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Experimental and numerical investigation of a counter rotating open rotor flow field

Eric W.M. Roosenboom*, Andreas Schröder†, Reinhard Geisler‡, Dieter Pallek§ and Janos Agocs** DLR, German Aerospace Center, 37073 Göttingen, Germany

Arne Stürmer†† and Carlos Omar Marquez Gutierrez ‡‡ DLR, German Aerospace Center, 38108 Braunschweig, Germany

and

Klaus-Peter Neitzke§§ AIRBUS Operations GmbH, 28199 Bremen, Germany

Currently counter rotating open rotor (CROR) propulsion systems are again considered as viable alternatives to conventional propulsion systems. This paper contributes to the resurgence of CROR concepts and contains details of an experimental and numerical concept study on a generic CROR model. This model has 10 front blades and 8 aft blades, with blade design similar to modern propellers for high disk loadings. Recent progress in experimental and numerical techniques enables new insight in the complex flow phenomena of multiple vortex structures. Stereoscopic Particle Image Velocimetry (SPIV) and unsteady Reynolds-averaged Navier Stokes (uRANS) have been applied for the flow field investigation behind a counter rotating open rotor (CROR) model. Of particular interest is the validation of numerical codes as well as a dedicated recording of the phase delays to determine the phase positions of both propellers at the experimental investigation of the flow field.

Nomenclature x = free stream flow direction y = horizontal direction in wt cross-plane z = vertical direction in wt cross-plane u = velocity component in mean flow direction v = velocity component in y- direction w = velocity component in z- direction BA = aft rotor blade passing frequency BF = front rotor blade passing frequency CF = blade loading coefficient r = radial position R = rotor radius U∞ = freestream velocity ω = vorticity

* Research Scientist, Experimental Methods, Institute of Aerodynamics and Flow Technology, Bunsenstr. 10; eric.roosenboom@dlr.de. AIAA Senior member. † Research Scientist, Experimental Methods, Institute of Aerodynamics and Flow Technology, Bunsenstr. 10. ‡ Research Scientist, Experimental Methods, Institute of Aerodynamics and Flow Technology, Bunsenstr. 10. § Research Scientist, Experimental Methods, Institute of Aerodynamics and Flow Technology, Bunsenstr. 10. ** Research Engineer, Experimental Methods, Institute of Aerodynamics and Flow Technology, Bunsenstr. 10. †† Research Scientist, Transport Aircraft, Institute of Aerodynamics and Flow Technology, Lilienthalplatz 7. ‡‡ Research Scientist, Transport Aircraft, Institute of Aerodynamics and Flow Technology, Lilienthalplatz 7. §§ Test Engineer, Experimental Aerodynamics Department, Airbus-Allee 1.

29th AIAA Applied Aerodynamics Conference27 - 30 June 2011, Honolulu, Hawaii

AIAA 2011-3184

Copyright © 2011 by Airbus SAS and DLR - German Aerospace Center. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.

I. Introduction ESEARCH for the investigation of open rotor concepts has become again an active topic of research1 due to increased oil prices and the need for more fuel efficient propulsive systems. Decades ago counter-rotating open

rotors (CROR) were mentioned as viable competitors for turbofan aircraft2. The combination of the fuel efficiency requirements and the ongoing technical developments has lead to the revival of the CROR propulsion. The inherent complexity of such systems is what put the further development of those systems to a halt. In particular aerodynamic phenomena as fluid-structure interaction, blade-to-blade interactions, and sound generation are key issues to be addressed and solved for a successful implementation of CROR propulsion systems. Part of the aerodynamic phenomena can be addressed with advanced experimental and numerical techniques. Experimental techniques such as Particle Image Velocimetry (PIV) enable detailed understanding of complex flow fields3. The last few years PIV has been successfully applied in various propeller experiments4-6 dedicated for the understanding of the complex vortex structures at high lift conditions and at propeller thrust reverse. The most compelling aspect of PIV is its non-intrusive whole field aspect, coupled with the ability to synchronize the measurements with specific propeller blade phase positions makes it an indispensable tool for CROR investigations. The Background Oriented Schlieren (BOS) technique has also been applied for the investigation of the propeller slipstream7. Numerical techniques have been developed for the advancement of the understanding of propeller installation effects. The unsteady Reynolds-Averaged Navier-Stokes (uRANS) code from DLR, the DLR TAU-code, has been used with the Chimera technique for the unsteady numerical analysis of propeller systems. The validation of DLR TAU computations using PIV data has been performed for a dedicated propeller configuration8. Recent numerical developments are already progressing for the determination of complex flow field and aeroacoustic interactions at CROR configurations9. The limited availability of available literature as well as the inherent complexity of a counter rotating rotor requires further dedicated analysis for the understanding of various flow phenomena. In addition, while fully resolved Direct Numerical Simulations (DNS) on complex configurations are not yet available10, engineering practice to date still relies on the Reynolds-Averaged Navier-Stokes (RANS) simulations. In order to determine the requirements for the closure of the turbulence models included in RANS simulations dedicated experiments are necessary. Previously our experience in numerical validation of the DLR TAU code for propeller flow with PIV measurements8 indicated that the vortical systems obtained with uRANS were influenced by numerical dissipation. The focus of the current paper is the ongoing development and improvement of stereoscopic Particle Image Velocimetry techniques and unsteady Reynolds-averaged Navier-Stokes calculations with respect to CROR configurations.

R

II. Details of the Experimental Set-up

A. Wind tunnel model The present collaborative experimental and wind tunnel test investigation was performed for a generic wind

tunnel model scale isolated Contra Rotating Open Rotor (CROR) configuration. The tested turbine powered model was tested utilizing an aft mounted single sting. It is representative of a pusher CROR propulsion system and is equipped with 10 blades on the front and 8 blades on the aft rotor, where rotor diameters are identical. Specific attention was placed on matching the flow conditions of the wind tunnel test and the CFD simulation, with the focus in the present paper being an axial flow case at low speed flight conditions. The rotational speeds were set to be identical for both rotors in the tests and in the CFD simulations.

B. Triggering using propeller signals Of particular relevance for acoustics and fluid-interactional behavior in a CROR configuration is the blade-to-

blade interaction. So the interaction of both CROR slipstream vortices has to be determined in accordance to the specific blade phase positions. For PIV applications to propeller research the ability to trigger on specific phase positions allows to identify quasi-time-resolved propeller flow phenomena6,11. However, the front and aft propellers are uncoupled on the wind tunnel model which complicates the determination of the phase-positions of both propellers as well as the triggering of the laser and cameras with respect to propeller positions. Due to the uncoupled nature it has been decided to use only the front propeller as a trigger signal and to record all phases and periods of the second propeller and rearrange in a post-processing step. The triggering is performed according to figure 1. A custom-made LabVIEW program has been designed for the control and monitoring of the trigger signals and the data flow. The principal signals and routing are visualized in figure 2. The propeller signals (1 per revolution) are fed into a Schmitt trigger box which turns the signal into a PIV-useable signal of 5V amplitude with a rising edge. The trigger signal is sent to the sequencer12 for the control of the laser pulses. Both propeller signals are then recorded by a data acquisition system (National Instruments NI-DAQ control boards).

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Phase Setting, Sequencer

Period 1

Period 2

Phase 1

Phase 2(variable)

Camera / Laser

Propeller 1

Propeller 2

Figure 1. PIV triggering and phase recording.

The main function of the control board is to record the phase and periods of the respective propeller signals as well as providing the appropriate camera trigger signals. Additionally, the number of pulses are counted and controlled. Also the directory and file tree for the measurement is predefined by the LabVIEW program. The timestamps of the phases and delays are stored in a file with the same numbering as for the instantaneous PIV snapshots. One of the main benefits of the control board is that it allows a quasi-automatic work-flow during the measurement campaign. An additional PC is connected to the system for intervention and manual control over the process.

The phase position of the front propeller has been increased in steps of 6 deg in order to obtain single blade to blade phase orientations. This was accomplished by adjusting the PIV sequence generator with appropriate phase delays. At each of the PIV measurements at a distinct phase orientation 500 instantaneous PIV snapshots have been made. As the phase delays and periods for each of the instantaneous PIV snapshots have been recorded, the PIV flow fields could then be sorted, during post-processing, in phase bins of 3 degrees (in terms of the aft propeller). So, the results of PIV experiment are triggered with respect to phase-position of the front propeller and subsequently phase-arranged by the information in the log-files with respect to the aft propeller. Hence it was possible to achieve a pseudo time resolved experimental determination of the CROR vortex systems, while all instantaneous velocity vector fields within each 3 degree phase bin achieved by stereo PIV have been averaged.

Figure 2. Functional description of trigger routing.

Two seeding generators, built according to a DLR design, are placed at the wind tunnel intake and are able to seed the test section homogenously. The seeding particles are DEHS (Di-2-Ethylhexyl-Sebacat) droplets. Each

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generator incorporated 5 Laskin nozzles, each with 12 holes per nozzle, being immersed in the DEHS. Compressed air was blown through the Laskin nozzles at ~ 1.2 bar producing a mist of particles in the space above the liquid. The size distribution of the particles is approximately bell-shaped, with a modal diameter slightly bigger than 1 μm. An Innolas Spitlight 1000 laser with a nominal output of 500 mJ per pulse was used for the generation of the laser light sheet (figure 3).

Two PCO.2000 scientific CCD cameras (2048 x 2048 pixel) have been used in a stereoscopic viewing arrangement. An overview of the cameras, white encircled, in the wind tunnel is given in figure 4. The upper camera is placed at a shallow angle to the measurement, while the lower camera has a larger angle towards the laser light sheet plane. Lenses with a focal length of 60 mm are used (yielding a measurement area of about 285 by 190 mm2) with the f-numbers set to 4. Both cameras are mounted on a 2-axis Scheimpflug adapter allowing the camera body and CCD array to be rotated about an axis normal to the lens axis. This is needed in order to fulfill the Scheimpflug-condition, i.e. the correction of focus due to a perspective view angle.

The resulting recorded particle images have been analyzed using PIVview software executing an iterative multi-grid image deformation scheme and a Gaussian peak fit algorithm with Whittaker reconstruction by using the settings listed in table 1.

Figure 3. Laser light sheet in wind tunnel. Figure 4. PIV cameras attached to wind tunnel.

Lower PIV camera

Upper PIV camera

Table 1. PIV Multigrid interrogation with image deformation settings.

PIV Evaluation setting Value

Spatial resolution [pixel x pixel] 24 x 24 Stepsize [pixel x pixel] 6 x 6 Spatial resolution [mm x mm] 3.33 x 3.33 Stepsize [mm x mm] 0.83 x 0.83 Final resolution [mm x mm] 0.83 x 0.83 Mapped field of view [mm x mm] 287 x 191 Δt [μs] 25 Nr. of vectors (per image) 345 x 230

III. Details of the Numerical Analysis The CFD computations are performed using the DLR TAU-code13,14, an unstructured finite-volume vertex-based

CFD solver developed by DLR. For the simulations described here, spatial discretization of the convective fluxes is done using a second order central differencing scheme with scalar dissipation while the viscous fluxes are discretized with central differences. Turbulence in these fully turbulent simulations is modeled with the 1-equation model of Spalart-Allmaras as modified by Edwards15,16. The well-established dual time approach is used in the DLR TAU-code to compute unsteady flows17. For convergence acceleration a 3v-multigrid cycle is employed along with a 3-stage Runge-Kutta scheme with local time-stepping in the pseudo time of the dual time method. In order to simulate the relative motion of the rotors use is made of the codes Chimera capability as well as the implemented

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motion libraries. The simulations were performed for a geometry approximating the wind-tunnel setup without actually including those components of the test setup which were believed to have no impact on the rotor performance as well as the flow field in their direct vicinity. Thus the sting was simplified to an axis symmetric body extending well aft of the rear rotor while the strut on which the CROR was mounted in the wind tunnel was omitted.

a) Periodic mesh for a single blade passage b) Completed full annulus front rotor mesh Figure 5. Structured ICEM Hexa mesh for the rotating parts of the CROR test rig.

The accuracy of solutions obtained through CFD is highly dependent on the density and quality of the

computational grids used. The adopted approach in terms of mesh generation is based on and exploits the DLR TAU-Codes Chimera capabilities. Drawing on past experience of propeller and CROR simulations, both block-structured grids generated using the ICEMCFD Hexa as well as hybrid/unstructured grids created with the CentaurSoft Centaur mesh generation software suites were used.

All rotor meshes are structured meshes, which were generated using the ANSYS ICEM CFD Hexa mesh generation software. The periodic nature of the geometry was exploited, and a mesh was generated for a single blade passage and subsequently completed to the full annulus, as shown in figure 5. This approach ensures an identical spatial resolution of the mesh for all blades of a rotor and thus greatly enhances the achievement of a periodic CFD result. A c-mesh topology enclosing the blade was used to improve blade wake and tip vortex resolution and all surfaces were gridded to obtain a proper resolution of the boundary layers. Due to the important consequences of the aerodynamic interactions between the front and aft rotor on both performance and noise emissions, the rotor mesh generation process was a primary focus in this investigation. The grid block for the sting was created using the CentaurSoft Centaur mesh generation software. A total of 25 hexahedral or prismatic layers are used on all surfaces, with appropriate settings for the initial cell and overall stack height to obtain an adequate resolution of the boundary layer in the simulations. Refined mesh regions are set in the rotor in- and outflow as well as at the Chimera boundaries to ensure the element sizes are of the same size as in the overlapping grid blocks. The complete 3-block mesh for the isolated CROR configuration consists of 46.664.079 nodes.

The simulations were performed based on experience gained in a number of previous similar investigations18,19 and were run on 256 processors of DLRs C2A2S2E2-cluster. A periodic solution for the CROR flow field was obtained after 6 rotor revolutions were computed, with all subsequent results drawn from a post-processing of data from this final rotation. Total runtime for the CFD simulation was just under 3 weeks.

IV. Results Results of both methods and a comparison are presented in the following. Figure 6 shows a phase locked and bin

sorted and averaged three-component (3C) velocity vector field obtained during the measurements by stereo PIV. The path of the tip vortices is clearly visible for both propellers by the white areas of vorticity contours. Behind the aft propeller the upper row of vortices emanate from the front propeller, the lower row stem from the aft propeller. Clearly the shear lines of each blade passage are visible in the slipstream as well as their deformation due to flow

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acceleration with its maximum at ~ 0.5 R. Of particular interest will be the progression and path of the front and aft vortices, these are measured for various phase orientations of the front propeller and sorted in 3 degree bins as discussed in Section II.B.

Figure 6. Phase locked and bin sorted 3C-velocity vector field (PIV) for one phase relation of both blades (u- velocity color coded, y-vorticity black-white coded).

CROR propulsion systems derive their superior efficiency from the reduction of the front rotor slipstream residual swirl by the contra-rotating aft rotor, which at the design point should lead to essentially axial acceleration of the flow downstream of the second rotor. As shown in the CFD visualization of the vorticity contours plotted in figure 7, the downside of this is the strongly perturbed inflow resulting for the aft rotor, where the blades are periodically affected by both the blade wake and tip vortices of the front rotor. Thus, pronounced unsteady loadings occur, which result in both vibrations as well as additional noise emissions, the latter being a primary concern for the development of a viable CROR propulsion system for application to civil transport aircraft. The determination of unsteady blade loadings is difficult to assess experimentally, and can only be derived from CFD calculations. These unsteady blade loadings are plotted in figure 8a, which shows the front and aft rotor blade loading coefficient development during on full rotor revolution as blue and red lines respectively.

Figure 7. CFD visualization of the vortical structures driving rotor-rotor interactions.

Both rotors are seen to have a constant mean value of the blade loadings with very notable unsteady but periodic fluctuations linked to the blade-blade interactions. For the front rotor, the unsteady loadings are a result of the aft blade potential flowfield, which have an effect primarily on the pressure sides of the blades. A much stronger oscillation is seen in the aft blade loadings, which are caused by the impingement of the front blade wakes and tip

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vortices. Figure 8b presents a spectral analysis of these loading oscillations as a function of the so-called shaft-order, which is a frequency based on the rotational speed of the rotors. For each rotor, the dominant unsteady loadings occur at twice the blade passing frequency of the respective other rotor, i.e. at 2*BA (shaft order 16) for the front and 2*BF (shaft order 20) for the aft rotor. This is naturally a consequence of the twice-per-revolution interactions of each blade of one rotor with each blade of the other rotor – once on the downward and once on the upward sweep for example. Higher harmonics of these fundamental frequencies are also evident. The spectral analysis clearly shows that the aft rotor is subject to a significantly greater unsteady loading than is the front rotor. Therefore, in order to address the issues of noise and vibrations for CROR propulsion systems, a proper capturing of the front rotor blade wakes and tip vortices in their interaction with the aft rotor is an essential requirement for any CFD analysis.

a) Blade total loading coefficient development during a full rotation

b) Spectral analysis of the blade loading oscillations

Figure 8. Unsteady loadings of the front (blue) and aft (red) rotor blades due to mutual rotor-rotor interactions.

a) Normalized absolute velocity contours b) Vorticity contours

Figure 9. Comparison of selected instantaneous PIV (top) and CFD (bottom) results.

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Figure 9 shows instantaneous contour plots of the unsteady experimental and numerical results in terms of normalized absolute velocity magnitudes as well as normalized vorticity. In each figure, the top half shows the PIV measurements, while the corresponding CFD results are shown in the bottom half.

The absolute velocity contours in figure 9a, normalized with the freestream velocity, show a favorable agreement between the experimental and numerical results. The acceleration of the flow by the front rotor as well as the further subsequent increase in the velocity magnitude aft of the second rotor is clearly evident in both results. Generally however, the CFD results show slightly higher velocities in the rotor slipstream than found in the PIV data set. A possible explanation for this could lie in slight differences in the rotor operating points in terms of rotational speeds and blade pitch settings, which were set to the nominal values in the TAU simulations but can of course show small deviations in the wind tunnel test. For the latter aspect an additional cause could be blade flexibility. In the CFD simulation the blades were treated as rigid, i.e. no fluid-structure coupling was employed, nor was the blade shape modified to account for expected blade deformation. This could account for a small difference in effect blade pitch angles and thus lead to the increases in the slipstream velocities in the CFD simulation.

The vorticity contours in figure 9b show a very good agreement of the simulation and PIV results, in particular in the direct vicinity of the rotors, where the greatest focus was placed in the mesh generation process for the TAU simulations. Tip vortex characteristics and trajectories are well matched, as are the interactions of the front and aft blade vortices downstream of the rear rotor. However, the CFD mesh coarsens with increasing axial distance from the rotors, and thus the vortices are seen to dissipate more rapidly than was measured in the wind tunnel.

a) Blade wake and tip vortex vorticity contours b) Front and aft blade tip vortex development at axial

positions of x/R=0.27 and 0.53 Figure 10. Comparison of the experimentally and numerically determined tip vortex characteristics.

In order to investigate in detail the important interaction of the front rotor blade tip vortex with the aft rotor, figure 10 plots a comparison of the non-dimensional vorticity contours at one instant in time. In figure 10a, the CFD results are shown as the shaded contours, while the PIV results are superimposed as contour lines. The selected instantaneous snapshot shows both a front blade tip vortex prior to its interaction with the aft rotor as well as after it has passed through it and interacts with the tip vortex of an aft blade. The general characteristics are in good agreement in both results. A slight offset in radial position is visible between the computed and the measured tip vortices, with the numerical results showing a slightly more inboard location, indicating that the slipstream contraction, and thus blade loading, is higher than in the experimental results. This is consistent with the observed slightly higher absolute velocity magnitudes in the CFD simulations and could again be caused by small deviations in the rotor operating point, in particular a small difference in blade pitch angle due to perhaps blade deformation in the wind tunnel test. This could also explain the more pronounced blade wakes found in the CFD results, which are again an indication of higher blade loading versus the experimental results.

A quantitative comparison of the tip vortex development is plotted in figure 10b, which shows the non-dimensionalized vorticity distributions at axial locations that correspond to a cut through the vortex cores found in

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figure 10a. The PIV results are shown as black lines, while the CFD results are plotted in red. Corresponding to figure 10a, the solid lines show a cut through the front blade vortex core prior to its interaction with the aft rotor at an axial location of x/R = 0.27 aft of the front rotor plane of rotation, while the dash-dotted lines show the cut through the front and aft blade vortices downstream of the rear rotor at x/R = 0.53. Apart from the approximately 1% difference in radial location, the agreement between the numerical and experimental results is excellent for the x/R = 0.27 position. Both vortex sizes as well as peak vorticity levels are in very good agreement. For the downstream location, more notable differences are found. Here the CFD results show a much higher peak vorticity level for the aft blade vortex, while the front blade vortex is more strongly dissipated. These two effects could in fact be linked and again a result of a potentially more highly loaded blade in the rigid-body CFD simulation. Naturally, the inherent numerical dissipation will certainly also have an impact on a more rapid dissipation of the vortical structures in the CFD simulation and could have contributed to the reduction in front blade tip vortex strength at this location.

Nevertheless, the favorable agreement between the PIV and CFD results, in particular in terms of the front rotor tip vortex development through its interaction with the aft rotor is an encouraging sign that the numerical simulations are in fact a useful tool to investigate in detail the challenging aspects of blade-blade interactions and their influence on the CRORs aerodynamic and aeroacoustic performance.

V. Conclusions A collaborative experimental and numerical investigation of the complex aerodynamic interactions between

rotors of a contra-rotating open rotor (CROR) turbine powered simulator test rig was conducted, utilizing DLR’s stereoscopic Particle Image Velocimetry (PIV) methods and TAU uRANS CFD solver respectively. The individual methods serve an important purpose in helping to improve understanding of the complex flow physics for this novel type of propulsion system and can help to address remaining challenges in terms of the noise emissions which need to be addressed prior to development of the CROR as an engine for future civil transport aircraft. By using the synergetic effect of experimental and numerical methods even more purpose can be reached of addressing the unsteady blade loading calculations with experimentally obtained velocity (and vorticity) field information, as well as the important aspect of validating the numerical calculations with experimental data.

High quality instantaneous 3C velocity vector fields have been achieved by means of stereo PIV within this experimental wind tunnel investigation of a CROR configuration including the slipstream flow. The application of a software controlled triggering scheme enabled a combined phase locking, recording and sorting method for the phase positions of both uncoupled blades with respect to the PIV data. Thus a quasi-time resolved reconstruction of the phase series of velocity vector fields was possible. The unsteady CFD simulations with the TAU-code benefit greatly from the validation opportunities presented by the availability of the PIV data. Generally, the agreement between the experimental and numerical results was quite favorable, showing a similar development of the rotor slipstream as well as the blade tip vortex trajectories and characteristics. Naturally, numerical dissipation and mesh density are responsible for some of the premature decay in the vortical structures that was found downstream of the aft rotor, but many of the slight differences indicate that perhaps slight differences in the rotor operating point and the impact of blade deformation under load – not accounted for in the simulations – are important considerations for the comparison. Thus the availability of a comprehensive dataset including force balance measurements as well as blade deformation assessments would be a great benefit in truly determining the proper matching of the simulated and the tested flow and model operating conditions.

A dedicated mesh-refinement study as well as an investigation of the turbulence model impact on blade wake and tip vortex development is certainly one of the planned future activities to further improve the quality of the results achieved in the uRANS simulations.

Acknowledgments The authors greatly acknowledge Airbus for providing support during the experiments and numerical analysis.

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