Numerical Investigation of the Aerodynamic Behavior of a Generic Light Aircraft

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Numerical Investigation of the Aerodynamic Behavior of a Generic Light Aircraft

Dennis Keller, Dominique Farcy, Jean-François Le Roy

To cite this version:

Dennis Keller, Dominique Farcy, Jean-François Le Roy. Numerical Investigation of the Aerodynamic

Behavior of a Generic Light Aircraft. AAAF AERO2019, Mar 2019, PARIS, France. �hal-02127311�

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54^th3AF International Conference on Applied Aerodynamics

25 — 27 March 2019, Paris – France

FPnum-AERO2019-keller

NUMERICAL INVESTIGATION OF THE AERODYNAMIC BEHAVIOR OF A GENERIC LIGHT AIRCRAFT

Dennis Keller⁽¹⁾and Dominique Farcy⁽²⁾and Jean-Franc¸ois Le Roy⁽³⁾

(1)Institute of Aerodynamics and Flow Technology, German Aerospace Center, Lilienthalplatz 7, 38108 Braunschweig, Germany, Email: dennis.keller@dlr.de

(2)Aerodynamics, Aeroelasticity, Acoustics Department, ONERA - The French Aerospace Lab, Lille, France, Email: dominique.farcy@onera.fr

(3)Aerodynamics, Aeroelasticity, Acoustics Department, ONERA - The French Aerospace Lab, Lille, France, Email: jean-francois.le roy@onera.fr

ABSTRACT

The present paper summarizes the key findings of a numerical study on the aerodynamic behavior of a generic light aircraft under flow conditions, which are typically associated with spin motions. These conditions include high angles of attack, crosswind and rotational motion.

Besides investigating the limits of Reynolds-averaged Navier-Stokes simulations for this type of conditions, the simulations contribute to a better understanding of existing wind-tunnel data. Furthermore, the influence of wind-tunnel related aspects such as scaling effects are investigated. The comparison between the numerical and experimental results generally shows good agreement re- garding global force coefficients and separation behavior. The characteristic behavior with regards to crosswind and rotational motion around the longitudinal wind axis is captured well by the computations. Scaling effects are considerable with the maximum vertical force coefficient increasing by up to∆CZ,max=0.25 at real flight Reynolds and Mach number compared to wind-tunnel conditions.

1. INTRODUCTION

Loss of control due to stall/spin is one of the main causes of fatal accidents in general aviation. The Aerodynamics, Aeroelasticity, Acoustics Department at ONERA, Lille investigates the spin behavior of a generic light aircraft for years. Two test campaigns in ONERA’s vertical wind tunnel SV4 [4, 1] contributed to a substantial amount of aerodynamic data, which is used for further flight dy- namic evaluations. In the course of collaboration be-

tween ONERA and DLR, the aerodynamic dataset was extended by results from numerical simulations based on the Reynolds-averaged Navier-Stokes equations. Tradi- tionally, the aerodynamic behavior under spin conditions is investigated with wind-tunnel experiments [3, 6] as the conditions are highly off-design implying complex flow phenomena. On the one hand, the aim of the simulations is to verify the numerical approach for assessing the aerodynamic behavior of light aircraft particularly at flow conditions associated with spin motions. These flow conditions typically involve high angles of attack, sideslip angles, and coupled roll and yaw motions. On the other hand, the simulations are thought to contribute to a better understanding of the wind tunnel data, as the latter pro- vides limited information on existing flow phenomena.

Moreover, the influence of wind tunnel related aspects such as scaling effects are investigated. The present paper illustrates the key findings from the numerical simulations. Numerical results for static conditions with varying angles of attack and sideslip angles, and at constant rota- tions around the longitudinal wind axis are compared to wind tunnel results. The influence of the model support is examined as well as transition effects. Furthermore, numerical results for free flight conditions are presented.

2. NUMERICAL SETUP

The computations are performed with theDLR TAUcode [5], which is based on an unstructured finite volume approach for solving the Reynolds-averaged Navier-Stokes equations. For the present investigation, the implicit

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LUSGS scheme is used for time stepping. A central scheme and second order Roe upwind scheme are used for the spatial discretization of the inviscid mean flow fluxes and the turbulent convective fluxes, respectively.

Two turbulence models have been used. The turbulence effects are modeled with the Spalart-Allmaras turbulence model [9] with vortical and rotational flow correction based on the Spalart-Shur correction [10].

Computations were performed with fully turbulent flow, fixed transition atX/c≈0.05 similar to the wind- tunnel test, and transition prediction. The latter was used to simulate the behavior of the model in the wind-tunnel with natural transition. For the evaluation of the transition line, only Tollmien/Schlichting wave instabilities are considered (besides flow separation). Transition is predicted based on the eN-Method with N-factors computed by the linear stability solver LiLo [7].

In order to model the propeller effects, an actuator disk approach based on 2D blade element theory is imple- mented. In this way, the local load of the propeller is calculated based on a given radial distribution of force coefficients along the blades and the local flow conditions [8].

3. TEST CONFIGURATION

The test configuration is a general light aircraft (GLA) with low-wings and a single piston engine located in the front fuselage. The wind-tunnel model is scaled by a 1 : 5 ratio. Fig. 1 shows the model in the wind tunnel (2017 test campaign [1]) and as it is used for the computations with dorsal sting. Tab. 1 depicts the basic geometric parameters of the model in wind-tunnel scale and full scale.

W/T scale full scale

Span 1.972m 9.862m

Chord (reference length) 0.249m 1.245m Reference area 0.4912m² 12.28m² Table 1: Geometric parameters of the CAD model for computations

Tab. 2 summarizes the free stream conditions for the computations at W/T scale and at full scale (real flight conditions). In case of the computations with actuator disk the thrust coefficient was set toC_T =0.04, slightly above the value necessary to balance out drag atα=0^◦.

W/T scale full scale

Mach number 0.1469 0.2374

Reynolds number 834701 5211441 Table 2: Free stream conditions for model scale and full scale computations

The hybrid CFD meshes were built with the semi-

(a) Model in wind tunnel SV4

(b) CAD model for TAU computations

Figure 1: Geometry of generic light aircraft with wind tunnel mounting

automated mesh generator Centaur [2]. The meshes of the model in wind tunnel scale with mounting consists of 310000 surface nodes, resulting in a volume mesh with 25.6M nodes. The mesh for the full scale model consists of 300000 surface nodes, leading to a volume mesh with 25.2M nodes. The surface mesh of the model in wind tunnel scale is shown in figure 2.

4. RESULTS 4.1 Stall behavior

The numerical simulations were performed with two turbulence models, the SA turbulence model with rotational and curvature correction (SA-RC) and the SSG-LRR Reynolds-stress model. Both turbulence models predict a main wing stall behavior similar to the one seen in the experiment. Fig. 3 illustrates the evolution of flow separation with respect to the angle of attack for the SA- RC model in terms of skin friction (c_{f x})-iso-lines. At

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Figure 2: Surface mesh of the model in wind tunnel scale with dorsal sting

the main wing, both models predict trailing edge separation with the flow separation being more advanced at the wing root. With rising angle of attack, the flow separation expands in upstream direction and spreads towards the midboard and outboard of the wing. This behavior agrees with the one indicated by the wind tunnel data.

However, the flow separation in case of the SSG-LRR model generally occurs slightly later compared to the SA- RC model, leading to smaller regions of separated flow at same angle of attack. Fig. 4 compares theC_pdistribution of the simulations and the experiment in cutting planes for α=24^◦. Atη =0.15 (Fig. 4(a)), theCp distribution from the wind-tunnel shows a large pressure plateau starting fromX/c=0.2, indicating a large region of flow separation. The simulations with both turbulence models capture this behavior well. In the midboard region, atη=0.6 (Fig. 4(b)), the flow separation is of similar size as seen forη=0.15 according to the wind-tunnel data. Again, the SA-RC model captures the flow separation well. The SSG-LRR model also indicates trailing edge separation. Nevertheless, the extend of the separation region is notably smaller compared to the wind- tunnel results.

In contrast to the rather good agreement of the main wing’sC_pdistributions between the computational results and the wind-tunnel results, the agreement of the horizontal tail plane’s surface pressure data is rather poor. In particular at high angles of attack, the limited available data from the wind-tunnel experiment disagrees consid- erably with theC_p distributions from the computations as Fig. 5 indicates for α =18^◦. Furthermore, theC_p distributions of the computations with SA-RC and with SSG-LRR strongly differ from each other. In case of the SA-RC turbulence model, the suction peak is completely broken down. In contrast, the SSG-LRR model predicts a notable suction peak.

Figure 3: Evolution of flow separation based on TAU computations

4.1.1 Effect of Transition

Computations were carried out with fully turbulent flow (FT), fixed transition on the main wing’s upper surface (TD) as it was done in the experiment and transition prediction (TN). At low angles of attack, theC_p distributions from the experiment and the computations do not show a significant difference between fixed transition and natural transition/transition prediction. Atα =0^◦, the computations indicate transition to occur at around X/c_trans≈0.55 along the upper side of the main wing and slightly earlier (0.44<X/c_trans<0.54) on the lower side.

Fig. 6 compares the influence of the transition position on the surface pressure coefficient of the computations with SA-RC turbulence model to the one of the experiment at η=0.6. Atα=12^◦(Fig. 6(a)), the computations predict transition to occur atX/c≈0.15, as indicated by the notable change in pressure gradient. The predicted position of transition agrees well with the wind-tunnel data.

However, the increase of the suction peak due to laminar flow is slightly lower in the computations compared to the increase observed in the experiment. The reason for the lower suction peak may be the laminar separation bubble, which occurs in the computations. It is unknown whether the separation bubble existed during the wind- tunnel test. Atα=18^◦(Fig. 6(b)), the transition position moves upstream toX/c≈0.1 and is still triggered by the laminar separation bubble according to the computations.

The pressure coefficient of the case with TN recovers to slightly higher pressure values at the trailing edge, indicating less trailing edge separation due to laminar flow.

The characteristics of theCp distribution, including the leading edge suction peak, the position of the change in

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(a)η=0.15

(b)η=0.6

Figure 4: Main wingC_pdistributions atα=24^◦

gradient due to transition and the change in gradient at the rear due to reduced separation agrees well between the computations and the wind-tunnel test.

Fig. 7 summarizes the evolution of the transition line on the main wing’s upper surface with rising angle of attack as predicted by the computations with SA-RC. From α =0^◦ toα =12^◦, the transition lines move consider- ably upstream. Afterα =12^◦, the location of the transition lines is nearly unchanged as it is influenced by the laminar separation bubble.

Fig. 8 compares the vertical force coefficients with respect toα of the computations with SA-RC to the ones from the wind-tunnel test. The results agree very well for the fixed transition (TD) up toα =18^◦. At higher angles of attack, the results begin to diverge mainly due to delayed flow separation in case of the computations.

The computations as well as the experiment predict a notable increase in vertical force coefficient if transition is

Figure 5:C_pdistributions atηHT P=0.5 of the horizontal tail plane forα=18^◦

not fixed (TN). Atα=8^◦, the computations and experiment yield an increase of∆CZ=0.045 and∆CZ=0.05, respectively. Again, at low angles of attack (α <10^◦), the computational results agree very well with the experimental results. Atα ≥10^◦, the difference between TN and TD is notably smaller in the computations compared to the experiment. A possible explanation for the discrepancy might be the laminar separation bubble, which occurs in the computation. Despite the divergence of the results with free transition (TN), the maximum vertical force coefficient only differs by∆C_Z,max=0.03 between the computations and the experiment.

4.1.2 Effect of Free Stream Conditions and Pro- peller Slipstream

In order to investigate the influence of real flight free stream conditions compared to wind-tunnel conditions, computations at flight Reynolds and Mach numbers were performed. Furthermore, computations with actuator disk were carried out to assess the effect of propeller slipstream on the aircraft’s aerodynamic behavior. Fig.

9 illustrates the influence of free stream conditions and propeller effects on the vertical force coefficient. Under real flight conditions,C_Z,max is increased by 0.14 compared to wind-tunnel conditions in case of fully turbulent flow (FT) mainly due to delayed flow separation. The increase in the maximum vertical force coefficient due to real flight conditions is even higher when flow transition is predicted (TN) with∆CZ,max=0.25. The missing model support in case of the computations with real flight conditions plays a rather minor role. Computations without model support under wind-tunnel conditions have shown that the existence of the model support leads to a reduction of∆CZ,max=−0.03. The computations with propeller indicate an increase of∆CZ,max=0.075 in the

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(a)α=12^◦

(b)α=18^◦

Figure 6: Influence of transition onC_pdistribution of the main wing atη=0.6

Figure 7: Evolution of upper surface transition line based on TAU computations

airframe’s vertical force coefficient. The propeller slipstream mainly affects the inboard region of the main wing (|η|/0.3) and the tail. Flow separation at the wing root, which occurs with rising angle of attack is there-

Figure 8: Vertical force coefficient with respect to the angle of attack

fore reduced on the downwash side of the propeller and increased on its upwash side. As a result, the propeller has a significant effect on the rolling moment at high angles of attack (α >14^◦). Furthermore, asymmetric flow conditions at the vertical tail plane (VTP) cause yawing moments to build up with rising angle of attack.

Figure 9: Influence of free stream conditions and propeller slipstream on vertical force coefficient with respect to the angle of attack

4.2 Behavior under Crosswind Conditions

The surface pressure distribution of the main wing is affected by crosswind in various ways. Besides the altered normal component of the free stream velocity, the main

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effects for the present aircraft are related to the wing’s dihedral and fuselage integration. The (positive) dihedral causes an increase of the local angle of attack at the windward side and a decrease of the local angle of attack at the leeward side. In contrast, the low wing configuration leads to a decrease of the local angle of attack at the windward side and an increase at the leeward side in proximity to the fuselage. The experimental and computational results at low angles of attack reflect these characteristics by indicating higher pressure on the upper surface of the windward side compared to the leeward side in the inboard region of the main wing. In the midboard and outboard region the pressure on the upper surface of the windward side is lower compared to the leeward side.

Fig. 10 compares theC_p distributions of the computations and the experiment forα =14^◦. Atη=0.15 (Fig.

10(a)), the experiment and the computations indicate a higher leading edge suction peak on the windward side (RS) compared to the leeward side (LS). Furthermore, the pressure plateau at the trailing edge is significantly larger on the leeward side as demonstrated by both experiment and computations. It can be concluded that the increase in local angle of attack due to the fuselage effect on the leeward side causes stronger flow separation than it is the case on the windward side, where the fuselage effect leads to a reduction of the local angle of attack. In the midboard region atη=0.6 (Fig. 10(b)), theC_pdistri- butions show the expected behavior with the suction peak on the windward side (RS) being slightly higher than the one on the leeward side. The effect of crosswind on the surface pressure levels agree well between the experiment and the computations.

The flow separation observed in the inboard region of the main wing has a notable impact on the flow conditions at the VTP as seen in Fig. 11. Atα=0^◦(Fig. 11(a)), the oncoming flow at the VTP is undisturbed, indicated by the homogeneous Mach number of the streamlines.

Atα =12^◦(Fig. 11(b)), the separated flow, identifiable by the streamlines with low Mach number, is transported along the fuselage towards the VTP. Here, the reduced flow velocity, caused by flow separation at the main wing and increased losses within the fuselage boundary layer lead to a notably reduced flow velocity along the suction side of the VTP at its root. As a result, the VTP side force is reduced. Atα=18^◦(Fig. 11(c)), the flow separation at the main wing is further increased, resulting in a larger region of reduced flow velocity at the VTP. Moreover, the main wing wake flow reaches the VTP at a higher position due to the increased angle of attack. The main wing wake flow now leads to strong flow separation in the midboard region of the VTP and thus reduces its effectivity significantly.

Fig. 12 demonstrates the impact of the asymmetric flow separation on the main wing and its interaction with the VTP on the lateral moments. Atα=0^◦andβ=10^◦

(a)η=0.15

(b)η=0.6

Figure 10: Comparison ofC_pdistribution of left and right main wing atα=14^◦andβ=10^◦

(solid lines), the rolling moment coefficient (C_l) is rather small as Fig. 12(a) suggests. With rising angle of attack, C_lincreases in magnitude mainly due to the contribution from the main wing. This trend is reflected by the experiment and the computations. Nevertheless, theC_l curve based on the computations is slightly offset from the one based on the experimental results. The offset inC_l also exists at zero crosswind (dash-dotted lines). The reason for the unbalanced rolling moment coefficient in the experiment at zero crosswind (and low angles of attack) re- mains unknown.

Fig. 12(b) illustrates the evolution of the yawing moment coefficient (C_n) with rising angle of attack. The stabilizing yawing moment, which is mainly caused by the VTP, is highest atα=0^◦. With rising angle of attack, Cndeteriorates due to increased losses within the fuselage boundary layer and the interaction of the main wing

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(a)α=0^◦

(b)α=12^◦

(c)α=18^◦

Figure 11: Influence of flow separation at the main wing root on the flow conditions at the VTP forβ=10^◦(based on TAU computations without mounting)

wake with the VTP. Again, this trend is represented by both, experiment and computations with theC_ncurve of the computations being offset from the one of the experiment.

4.3 Rotation

Similar to the procedure in the experiment, steady simulations of a rotational motion around the streamwise axis (roll axis in the aerodynamic coordinate system) at constant angular rate were performed. The computations were carried out with fixed transition. Fig. 13 compares the surface pressure distributions and skin friction lines between the case without motion and the one at a dimensionless angular rate of ω·c/V =0.05215 for α =0^◦. Without rotational motion (Fig. 13(a)), the flow is fully attached to the main wing as it is indicated by theC_{f x}=0- iso-lines (purple lines). The red color at the leading edge indicates the stagnation line. With rotational motion (Fig.

13(b)), the distribution of the surface pressure coefficient changes as expected in case of a positive roll rate. On the port side, the rotation reduces the local angle of attack with the magnitude of the change inα_locdepending on the spanwise position. As a result, the stagnation line

(a) Rolling moment

(b) Yawing moment

Figure 12: Comparison of lateral moment coefficients with respect to angle of attack atβ=10^◦

moves on the upper surface, as indicated by the red color, and reduces the lift. Since the induced angle of attack due to the roll motion is increasing towards the wing tip, the stagnation line moves further downstream with increasing|η|. In contrast, the local angle of attack is increased on the starboard side causing stronger suction on the upper surface and thus higher lift. In the midboard region, a small region of flow separation can be observed at the trailing edge. Even though, the angle of attack induced by the roll motion is highest at the wing tip, the wing tip region is also influenced the most by 3D effects which induce a negative angle of attack. As a result, the local

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angle of attack, which is the combination of global angle of attack, geometric angle of attack, induced angle of attack due to 3D effects, and induced angle of attack due to roll motion, reaches its maximum atη≈0.6 and thus flow separation occurs first, here.

(a) ω·c/V=0

(b)ω·c/V=0.05215

Figure 13: Influence of rotational motion on surface pressure distribution and skin friction lines atα=0^◦

At α =15^◦, the flow is already partially separated from the main wing in case of no rotational motion (Fig.

14(a)). Due to the rotational motion, the flow separation is reduced on the port side and increased at the starboard side (Fig. 14(b)). Despite the change in flow separation, the suction peak is reduced on the port side and increased on the starboard side of the main wing. However, the extend of the low pressure zone on the starboard-sided main wing is limited by flow separation.

Atα=25^◦, the flow separation on the main wing has expanded upstream to the leading edge in case of no rotation (Fig. 15(a)). Due to the rotation (Fig. 15(b)), the region of flow separation is notably reduced on the port side. In contrast toα=15^◦, the suction peak increases on the port side. On the starboard side, the flow is entirely separated from the wing. As a result, the suction peak on the starboard side vanishes.

The phenomena illustrated in Fig. 13 - 15 have a no-

(a)ω·c/V=0

(b)ω·c/V=0.05215

table impact on the lateral moment coefficients as shown in 16. Fig. 16(a) depicts the evolution of the rolling moment coefficient with respect to the angular rate for the computations and the experiment. The trends ofC_l agree very well between the experiment and the computations.

Atα=0^◦, the increased lift on the starboard side and decreased lift on the port side due to the rotational motion causes a damping rolling moment. The magnitude ofC_l increases linearly with rising angular rate. Atα=15^◦, the change in flow separation on the main wing leads to a reduction of the lift decrease on the port side and lift increase on the starboard side due to the rotational motion.

As a result, the increment inC_ldue to the rotational motion decreases and the trend of the rolling moment coefficient with respect to the angular rate becomes non-linear.

With rising angle of attack, the damping rolling moment lessens further. Atα=25^◦, the rotational motion leads to an increase in lift on the port side and a decrease in lift on the starboard side as illustrated in Fig. 15. As a result, the C_lincrement due to the rotational motion becomes positive, causing a reversion in the behavior of the rolling moment coefficient with respect to the angular rate. While the trend ofC_l with respect to the angle of attack and

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(a) ω·c/V=0

(b)ω·c/V=0.05215

the angular rate agrees well between the experiment and the computations, the behavior ofC_l with rising angle of attack in case of the computations seems to be lagging behind the one based on the experiment. The reason for this is thought to be a slightly delayed flow separation in the computations compared to the experiment.

Fig. 16(b) compares the yawing moment coefficient with respect to the angular rate of the experiment and the computations. With C_n becoming non-linear with respect to the angular rate at high angles of attack and eventually reversing atα=25^◦, the yawing moment coefficient shows a behavior, which is similar to the one of the rolling moment coefficient. Besides, the results demonstrate an additional characteristic. In contrast to C_l, which steadily increases with rising angle of attack at constant angular rate,C_nfirst decreases betweenα=0^◦ andα =10^◦ before it increases. All of the mentioned trends are equally reflected by the experiment and the computations, demonstrating very good agreement between the results. Breaking down the forces by model components reveals that the change in gradient ofCnwith respect to the angle of attack at constant angular rate is linked to theCX evolution of the starboard-sided main

wing.

(a) Rolling moment

(b) Yawing moment

Figure 16: Lateral moment coefficients with respect to the dimensionless angular rate for various angles of attack

5. CONCLUSION

A numerical study on the aerodynamic behavior of a generic light aircraft was performed. Simulations at sym- metric conditions as well as under crosswind conditions and with roll motion were carried out. Results of computations at wind-tunnel model conditions were compared to experimental results. The influence of transition was investigated. Furthermore, simulations under flight conditions, including transition prediction and propeller effects, were performed.

The main wingCp distributions of the computations with dorsal sting, particularly the ones with SA-RC, and

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the C_p distributions of the experiment generally agree well in longitudinal motion. Computations and experiment indicate a similar separation behavior. However, the separation evolution in the computations, especially in case of the SSG/LRR turbulence model, is slightly delayed compared to the experiment. Significant differences can be found in theC_pdistributions of the HTP in particular at high angles of attack when the flow conditions at the HTP are affected by inboard separation on the main wing.

The influence of transition based on the computations with transition prediction agrees well at low and moder- ate angles of attack. At higher angles of attack, the lateral force and moment coefficients yield larger differences to the experimental results. A possible explanation for the discrepancy is the laminar separation bubble, which occurs in the computation.

The computations at flight conditions show a notable increase in C_Z,max. In case of fully turbulent flow, the maximum vertical force coefficient increases by

∆C_Z,max=0.14 compared to the case at model conditions with sting. The increase inCZ,max is mainly caused by the delayed trailing edge separation at flight conditions due to the thinning of the boundary layer. The maximum vertical force coefficient is further raised when laminar flow is considered by transition prediction. In this case, the maximum vertical force coefficient is raised by

∆C_Z,max=0.29 compared to the case at real flight conditions and fully turbulent flow and by ∆C_Z,max=0.25 compared to wind-tunnel conditions and transition prediction. Applying thrust increases the maximum vertical force coefficient by∆C_Z,max=0.075.

The simulations with crosswind under wind-tunnel conditions yield a similar behavior as the experiment does. With rising angle of attack, a negative rolling moment builds up due to the asymmetric evolution of flow separation on the main wing. Furthermore, the stabilizing yawing moment decreases with rising angle of attack due to main wing wake-VTP interaction. While the trends of the lateral moments are similar for the experimental and computational results, the data show an offset in the lateral moment coefficients between the experiment and the computations as it is also seen for zero crosswind.

The results of the simulations of a motion around the aerodynamic X-axis agree very well with the results from the experiment. At low angles of attack, the rolling and yawing moment coefficients decrease linearly with rising angular rate. With increasing flow separation, the behavior becomes non-linear as the motion influences the separation evolution. The region of separated flow is increased on the side where the main wing is moving down and decreased on the side where it is moving up. As a result, the additional vertical force on the side, which is moving down, and the reduction of the vertical force on the side, which is moving up, are decreased. At even

higher angles of attack, the motion leads to a change in sign of the lateral moments, since the motion leads to a complete lift break down on the side, which is moving down.

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