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Steady and stall analysis of the NLR 7301 airfoil

Profile image of max platzermax platzer

1999

Abstract

free stream Mach number non-dimensional breakdown rate parameter spot generation rate turbulence production term free-stream turbulence at z t C7o] Reynolds number CU/r/ turbulent Reynolds number, k 2 /i/E nondimensional time, la./c Local free-stream velocity free stream velocity magnitude velocity components coordinate parallel to chord transition onset location velocity component of blade surface velocity component of blade surface nondimensional normal wall distance spot spreading half angle, angle of attack intermittency factor ratio of specific heats pressure gradient parameter, (02 /v)/(dU/dr) pressure gradient parameter at r, viscosity kinematic viscosity turbulent viscosity boundary layer momentum thickness density free stream density spot propagation parameter constant of turbulence model differentiation with respect to t quantity on the surface of the blade

Figures (15)
The steady state computations as well as the measure- ments were obtained at fixed angles of attack in a range from -5 degrees up to 20 degrees. The Mach oumber for the experiments was approximately 0.3 and the Reynolds num- ber 4 x 10°. In Fig. 2 the computed steady-state results are compared with the measured data. FIG. 2 Lift coefficient versus angle of attack, experimental data by McCroskey et al. Fig. 2 shows the linear results obtained with the poten- tial flow panel code UPOT (Teng, 1987) and results for vis- cous computations using the Baldwin-Lomax (BL) and the Baldwin-Barth (BB) turbulence model. All viscous compu- tations were performed assuming fully turbulent flow. The BL and BB computed lift coefficients are in close agreement with the measured data for a range of the angle of attack Fully Turbulent Steady-State Computations
The steady state computations as well as the measure- ments were obtained at fixed angles of attack in a range from -5 degrees up to 20 degrees. The Mach oumber for the experiments was approximately 0.3 and the Reynolds num- ber 4 x 10°. In Fig. 2 the computed steady-state results are compared with the measured data. FIG. 2 Lift coefficient versus angle of attack, experimental data by McCroskey et al. Fig. 2 shows the linear results obtained with the poten- tial flow panel code UPOT (Teng, 1987) and results for vis- cous computations using the Baldwin-Lomax (BL) and the Baldwin-Barth (BB) turbulence model. All viscous compu- tations were performed assuming fully turbulent flow. The BL and BB computed lift coefficients are in close agreement with the measured data for a range of the angle of attack Fully Turbulent Steady-State Computations
FIG. 1 C-type grid for the NLR 7301 airfoil
FIG. 1 C-type grid for the NLR 7301 airfoil
of -5 degrees to 8 degrees. Although the BL and BB com- puted lift coefficients are almost the same up to a= 8 de- grees. simulations with BB show more flow separation near the trailing edge on the upper surface than BL. For both models this separation grows significantly with increasing angle of attack but the flow stays attached longer for flow simulations with BL due to BL computing higher viscosity. The locations of the separation onset s/c versus the angle of attack for both turbulence models can be seen in Fig. 3. Once the flow is separated, it does not re-attach. For flow angles of 0 and 5 degrees both turbulence models show no separation. FIG. 3 Variation of the separation onset location Steady-state solutions in terms of the pressure coefficient distributions versus the chord for a = 14, 17 and 17.6 de- grees are given in Figs. 4 to 6.
of -5 degrees to 8 degrees. Although the BL and BB com- puted lift coefficients are almost the same up to a= 8 de- grees. simulations with BB show more flow separation near the trailing edge on the upper surface than BL. For both models this separation grows significantly with increasing angle of attack but the flow stays attached longer for flow simulations with BL due to BL computing higher viscosity. The locations of the separation onset s/c versus the angle of attack for both turbulence models can be seen in Fig. 3. Once the flow is separated, it does not re-attach. For flow angles of 0 and 5 degrees both turbulence models show no separation. FIG. 3 Variation of the separation onset location Steady-state solutions in terms of the pressure coefficient distributions versus the chord for a = 14, 17 and 17.6 de- grees are given in Figs. 4 to 6.
These plots show that a higher suction peak is:predicted by BL than by BB. Furthermore, the BB model yields a much more constant static pressure in the separation region, as can be seen from the pressure plateaus in front of the trailing edge. Both models predict a nonlinear increase of the lift coefficient for angles of attack higher than $ degrees. The lift coefficients calculated with the BB model are in good agreement with the measurements up to 14 degrees while the BL model overpredicts che lift for angles of attack in excess of 8 degrees due to the higher suction peak and smaller flow separation. _ Downloaded From: http://proceedings.asmedigitalcollection.asme.org/ on 02/12/2016 Terms of Use: http://www.asme.org/about-asme/terms-of-use__
These plots show that a higher suction peak is:predicted by BL than by BB. Furthermore, the BB model yields a much more constant static pressure in the separation region, as can be seen from the pressure plateaus in front of the trailing edge. Both models predict a nonlinear increase of the lift coefficient for angles of attack higher than $ degrees. The lift coefficients calculated with the BB model are in good agreement with the measurements up to 14 degrees while the BL model overpredicts che lift for angles of attack in excess of 8 degrees due to the higher suction peak and smaller flow separation. _ Downloaded From: http://proceedings.asmedigitalcollection.asme.org/ on 02/12/2016 Terms of Use: http://www.asme.org/about-asme/terms-of-use__
The BL mode! predicts the highest lift coefficient ac 17 degrees angle of attack in agreement with the experiments, but overpredicts the lift coefficient by 11%. BB predicts the highest lift at an angle of attack of 16 degrees. For angles of attack greater than 14 degrees, the BB model yields a lower lift coefficient than the measurements. [t underpredicts the lift by 8%. For angles of attack greater than 17 degrees the convergence behaviour of both models is quite different. Although the flow, after reaching the stall angle of approx- imately 17 degrees, will no longer be steady and therefore the measured and the computed data have to be regarded as averaged values, the BL mode! converges to a constant lift coefficient up to an angle of attack of 17.6 degrees. In Fig. 6 the BL and BB computed pressure distributions are compared with the experimental data.
The BL mode! predicts the highest lift coefficient ac 17 degrees angle of attack in agreement with the experiments, but overpredicts the lift coefficient by 11%. BB predicts the highest lift at an angle of attack of 16 degrees. For angles of attack greater than 14 degrees, the BB model yields a lower lift coefficient than the measurements. [t underpredicts the lift by 8%. For angles of attack greater than 17 degrees the convergence behaviour of both models is quite different. Although the flow, after reaching the stall angle of approx- imately 17 degrees, will no longer be steady and therefore the measured and the computed data have to be regarded as averaged values, the BL mode! converges to a constant lift coefficient up to an angle of attack of 17.6 degrees. In Fig. 6 the BL and BB computed pressure distributions are compared with the experimental data.
FIG. 9 Instantaneous Mach number distribution for a = 20 degrees computed with the BL model
FIG. 9 Instantaneous Mach number distribution for a = 20 degrees computed with the BL model
FIG. 10 Instantaneous Mach number distribution for a = 20 degrees computed with the BB modet It can be seen that the BB computed flow on the pressure side is in slightly better agreement with the experiment. On the suction side, except near the suction peak, the BL com- puted pressures agree with the experiment up to 70% chord. Further downstream the pressure is too low. The BB com- puted suction peak almost yields the measured peak, but the pressure coefficient between 10% and 70% chord is un- derpredicted which explains the underprediction of the lift coefficient (Fig. 2). The development of the boundary layer along the airfoil for 17.6 degrees is given in Fig. 7. For fow angles exceeding 17.6 degrees the computed lift coefficients are no langer steady. This can be seen in Fig. 8 where
FIG. 10 Instantaneous Mach number distribution for a = 20 degrees computed with the BB modet It can be seen that the BB computed flow on the pressure side is in slightly better agreement with the experiment. On the suction side, except near the suction peak, the BL com- puted pressures agree with the experiment up to 70% chord. Further downstream the pressure is too low. The BB com- puted suction peak almost yields the measured peak, but the pressure coefficient between 10% and 70% chord is un- derpredicted which explains the underprediction of the lift coefficient (Fig. 2). The development of the boundary layer along the airfoil for 17.6 degrees is given in Fig. 7. For fow angles exceeding 17.6 degrees the computed lift coefficients are no langer steady. This can be seen in Fig. 8 where
The fully turbulent flow computations described in the previous section show that the BB model is superior to the BL model. However, the sensitivity to transitional flow effects is an important aspect which needs to be studied. Therefore, the computations were repeated with the BB mode! by assuming that transition starts at z/c = 0.02 for angles of attack between 14 and 17.6 degrees. The nu- merical results can be seen in Fig. 11. Fig. 11 shows that transition becomes important as the incidence angle is increased. Incorporation of transition sub- stantially improves the agreement with the measured lift values in the high angle of attack range. This improvement can also be seen in Fig. 6. On the pressure side the compu- tations with and without transition differ only slightly, but inclusion of transition yields better agreement with the ex- perimental data on the suction side. Only the suction peak is overpredicted, The development of the boundary layer including transition is given in Fig. 7. The separation onset on the suction side was moved downstream from 48% chord without transition to 60% chord with transition.
The fully turbulent flow computations described in the previous section show that the BB model is superior to the BL model. However, the sensitivity to transitional flow effects is an important aspect which needs to be studied. Therefore, the computations were repeated with the BB mode! by assuming that transition starts at z/c = 0.02 for angles of attack between 14 and 17.6 degrees. The nu- merical results can be seen in Fig. 11. Fig. 11 shows that transition becomes important as the incidence angle is increased. Incorporation of transition sub- stantially improves the agreement with the measured lift values in the high angle of attack range. This improvement can also be seen in Fig. 6. On the pressure side the compu- tations with and without transition differ only slightly, but inclusion of transition yields better agreement with the ex- perimental data on the suction side. Only the suction peak is overpredicted, The development of the boundary layer including transition is given in Fig. 7. The separation onset on the suction side was moved downstream from 48% chord without transition to 60% chord with transition.
FIG. 12 Unsteady lift coefficient versus angle of attack obtained with the BL model, experimental data by McCroskey et al. The first test case had a mean angle of a, = 11.96 de- grees and ap amplitude of a, = 2.0 degrees. The reduced frequency was k = 0.4, the Mach number 0.293 and the Reynolds number 3.72 x 108. All unsteady numerical com- putations were performed time accurately after calculating a steady state solution for the mean angle. The unsteady so- lutions were assumed to be converged if consecutive hystere- sis loops did not change. The eompotacions were converged after 3 ta 4 periods. The prediction of the unsteady onset location of transition was obtained with the Michel criterion. It is apparent that the BL model fails to predict the measured hysteresis loop. Repeating the calculations with the BB model, with and without transition, yields much better agreement with the measured hysteresis loop, Fig. 13. Because the unsteady onset locations of transition were not measured, the Michel criterion was used for the calculations.
FIG. 12 Unsteady lift coefficient versus angle of attack obtained with the BL model, experimental data by McCroskey et al. The first test case had a mean angle of a, = 11.96 de- grees and ap amplitude of a, = 2.0 degrees. The reduced frequency was k = 0.4, the Mach number 0.293 and the Reynolds number 3.72 x 108. All unsteady numerical com- putations were performed time accurately after calculating a steady state solution for the mean angle. The unsteady so- lutions were assumed to be converged if consecutive hystere- sis loops did not change. The eompotacions were converged after 3 ta 4 periods. The prediction of the unsteady onset location of transition was obtained with the Michel criterion. It is apparent that the BL model fails to predict the measured hysteresis loop. Repeating the calculations with the BB model, with and without transition, yields much better agreement with the measured hysteresis loop, Fig. 13. Because the unsteady onset locations of transition were not measured, the Michel criterion was used for the calculations.
FIG. 13 Unsteady lift coefficient versus angie of attack obtained with the BB madel, experimental data by McCroskey et al. Additionally, the BB computed unsteady pressure coeffi- cient distributions on the suction side including transition are compared with the measured pressure distributions in Fig. 14 for 20 different angles of attack during the oscilla- tion of the airfoil. It is seen that the computed pressures agree well with the measured distributions.
FIG. 13 Unsteady lift coefficient versus angie of attack obtained with the BB madel, experimental data by McCroskey et al. Additionally, the BB computed unsteady pressure coeffi- cient distributions on the suction side including transition are compared with the measured pressure distributions in Fig. 14 for 20 different angles of attack during the oscilla- tion of the airfoil. It is seen that the computed pressures agree well with the measured distributions.
FIG. 15 Unsteady {tft coefficient with transition versus angle of attack obtained with the BL model, experimental data by McCroskey et al. one can see the numerical results including transition for both turbulence models and the comparison with the ex- perimental data. The unsteady onset locations of transition for both calculations were predicted with Michel's criterion because of the unavailability of relevant experimental tran- sition data.
FIG. 15 Unsteady {tft coefficient with transition versus angle of attack obtained with the BL model, experimental data by McCroskey et al. one can see the numerical results including transition for both turbulence models and the comparison with the ex- perimental data. The unsteady onset locations of transition for both calculations were predicted with Michel's criterion because of the unavailability of relevant experimental tran- sition data.
FIG. 16 Unsteady lift coefficient with transitian versus angle of attack obtained with the BB madel, experimental data by McCroskey et ai.
FIG. 16 Unsteady lift coefficient with transitian versus angle of attack obtained with the BB madel, experimental data by McCroskey et ai.
FIG. 18 Fully turbulent unsteady lift coefficient versus angie of attack obtained with the BB model. experimental data by McCroskey et al. for forced turbulent flow FIG. 17 BB computed unsteady pressure coefficient versus chord in comparison with the measurements by McCroskey et al.
FIG. 18 Fully turbulent unsteady lift coefficient versus angie of attack obtained with the BB model. experimental data by McCroskey et al. for forced turbulent flow FIG. 17 BB computed unsteady pressure coefficient versus chord in comparison with the measurements by McCroskey et al.
in Figs. 15. 16 and 17 were obtained with free transition. A dramatically different hysteresis loop was measured if tran- sition was forced. This is shown in Fig. 18. Unfortunately, no information is available on the precise location of the transition strip. The computation assuming fully turbulent flaw is shown in Figs. |7 and 18. Clearly, the inclusion of transition has a negligible influence if transition onset is predicted from Michel's cnterion.
in Figs. 15. 16 and 17 were obtained with free transition. A dramatically different hysteresis loop was measured if tran- sition was forced. This is shown in Fig. 18. Unfortunately, no information is available on the precise location of the transition strip. The computation assuming fully turbulent flaw is shown in Figs. |7 and 18. Clearly, the inclusion of transition has a negligible influence if transition onset is predicted from Michel's cnterion.

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free stream Mach number non-dimensional breakdown rate parameter spot generation rate turbulence production term free-stream turbulence at z t C7o] Reynolds number CU/r/ turbulent Reynolds number, k 2 /i/E nondimensional time, la./c Local free-stream velocity free stream velocity magnitude velocity components coordinate parallel to chord transition onset location velocity component of blade surface velocity component of blade surface nondimensional normal wall distance spot spreading half angle, angle of attack intermittency factor ratio of specific heats pressure gradient parameter, (02 /v)/(dU/dr) pressure gradient parameter at r, viscosity kinematic viscosity turbulent viscosity boundary layer momentum thickness density free stream density spot propagation parameter constant of turbulence model differentiation with respect to t quantity on the surface of the blade

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max platzer

Journal of Fluids and Structures, 2000

The dynamic stall behavior of the supercritical NLR 7301 airfoil is analyzed with a 2-D thin-layer Navier}Stokes code. The code solves the compressible Reynolds-averaged Navier-Stokes equations with an upwind biased numerical scheme in combination with the Baldwin}Lomax or the Baldwin}Barth turbulence models. The e!ect of boundary layer transition is incorporated using the transition length model of Gostelow et al. The transition onset location is determined with Michel's formula or it can be speci"ed as an input parameter. The two turbulence models yield signi"cantly di!erent steady-state lift coe$cients at incidences greater than 83. The use of the one-equation Baldwin}Barth model together with the Gostelow transition model is found to give substantially better agreement with the experimental data of McCroskey et al. than the Baldwin}Lomax model. Also, the unsteady computations are strongly a!ected by the choice of the turbulence model. The Baldwin}Barth model predicts the lift hysteresis loops consistently better than the algebraic turbulence model. However, the one-equation model improves the prediction of the moment hysteresis loops only for one test case.

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The effect of turbulence intensity on stall of the NACA 0021 aerofoil
John Sheridan

Proceedings of 14th …, 2001

This paper presents lift and drag data obtained from pressure taps on a NACA 0021 aerofoil at Reynolds numbers of around 3.5 x 10 5 over a wide range of angles of attack. The airfoil was subjected to low turbulence flow of turbulence intensity 0.6%, and turbulent flows of length scale 0.56 chords and intensities of 4% and 7%. Turbulence was found to delay stall in a way that is consistent with the delayed stall seen on Horizontal Axis Wind Turbines. Increasing the turbulence intensity delayed stall until higher angles of attack. Further work is proposed to investigate the reasons for this delay, to repeat this experiment on a thick cambered aerofoil and to assess the likely effect on wind turbine performance.

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Turbulent Flow Simulation of the NREL S809 Airfoil
O. Guerri

Wind Engineering, 2006

Numerical computations are carried out for the NREL S809 airfoil. The flow is modelled using an unsteady incompressible Reynolds Averaged Navier-Stokes solver. Two turbulence models (SST k/ω of Menter and RNG k/ε) are applied to close the RANS equations. All computations are performed assuming fully turbulent flow. The flow field is analyzed at various angles of attack from 0 to 20 degrees. Lift and drag forces are obtained from the computations by integrating the pressure and shear stress over the blade surface. The performance of the two turbulence models is compared and the influence of the free stream turbulence intensity is checked. The results confirm the satisfactory performance of the SST k/ω model of Menter for modelling turbulent flow around airfoils.

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Numerical and experimental study of the impact on aerodynamic characteristics of the NACA0012 airfoil
Mohammed Abdulwahid

Open Engineering, 2024

Using computational models and low-speed wind tunnel tests, the aerodynamic characteristics of the NACA 0012 airfoil with low Re numbers of (8 × 10 4 , 2 × 10 5 , 3 × 10 5 , and 4 × 10 5) and angle of attack (AOA) ranging from 0°t o 18°by two steps are examined. Using the same 3-D wind tunnel dimensions, numerical simulations were run. The software program ANSYS FLUENT was used to solve the mathematical model using the continuity equation, the Navier-Stokes equations, and the k-ω shearstress transport turbulence model. Findings demonstrate that at all AOAs, there is a direct relationship between Reynolds numbers (Re), lift and drag coefficients, kinetic energy, and stall angle. The lift coefficient rises linearly as the AOA increases, peaking at 14°, the stall angle at higher Reynolds number. The lift coefficient was found to decline when the AOA was increased further, reaching its minimal value at an AOA of 18°. With a greater AOA, the airfoil's drag coefficient rises, creating turbulent flow. The eddies produced by the turbulence cause the flow to start separating from the airfoil surface as turbulence increases. As a result, the airfoil lift coefficient drops, and its drag coefficient rises at the same time, leading to poor performance. The validation of the numerical results through wind tunnel experiments provided confidence in the findings of the study.

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