

Additionally, the influence of a deteriorated front stage on overallHPC performance has been assessed. The shear size of the model,however, only allowed for a single operating point calculation perdeterioration variant. Therefore, the cruise condition was chosen.The results can be summarized as follows:

According to expectations, deterioration of a front stage rotorinfluences the behavior of the entire HPC. However, while the workcoefficient shows a noticeable response to the evaluated geometrychanges, their impact on pressure coefficient is negligible.

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It has to be mentioned, that some deterioration effects like rough-ness or changing tip clearances have not been regarded.

For a yet deeper understanding of the influence of blade deterio-ration on compressor performance some further actions have to bedone in future studies:

1. Further studies should also address changed roughnesses ortip clearances.

2. To fill the parameter space of geometric properties, a designof experiments should be carried out. Thereby, further geome-tries with random geometric properties could be calculated toidentify the range of variation of characteristic curves.

3. Additionally, deterioration of stator vanes should be taken intoaccount.

4. At an advanced stage, deterioration of the entire machineshould be analyzed. In doing so, a prediction of the entirejet engine could be given, depending on HPC condition.

The next step should be the design of experiments to fill theparameter space of an entire stage. Therefore, the tip clearanceshould be taken into account as well as changed stator vanes. Bythis means, the range of characteristic lines could be characterizedfor a single stage. Further studies could check if the received rangeof characteristic lines is appliable for the other stages or if the samework has to be done for every single stage.

ACKNNOWLEDGEMENTThe authors would like to thank MTU Maintenance Hannover

GmbH for funding and for allowing the publication of this work.

References[1] K. Becker, K. Heitkamp, E. Kugeler, 2010, “Recent Progress

in a Hybrid-Grid CFD Solver for Turbomachinery Flows”, Pro-ceedings of V. European Conference on Computational FluidDynamics, Lisbon, Portugal.

[2] B. Bohari, A. Sayma, 2010, “CFD Analysis of Effects of Dam-age due to Bird Strike on Fan Performance”, Asme Turbo Expo2010, Glasgow, United Kingdom.

[3] A. Giebmanns, R. Schnell, W. Steinert, A. Hergt, E. Nicke,C. Werner-Spatz, 2012, “Analyzing and Optimizing Geometri-cally Degraded Transonic Fan Blades by Means of 2D and 3DSimulations and Cascade Measurements”, Asme Turbo Expo2012, Copenhagen, Denmark.

[4] A. Kellersmann, G.Reitz, J. Friedrichs, 2014, “Numerical in-vestigations of circumferential coupled deterioration effects ofa jet engine compressor front stage compared to BLISK ge-ometry”, Proceedings of the 3rd International Conference inThrough-life Engineering Services, pp. 249-255, Cranfield,United Kingdom.

[5] J.-H. Krone, J. Friedrichs, J. Stading, 2012, “Performance studyof deterioration effects of a jet engine high pressure compressorstage”, DLRK Conference, Berlin, Germany.

[6] E. Kugeler, 2005, “Numerisches Verfahren zur genauen Anal-yse der Kuhleffektivitat filmgekuhlter Turbinenschaufeln”,PhD thesis, Ruhr-Universitat Bochum, Germany.

[7] A. Lange, K. Vogeler, V. Gummer, H. Schrapp, C. Clemen,2009, “Introduction of a Parameter based Compressor BladeModel for Considering measured Geometry Uncertaintiesin Numerical Simulation”, ASME GT2009-59937, Orlando,Florida, USA.

[8] J. Marx, J. Stading, G. Reitz, J. Friedrichs, 2013, “Investigationand Analysis of Deterioration in High Pressure Compressors”,DLRK Conference, Stuttgart, Germany.

[9] D. Nurnberger, 2004, “Implizite Zeitintegration fur die Sim-ulation von Turbomaschinenstromungen”, PhD thesis, Ruhr-Universitat Bochum, Germany.

[10] V. Marciniak, E. Kugeler, M. Franke, 2010, “Predicting Tran-sition on Low-Pressure Turbine Profiles”, Proceedings of V.European Conference on Computational Fluid Dynamics, Lis-bon, Portugal.

[11] G. Reitz, J. Friedrichs, J. Marx, J. Stading, 2014, “Per-formance Analysis of deteriorated High Pressure CompressorBlades”, ASME GT2014-25544, Dusseldorf, Germany.

[12] A. Saxer, M. B. Giles, 1993, “Quasi-three-dimensional non-reflecting boundary conditions for Euler equation calculation”,AIAA J. Prop. and Power, Vol. 9, No. 2, S. 263-271

[13] W. Tabakoff, A. N. Lakshminarasimha, M. Pasin9 1989,“Simulation of Compressor Performance Deterioration Due toErosion”, ASME Papter No. 89-GT-182, Toronto, Canada.

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