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Research Papers

Assessment and Optimization of the Aerodynamic and Acoustic Characteristics of a Counter Rotating Open Rotor

[+] Author and Article Information
R. Schnell1

 Institute of Propulsion Technology, German Aerospace Center (DLR), Linder Hoehe, 51147 Koeln, Germanyrainer.schnell@dlr.de

J. Yin

 Institute of Aerodynamics and Flow Technology, German Aerospace Center (DLR), Lilienthalplatz 7, 38108 Braunschweig, Germany

C. Voss, E. Nicke

 Institute of Propulsion Technology, German Aerospace Center (DLR), Linder Hoehe, 51147 Koeln, Germany

1

Corresponding author.

J. Turbomach 134(6), 061016 (Sep 04, 2012) (15 pages) doi:10.1115/1.4006285 History: Received January 28, 2011; Revised February 04, 2011; Published September 04, 2012; Online September 04, 2012

The present study demonstrates the aerodynamic and acoustic optimization potential of a counter rotating open rotor. The objective was to maximize the propeller efficiency at top of climb conditions and to minimize the noise emission at takeoff while fulfilling the given thrust specifications at two operating conditions (takeoff and top of climb) considered. Both objectives were successfully met by applying an efficient multi-objective optimization procedure in combination with a 3D RANS method. The acoustic evaluation was carried out with a coupled U-RANS and an analytic far field prediction method based on an integral Ffowcs Williams-Hawkings approach. This first part of the paper deals with the application of DLR’s CFD method TRACE to counter rotating open rotors. This study features the choice and placement of boundary conditions, resolution requirements, and a corresponding meshing strategy. The aerodynamic performance in terms of thrust, torque, and efficiency was evaluated based on steady state calculations with a mixing plane placed in between both rotors, which allowed for an efficient and reliable evaluation of the performance, in particular, within the automatic optimization. The aerodynamic optimization was carried by the application of AutoOpti, a multi-objective optimization procedure based on an evolutionary algorithm, which also was developed at the Institute of propulsion technology at DLR. The optimization presented in this paper features more than 1600 converged 3D steady-state CFD simulations at two operating conditions, takeoff and top of climb, respectively. In order to accelerate the optimization process, a surrogate model based on a Kriging interpolation on the response surfaces was introduced. The main constrains and regions of interest during the optimization were a given power split between the rotors at takeoff, retaining an axial outflow at the aft rotor exit at top of climb, and fulfilling the given thrust specifications at both operating conditions. Two objectives were defined: One was to maximize the (propeller) efficiency at top of climb conditions. The other objective was an acoustic criteria aiming at decreasing the rotor/rotor interaction noise at takeoff by smoothening the front rotor wakes. Approximately 100 geometric parameters were set free during the optimization to allow for a flexible definition of the 3D blade geometry in terms of rotor sweep, aft rotor clipping, hub contour as well as a flexible definition of different 2D profiles at different radial locations. The acoustic evaluation was carried out based on unsteady 3D-RANS computations with the same CFD method (TRACE) involving an efficient single-passage phase-lag approach. These unsteady results were coupled with the integral Ffowcs Williams-Hawkings method APSIM via a permeable control surface covering both rotors. The far field directivities and spectra for a linear microphone array were evaluated, here mainly at the takeoff certification point. This (still time consuming) acoustic evaluation was carried out after the automatic optimization for a few of the most promising individuals only, and results will be presented in comparison with the baseline configuration. This detailed acoustic evaluation also allowed for an assessment of the effectiveness of the acoustic cost function as introduced within the automatic optimization.

Copyright © 2012 by American Society of Mechanical Engineers
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Figures

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Figure 1

CROR baseline geometry V0 (Snecma proprietary)

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Figure 2

Automatic MO-optimization featuring steady-state RANS computations for aerodynamic performance analysis and FEM analysis; U-RANS method for aerodynamics of the acoustic near field (TRACE) and acoustic FWH-method for far field propagation (APSIM) for selected individuals

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Figure 3

Numerical setup: (1) Far field boundaries based on the prescribed ambient conditions (ps ,Ts ,Ma); (2) Giles-type nonreflecting mixing plane (steady-state) and sliding interface with phase-lagged blade row coupling; (3) and (4) Solid surfaces (rotating in the region of both rotors, stationary for the rest of the hub contour up- and downstream) with wall-function treatment for the coarse grid computations during the optimization loop (y+  < 50) and low-Reynolds formulation for the fine grid post-optimization evaluation (y+  < 5)

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Figure 4

Influence of the placement of the outer radius of the CFD computational domain on the CROR performance parameters (top of climb conditions)

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Figure 5

Validation of the CFD process – comparison with measurements taken at TsAGI facilities (rig-scale) for configuration V1.1

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Figure 6

Integration surface for the far field acoustic analysis onto which the U-RANS results were interpolated (the cylindrical part of the integration surface is located at approximately one blade height above the front rotor)

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Figure 7

Blade parameterization and free parameters of 2D construction profiles: Leading and traling edge metal angle (+/−5 deg with respect to reference), stagger angle (+/−5 deg with respect to reference) and suction side control point ySS

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Figure 8

Blade stacking by the definition of the leading and trailing edge lines (lower left) based on six 2D profile sections (upper left) resulting in the 3D blade geometry (right)

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Figure 9

Free parameters during the optimization and their corresponding bounds: hub control points and variable aft rotor clipping

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Figure 10

Isometric view of an arbitrary selection of individuals during the optimization procedure highlighting the range of possible geometric variation

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Figure 11

Pareto front from the first optimization: acoustic cost function values versus propeller efficiency; each cross (+) represents a result from a 3D-RANS analysis with two operating points T/O and ToC being considered); triangle: initial member, open circles: all individuals pareto ranked one; filled circle: selected optimized individual for further analysis

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Figure 12

Radial thrust distribution of Memb2652 from automatic optimization (a direct comparison with the baseline configuration is not possible due to confidentiality)

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Figure 13

Axial velocity at different radial positions at the front rotor exit (left, increments identical but absolute velocity levels differ between different radii) and contours of entropy (right): comparison of initial geometry with optimized Memb2652

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Figure 14

Iso-contours of surface blade static pressure at ToC conditions (suction side)

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Figure 15

Nondimensional blade surface static pressure (reference: ambient total pressure p0 ) at 50% span (left: front rotor, right: aft rotor) at ToC conditions

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Figure 16

CROR efficiency values at both operating points considered during the optimization

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Figure 17

Instantaneous contours of eddy viscosity near the hub (left) and static pressure close to the blade tip (right) at top of climb operating conditions for configuration V0 – results reconstructed from U-RANS phase-lagged single passage computations

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Figure 18

Comparison between results from a steady state computation with a mixing plane (MP) and the temporal average of the corresponding time accurate simulation (TA) – radial thrust distributions (left) and relative difference in thrust and power (reference MP results) as well as the absolute difference in propeller efficiency and the acoustic cost function (right) – all results exemplarily for V0 at top of climb conditions

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Figure 19

Blade pressure amplitudes on the aft rotor blade surface (SS) from U-RANS computations (second harmonic) - simplified blade view by x and r normalization based on blade chord and blade height

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Figure 20

Definition of directivity angles and microphone positions for the acoustic far field analysis

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Figure 21

Pressure spectra at θ = 90 deg (see also Fig. 2)

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Figure 22

Pressure spectra at θ = 140 deg (see also Fig. 2)

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Figure 23

Farfield directivity for configuration V2.0 split into contributions from the front rotor (dashed-dotted), the aft rotor (dashed) and the sum of both (solid) based on the blade pressure data in comparison with the farfield data computed based on the permeable (porous) integration surface as shown in Fig. 6 (solid line with circles)

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Figure 24

Comparison of the linear directivity in terms of the overall sound pressure level for the different configurations V0 (baseline), V1.1 (optimization reference), and Memb2652 (results from MO optimization) - microphone positions as defined in Fig. 2

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Figure 25

Overall sound pressure level (SPL) along the microphone positions as defined in Fig. 2: contributions from mainly blade row interaction (solid line) and rotor alone BPF tones (dashed line: aft rotor, dashed-dotted line: front rotor)

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Figure 26

Overall sound pressure level in terms of azimuthal directivity at an axial position in between both rotors (as defined in Fig. 2)

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