Correlations Between Near Wake Velocity Fluctuations and Aerodynamic Efficiency for the SD7003 Airfoil

The correlation in turbulent properties between the near wake, far wake and aerodynamic efficiency has not been explored so far. Overall, the goal of this experimental investigation is to gain insight into the trends of the mean and fluctuating flow quantities in the wake of an airfoil and determine if a correlation exists with maximum aerodynamic efficiency, (L/D)Max. Some of the mean flow quantities considered in this study are velocity components and vorticity. The fluctuating quantities explored in this investigation are root-mean-square velocities, Reynolds shear stress, turbulent kinetic energy, and turbulent production and dissipation. Inspiration for this research stems from previous work which identified a correlation between the mean and fluctuating flow properties with the drag coefficient and lift-to-drag ratio. However, this trend was found in the self-preserved wake, 10 chords downstream, where turbulent production is equal to dissipation. As a result, the mean and fluctuating flow properties remain the same from point to point in this region. This research examines the properties in the near wake, at the trailing edge, where production is expected to be higher than dissipation. In order to identify additional correlations between the near and far wake properties, as well as aerodynamic efficiency, the same airfoil and test facility from the far wake experiments were used in this study. Time Resolved Particle Image Velocimetry (PIV) was performed in the near wake of a wall-to-wall SD7003 wing for angles of attack (AoA) ranging from -2 to 8 degrees at the AFRL’s Horizontal Free-Surface Water Tunnel (HFWT) at a Reynolds number of ~68,000. Since water tunnels have a relatively high turbulence intensity, a detailed analysis of the wake was performed using various filtering techniques to quantify and correct the effect of the water tunnel turbulent intensity on the PIV data. Three different subtraction methods – Distortion Field, Mean, and RMS Subtraction – were studied in an attempt to remove the effects of freestream turbulence from the PIV data. Following the subtraction investigation, two filtering techniques, 3-Sigma and Vector Length Cutoff filters, were examined. Filters were studied due to the PIV time delay being tuned to the wake, which resulted in good correlations in the wake, compared to poor correlations in the freestream region.Results from the SD7003 near wake were split into three major sections: mean properties, fluctuating quantities, and some turbulent kinetic energy (TKE) budget components. Three distinct zones (groupings of similar slope) were seen in the momentum deficit, which suggest certain angle of attack ranges have different wake signatures. The momentum deficit in the near wake was found to match the trends in drag coefficient, aerodynamic efficiency, and far wake streamwise velocity: high gradient from 6° to 8° and decrease in magnitude around (L/D)Max. These trends and groupings persisted with the near wake vorticity, and the groupings were also seen in the V-velocity. The evolution of vorticity with respect to time was also examined. Strong vortex shedding was found at 0° angle of attack and also appeared, albeit with less strength, at -2° and 1° angle of attack. Beyond that angle of attack, vortex shedding is no longer present. This provided further evidence for three different wake signatures corresponding to three angle of attack ranges. Group 1 (-2° to 1°) shows strong vortex shedding. Group 2 (2° to 5°) has, decreasing magnitude of mean and fluctuating quantities to the maximum aerodynamic efficiency condition. Lastly, Group 3 (6° to 8°) sees an increase in magnitude as the airfoil’s flow begins to separate at 8°.Fluctuating quantities, URMS, VRMS, and Reynolds shear stress, exhibited similarly high gradients in the same angle of attack range, as well a decrease in absolute magnitude at the maximum aerodynamic efficiency angle of attack. Similar trends were found in the same fluctuating components for the self-preserved wake, as well. These trends suggest a correlation exists between the properties in an airfoil’s production-dominated and self-preserved wake and aerodynamic efficiency. Further evidence was offered by study of turbulent kinetic energy, turbulent production, and viscous dissipation. Similar behaviors were discovered, with high gradients present between 6° and 8°, as well as decreased magnitude around the maximum lift-to-drag ratio.Evidence from the SD7003’s wake properties strongly implies a correlation between those properties in the near and far wake and aerodynamic efficiency. An obvious next step would be to perform a similar investigation with different airfoils to determine if these correlations persist, or are isolated to the SD7003.Understanding the correlations between the flow physics and aerodynamic efficiency could lead to several benefits. One such benefit would apply to airfoil designers: a better understanding of the wake physics could allow for airfoil geometry to be tailored, such that (L/D)Max occurs at a desired angle of attack. Coupled with geometric tailoring would be increased wing performance due to having a more comprehensive understanding of the wake flow physics. Additionally, there is the potential to harvest energy from the wake to lessen power demands on aircraft, as well as attenuating unsteady aerodynamic loads