https://ntrs.nasa.gov/search.jsp?R=20060022521 2019-04-01T18:14:36+00:00Z Experimental Investigation of a 2D Supercritical Circulation-Control Airfoil Using Particle Image Velocimetry Gregory S. Jones*, Chung-Sheng Yao†, and Brian G. Allan‡ NASA Langley Research Center, Hampton, Virginia, 23681 Recent efforts in extreme short takeoff and landing aircraft configurations have renewed the interest in circulation control wing design and optimization. The key to accurately designing and optimizing these configurations rests in the modeling of the complex physics of these flows. This paper will highlight the physics of the stagnation and separation regions on two typical circulation control airfoil sections. Nomenclature A area TE trailing Edge b 2D airfoil span TI turbulence intensity c section lift coefficient T static temperature l Cµ momentum coefficient w slot width c chord α angle of attack CC Circulation Control β turbine flow meter coefficients CTOL Conventional Take Off & Landing δ jet thrust angle (ref. normal to jet exit) JET ESTOL Extreme Take Off & Landing Γ circulation GACC General Aviation Circulation Control θ jet separation angle JET h slot height at jet exit ρ density H tunnel height σ standard deviation of PIV velocity v LE leading edge l airfoil section lift Subscripts: M mach number ∞ free stream conditions m mass flow JET jet at slot exit NPR nozzle pressure ratio = P P duct duct stagnation condition 0 ∞ P pressure 0 stagnation conditions PIV Particle Image Velocimetry r trailing edge radius € U horizontal mean velocity component V vertical mean velocity component u horizontal velocity fluctuation v vertical velocity fluctuation q dynamic pressure S wing planform area SCFM standard mass flow (referenced to 14.7 psia & 72oF) * Senior Scientist, Flow Physics & Control Branch, M/S 170, and AIAA Senior Member. † Senior Scientist, Flow Physics & Control Branch, M/S 170. ‡ Research Scientist, Flow Physics & Control Branch, M/S 170, and AIAA Senior Member 1 American Institute of Aeronautics and Astronautics € I. Introduction I nterest in circulation control (CC) aerodynamics has recently increased for both military and civil applications with emphasis on providing better vehicle performance and prediction capability1. These demands are not only focused on performance and economic value, but are also related to new and stringent regulations associated with reduced airport noise and environmental issues. NASA and the FAA have made the latter issues a top priority in developing technologies required for optimization of near airport operations as described by NASA’s ESTOL program. The ESTOL vehicle goals were first formulated from an industry, academic, and government agency workshop held in Reno, Nevada, in January 2003. The purpose of this workshop was to define vehicle capabilities of interest to all partners, then to define the technical challenges that are barriers to achieving those capabilities today. The capabilities defined by this effort were based on a 50 – 150 passenger (nominally 100 passenger) aircraft. A notional concept vehicle is shown in Fig. 1. Nominal Capabilities of an ESTOL aircraft • Balanced field length of 2000 feet • Efficient cruise at Mach 0.8 • Takeoff and landing speeds less than 50 knots • Turn radius in terminal area less 0.25 nm • 1400 – 2000 mile range • Noise footprint within the airport boundary The emphasis of low speed take-off and landing on a 2000 ft. balanced field runway, shown in Fig. 2, initially identified a maximum lift of 10 while efficient cruise at Mach 0.8 required a lift to drag ratio near 25.2 Figure 1. Notional NASA ESTOL 100 passenger Simultaneous realization of all of these capabilities does vehicle with CC opportunities. not appear possible using conventional high-lift systems and prompted an interest in circulation control (CC) concepts for the ESTOL configuration. Participants at the 2004 NASA/ONR Circulation Control Workshop3 highlighted the inconsistencies of Computational Fluid Dynamics (CFD) predictions and a lack of modern experimental databases that could be used for code validation purposes. Many of the workshop participants suggested that the technology readiness level for circulation control has transitioned from basic science and technology to research and development (or applied engineering). Others said that circulation control performance cannot be reliably predicted and more basic research that focuses on the physics of Coanda surface jet separation and turbulence Figure 2. Performance benefit of technology applied modeling is needed. Both are correct. Engineers can to ESTOL type aircraft. design CC wings that typically fall into two classes of CC airfoils, either elliptic or supercritical geometries.4,5,6 However, optimizing a CC airfoil for a specific mission still requires significant experimental testing and verification.8,9,10 Development of more advanced CFD tools for improved prediction of CC airfoils would significantly reduce the aircraft design cycle time. Currently these advanced CFD tools are inconsistent and often over predict CC airfoil performance. Therefore detailed experimental data are needed to identify the physics that are being misrepresented in the codes.11,12,13 The global effects of modifying the circulation characteristics around the airfoil are captured in the integrated force, moment, and surface pressure profiles. To minimize the 3D effects on the model, a large span to chord ratio is desired. An additional technique used to minimize 3D effects removes the influence of the sidewall juncture flow through blowing or suction on the sidewalls. In addition to minimizing the 3D effects it is necessary to account for 2 American Institute of Aeronautics and Astronautics the influence of the wall interference, e.g. model blockage, and streamline curvature. This can be achieved by a large wind tunnel cross section to model frontal area ratio. It should be noted that traditional ratios are based on the physical size of the model and do not account for the pneumatic flap. Both of these problems, juncture flows and wall interference, are compounded by large streamline turning associated with super-circulation and high-lift configurations typical of circulation control.14 An alternative to experimental facility corrections is to use CFD tools that model the CC airfoil and the solid wind tunnel walls. Two-dimensional CFD analysis was used to gain a better understanding of the wind tunnel wall interference for this study. This paper will focus on the physics of high-lift CC experiments that identify Coanda separation and the associated performance of a 2D supercritical airfoil with two different Coanda surfaces as shown in Fig. 3. Insight into these results are intended to provide understanding of physics related to advanced circulation control geometries. To minimize the issues of identifying the exact Coanda separation, a Coanda flap that fixed the jet separation to a known location was tested. A second trailing edge configuration with a rounded Coanda surface allowed separation to move with varying jet mass flows. These experiments emphasize flow-field data using a 2- component Particle Image Velocimetry (PIV) system that characterized the circulation (flow turning) related to pneumatic flow control. Since the focus of this effort is to provide physics data for circulation control configurations, there was no effort to maximize the performance of either airfoil. (a) Flap Configuration (b) Circular configuration Figure 3. Comparison of flow field characteristics for two Coanda surfaces. II. Experimental Setup A. Wind tunnel and circulation control model The experimental results were obtained for the General Aviation Circulation Control (GACC) airfoil15 in the open return NASA Langley Basic Aerodynamic Research Tunnel (BART)16 shown in Fig. 4. The results described in this report are from the third entry of a test series intended to capture the flow field and the physics of two circulation control geometries, a 2% circular trailing edge and a 7% hinged CC flap, Fig. 5. The verification process of this test series has resulted in several observations that refine and improve these results. This test was conducted over a Mach number range of 0.08 to 0.1 Figure 4. Sketch and photo of GACC mounted in BART. 3 American Institute of Aeronautics and Astronautics corresponding to dynamic pressures of 10 psf and 15 psf respectively. Performance results described in Ref. 17 and 18 include lift, drag, pitching moment, yawing moment, and rolling moment obtained from a 5-component strain gage balance. Airfoil surface pressure measurements were obtained mid-span on the airfoil. 1. Jet slot height and Momentum Coefficient calculations Circulation control performance for a 2D airfoil is typically characterized by the thrust or momentum coefficient: 2 Cµ=THRUST=2hwρJET UJET (1) qS Cb ρ∞ U∞2 Cµ=THRUST=mUJET (2) € qS qS where (3) € m =ρJETUJET(h)(w) and Figure 5. Circulation control airfoil geomet€ri es having circular and flap type trailing edges.  γ−1 (4) UJET= 2γR(γT−0J1ET) 1− P0PJ∞ET γ      The sensitivity of the airfoil performance to Cµ is dependent on the jet characteristics and the airfoil geometry, particularly the Coanda surface. Inspection of Eqs. €1 and 2 highlights two approaches for obtaining Cµ. The experimental data described in this paper had jet exit conditions that ranged from Mach numbers of 0.1 to sonic conditions, but were concentrated at (Ujet/U )2 from 20 to 80, which corresponds to mass flows ranging from 0.05 ∞ lbm/sec to 0.13 lbm/sec for a nominal slot height of 0.010 inch. Figure 6 illustrates the sensitivity of the momentum coefficient and mass flow to the slot height measurement error. For example, a slot measurement error of ±0.001 inch would result in an error in mass flow of 20% at (Ujet/U )2 of 50. Using Eq. 2 simplifies the required ∞ measurements for determining Cµ and eliminates the need to measure slot height and jet density for the calculation of momentum coefficient. Slot height is a critical parameter to the airfoil setup and was given careful attention. Inserting a 0.010 inch piano wire at the slot exit and clamping it in place by pulling down on the model skin with screws was used to fix the slot to a uniform height along the span. Routine inspection of the slot revealed that the piano wire could be blown out of the slot, allowing the slot height to vary locally ±20% of the desired slot height. These piano wire standoffs were replaced when necessary and conditions were repeated. An example of missing standoffs is shown in Fig. 7. Figure 6. Momentum coefficient sensitivity to slot height and jet velocity, q=10 psf, To=72oF, chord=10.014 inch. The slot height measurements (feeler gage accuracy ±0.001 inch) highlight 4 American Institute of Aeronautics and Astronautics the slot conditions for missing standoffs at Z/C=0.65 and 0.61. The average measured slot height with all standoffs in place was 0.0091 inch. This is inconsistent with the standoff diameter of 0.010±0.0002 inch. The confidence of the slot measurement can be biased ±0.001 inch based on the inaccuracy of the measurement. 2. 3D effects 0.020 For a 2D experiment, it is assumed that the jet velocity is constant along the span. The validity of this 2D 0.015 AVERAGE SLOT HEIGHT PIV LOCATION assumption is affected by three factors; internal flow non- GHTs) 0.0091" uniformity to the slot exit, non-uniform slot height along HEIche0.010 the span, and wind tunnel wall interference effects, (e.g. OT h, in juncture region effects, and model blockage effects). The SL( slot height was fixed for both geometries at 0.010 inch, 0.005 corresponding to h/C of 0.001064 for the circular Coanda INBOARD SKIN OUTBOARD SKIN surface and 0.00100 for the CC flap Coanda surface. 0.000 Slot height variation along the span causes a non- 0.00 0.25 0.50 0.75 1.00 uniform jet exit velocity along the span. However, a slot Z/C height of 0.010±0.001 inch corresponds to the 2D plane Figure 7. Slot height variations along the span. where the PIV measurements were made. The velocity measurements were consistent with the averaged velocity calculated from the pressure ratio measured at 4 jet exit locations along the span. The 0.005 inch ID (0.010 inch OD) tubing used for these total pressure measurements were located in the jet exit and also acted as an additional standoff. 3. Flow Control System The 350-psig air delivery system used to supply the model with high volumetric flow was 20 temperature controlled to minimize the effects of density. Turbine type mass flow meters were used 15 to measure the total mass flow rate to the Coanda PIV DATA ACQUIRED IN THIS jet. These flow meters come with a manufacturer %) RANGE OF MASS FLOW specification of a 1% full-scale accuracy at standard ROR (10 LCIONRERAERCTED atmospheric conditions, SCFM. However, this ER E accuracy is based on ideal laminar flow conditions BIN 5 R that require long and straight inlet and exit TU plumbing. The system accuracy is degraded at non- 0 atmospheric conditions. An in-situ system calibration was performed for the text matrix pressure conditions. The sensitivity of the mass -5 0.00 0.05 0.10 0.15 0.20 flow system was determined, and evaluated for MASS FLOW STANDARD (lbm/sec) linearity. Errors are shown in Fig. 8 to approach 5% Figure 8. Turbine mass flow meter errors. in the range of interest when a linear fit is used. This was improved to 2% by applying a multiple non-linear regression of the type shown in Eq. (4): lbm =β0+β1x1+β2x12+β3x2+β4x22+β5x1x2 (4) sec where x =Turbine pressure and x =Turbine RPM 1 2 € 5 American Institute of Aeronautics and Astronautics B. Particle Image Velocimetry Measurements The two-component PIV system includes two 1280 x 1024 pixels CCD cameras and a pulsed laser installed on a scanning platform to measure the two dimensional flow field at multiple stations at the leading edge, trailing edge, and the upper surface of the airfoil model (Fig. 9). Each PIV camera was installed with a 50 mm macro lens which covers a field view about 150 mm x 120 mm at the test section. The camera magnification was calibrated using a grid target aligned with the laser sheet. The calibration accuracy of the measurement volume dimension was within 0.1 % or ± 1 pixel over 1000 pixels. The double-pulsed Nd-Yag laser, running at 10 Hz and 100 mJ energy output, projected a light Figure 9. Sketch of PIV system setup. sheet between 2.5 to 3.0 mm thick and of 300 mm wide to illuminate the measurement area covered by two PIV cameras mounted in tandem. The test section was seeded by smoke particles generated from a smoke generator using commercial smoke fluids. Particle sizes were measured to be between 0.7 ~ 1.0 µm. The interrogation resolution of the PIV measurement volume was set between 28 to 32 pixels corresponding to about 3.2 mm in physical dimension at the measurement area. Velocity fields were interrogated over a mesh of 100 x 80 grids, carrying about 50% overlapping of the individual grid volume. The near surface PIV measurements were limited due to a lack of seeding and/or high reflections near the surface. Flow-field statistics, including mean and variance were computed based on 400 PIV samples. Figure 10 shows an example of the convergence of the estimation of the means and second order moments at the location of peak Figure 10. Convergence of statistics estimations based on 400 PIV samples. 6 American Institute of Aeronautics and Astronautics fluctuation in the wake with blowing of Cµ=0.016. The uncertainties of the mean velocity estimation are within 2.5%, based on σ /N0.5, σ N N being the standard deviation of the velocity component. These uncertainties include, but are not limited to, errors associated with interrogation techniques, pixel-locking, displacement gradients, and background noise.19,20 The seeding particles coated the optical window at the juncture of the model and window. The rate of contamination was dependent on the blowing condition, i.e., higher blowing conditions resulted in more window contamination therefore more frequent window cleaning. An example of measurement repeatability is highlighted by the PIV data shown in Fig. 11. The differences in the jet region are related to the errors associated with resetting the mass flow conditions after a shutdown and restart of the experiment. III. Data and Analysis There are two distinct flow control regimes that define circulation control as a function of blowing.1,3 These distinct regimes are Figure 11. Comparison U-component commonly referred to as separation control and super-circulation velocity profiles of repeat tests at three control and exhibit different global efficiencies as determined by different X/C stations. change in unit lift due to change in unit blowing. The physical description of the efficiencies of these regimes is demonstrated by the relationship of the jet separation location on the trailing edge surface and the interaction of the jet with the on-coming flow. As the jet separation location moves around the Coanda trailing edge surface, the leading edge stagnation region moves aft and the effective aft stagnation moves forward, increasing the circulation and lift around the airfoil. Circulation affects lift, drag, and pitching moment, yielding performance levels consistent with ESTOL requirements. The transition from one regime to another is not always clearly identified and is dependant on the sharpness of the trailing edge. A major roadblock to predicting the performance of circulation control geometries is to accurately predict the separation location of the jet on the trailing edge surface. The following sections highlight two geometries, a Coanda flap trailing edge and a Coanda circular trailing edge. A. Circulation Control Flap Geometry 1. PIV data The global effects of circulation control are characterized by the streamlines around the entire airfoil. The PIV data were acquired in sections that were separated in time by as much as several weeks. The data for a given section or measurement location could take as long as 20 minutes to acquire and store. Wind tunnel and jet conditions varied less than 1% for this 20-minute period. PIV measurements were obtained for many blowing conditions at a fixed location. Upon completion of the blowing matrix, the measurement volume was moved to a different location, and then the blowing matrix was repeated. This process occurred over a several weeks. During this period, the wind tunnel and jet conditions could vary up to ±2%. These variations are observed as apparent discontinuities in streamlines, turbulence quantities, etc., when combining the different PIV data sets. This is most evident at the boundaries of the different measurement sections. Instead of averaging the jet momentum coefficients for the composite PIV data, it was determined to report only the jet characteristics of the PIV sector that captured the flow closest to the jet exit and Coanda surface. Figure 12 shows the lift performance of the CC flap geometry with corresponding PIV data. The boundaries of separation control and super-circulation control are historically based on the change in lift efficiency as a function of momentum coefficient. The transition of separation control to super-circulation control is difficult to quantify with this approach. Results of this experiment will refine this approach by identifying the end of the separation control regime to the jet separation located at the most aft portion of the CC flap and correlating it to the performance of the airfoil. A series of composite of PIV mean velocity flow fields are shown in Fig. 13 and identifies the end of separation control for this configuration to be at a Cµ of 0.029. 7 American Institute of Aeronautics and Astronautics 5.00 4.00 Re=5.69 x 105 SUPEERF-FCIICRICENUCLAYTION (OPEN) SEPARATION CONTROL EFFICIENCY 3.00 c l Re=4.65 x 105 2.00 (SOLID) REF PIV 1.00 SEPARATION SUPER-CIRCULATION CONTROL CONTROL 0.00 0.00 0.05 0.10 0.15 0.20 0.25 Cµ Figure 12. Lift performance of the CC flap geometry, identifying corresponding PIV data, α=0o. PIV measurements near the trailing edge highlight the transition from separation control to super-circulation control as shown in Fig. 14. The jet details near the surface were limited due to insufficient particle seeding in the jet and/or high reflections near the surface. The velocity ratio displayed is based on the magnitude of the measured mean PIV U-component and V-component and the measured wind tunnel free-stream velocity as defined by Eq. 5. |U | U2+V2 (5) = U U ∞ ∞ As the blowing is increased the separated flow is entrained and mixed with the jet (separation control) as shown in Fig. 14a and 14b. This continues until the €je t separation is extended to the most aft location on the flap, Fig. 14c. The streamlines continue to turn as the jet penetrates the lower flow field (super-circulation control) shown in Fig. 14d and 14e. The conditions described here are further illustrated by the comparison of sectional lift coefficient as a function of blowing coefficient in Fig. 12. The description based on the PIV flow field data combined with the lift curve confirm the higher efficiency of the blowing in the separation control regime and the lower blowing efficiency in the super-circulation regime. Another approach to compare the efficiency of the CC system throughout the range of blowing coefficients is to consider the unsteady quantities of the velocity components. To do this comparison, a measure of the turbulence intensity is calculated based on the magnitude of the standard deviation of the measured PIV U-component and V- component and the measured wind tunnel free-stream velocity and based on Eq. 6. u2+v2 (6) TI= U ∞ Turbulence characteristics shown in Fig. 15 and 16 highlight the bound region of the jet as it propagates through the near field wake. The magnitude of the turbul€e nce intensity in the wake region decreased as blowing is increased in the separation control regime (Fig. 15a and 15b). The turbulence intensity and associated Reynolds shear stress throughout the flow field is minimized at the condition that corresponds to the end of separation control or as the jet separation location has just reached the most aft region of the flap, Fig. 15c and 16c. The turbulence intensity corresponding to the jet begins to increase again as the blowing is increased in the super-circulation regime, Fig. 15d and 15e. The increase in unsteady quantities shown in the PIV flow field data is correlated to a decrease in circulation efficiency with respect to blowing shown in Fig. 12. Additionally, a large turbulent region appears approximately 1.4 chord lengths downstream of the trailing edge and can be seen in both the turbulence and Reynolds stress data shown in Fig. 15 and 16. This is possibly related to a far field coherent shear layer beginning to form. 8 American Institute of Aeronautics and Astronautics (a) Cµ=0.000 No Blowing (b) Cµ=0.003 (separation control) (c) Cµ=0.029 (End of separation control) (d) Cµ=0.084 (super-circulation control) (e) Cµ=0.158 (super-circulation control) Figure 13. PIV streamlines and velocity magnitude for the GACC airfoil with a circulation control flap, X/C =0.92, δ =40o, h/C=0.0010 and AOA=0.0 degrees. JET EXIT FLAP 9 American Institute of Aeronautics and Astronautics (a) No Blowing (b) Cµ=0.003 c) Cµ=0.029 (End of separation control) (d) Cµ=0.084 (e) Cµ=0.158 Figure 14. Streamlines and velocity magnitude in near field wake of circulation control flap for varying mass flow, X/C =0.92, δ =40o, h/C=0.0010 and AOA=0.0 degrees. JET EXIT FLAP 10 American Institute of Aeronautics and Astronautics