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Open Physics

formerly Central European Journal of Physics

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Volume 14, Issue 1

Issues

Volume 13 (2015)

Flap motion of helicopter rotors with novel, dynamic stall model

Wei Han
  • Department of Airborne Vehicle Engineering, Naval Aeronautical and Astronautical University, Yantai-264001, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jie Liu
  • Corresponding author
  • Department of Airborne Vehicle Engineering, Naval Aeronautical and Astronautical University, Yantai-264001, China
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Chun Liu / Lei Chen / Xichao Su
  • Department of Airborne Vehicle Engineering, Naval Aeronautical and Astronautical University, Yantai-264001, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Peng Zhao
Published Online: 2016-07-13 | DOI: https://doi.org/10.1515/phys-2016-0019

Abstract

In this paper, a nonlinear flapping equation for large inflow angles and flap angles is established by analyzing the aerodynamics of helicopter blade elements. In order to obtain a generalized flap equation, the Snel stall model was first applied to determine the lift coefficient of the helicopter rotor. A simulation experiment for specific airfoils was then conducted to verify the effectiveness of the Snel stall model as it applies to helicopters. Results show that the model requires no extraneous parameters compared to the traditional stall model and is highly accurate and practically applicable. Based on the model, the relationship between the flapping angle and the angle of attack was analyzed, as well as the advance ratio under the dynamic stall state.

Key words: Flapping; nonlinear differential equation; dynamic stall; Snel model

PACS: 47.85.Gj; 47.10.A-; 47.10.Fg

1 Introduction

The helicopter, an aircraft lifted and propelled by movable blades, is utilized often in both military and civilian fields, favored for unique characteristics including hovering ability and flexible manipulation [1] . The movement of a helicopter blade can be categorized, roughly, in one of two ways: in-plane motion (lag motion) and out-of-plane motion (flap movement) [2] . The primary focus of this paper is the flap motion of the rigid blade; specifically, the focus is on an equation that effectively reflects flap movement.

Many previous researchers have addressed this problem with notable achievements including the work of Leishman [3] and Johnson [4] . These studies, however, use linear approximation methods to obtain flap equations, based on assumptions of small inflow angle and flapping angle. This approach conveniently solves engineering problems inherent to small angle situations, but is not applicable to large angles. In an effort to remedy this, the present study first analyzes the aerodynamics of the blade element, then establishes a more general, nonlinear flap equation for both small angles and large angles.

Solving flap equations is no simple task. Accurate determination of the lift coefficient and drag coefficient under different conditions is crucial and rather difficult to achieve. For a small advance ratio and angle of attack, the lift coefficient can be obtained using a linear relation to advance ratio, and the drag coefficient can be obtained using a second-order polynomial fitting model in terms of angle of attack [5] . Under large advance ratio and angle of attack, the rotor readily falls into a stall condition, and the simple approximation relationship does not accurately calculate the lift coefficient or drag coefficient. Basically, stall conditions make coefficients nearly impossible to obtain.

Researchers Barakos and Spentzos used the CFD method to calculate the lift coefficient and drag coefficient under stall conditions in a previous study [6, 7]. Their method, which does show high accuracy, requires very lengthy calculation time and is thus not conducive to real-time computation or simulation. In order to build a model that satisfies both accuracy and real-time requirements, two semi-empirical models, the Leishman-Beddoes model, proposed by Leishman, Beddoes, Crouse et al. [8-10], and the ONERA model, proposed by Tran, Petot, McAlister~ et al. [11-13], both utilize experimental, static data to accurately determine lift coefficient and drag coefficient. These require in-practice parameters, however, which affects the practicability of the model.

To address all the issues described above, the Snel stall model, typically applied to wind turbine rotors, is applied for the first time in this study to determine the lift coefficient of helicopter blades. The effectiveness of the proposed method is then verified by simulation experiments. The quasi-static stall model (proposed by Leishman), is utilized to solve the drag coefficient problem.

In this study, a flap equation is established first, and the Snel dynamic stall model is applied to a helicopter for calculating lift coefficient under dynamic stall conditions. Results from an experiment to test the effectiveness of the model are described. Finally, the flap equation is solved alongside the model, using boundary value conditions, and the relationship between flapping angle, advance ratio, and angle of attack is also analyzed.

2 Materials and methods

2.1 Flap equation

2.1.1 Velocity and force analysis of blade element

Blade element theory (BET) is adopted first to establish the flap equation for the rotor. The blade's cross-section at a radial position y, with azimuth angle ϕ and pitch angle θ, and the radial length of the section dr, are selected for analysis as shown in Fig. 1.

Velocity and aerodynamic environment of blade element.
Figure 1

Velocity and aerodynamic environment of blade element.

The velocities of the blade element are shown in Fig. 1(a), where UR is the radial velocity, and UT and UP are tangential and perpendicular to the disk plane, respectively. The velocities are then expressed as follows:

{UT=ΩR(μsinϕ+rcosβ)UP=ΩR(μsinβcosϕ+λcosβ+rdβdϕ+VCΩR)UR=ΩRμcosϕ(1)

where Ω is the rotation rate of the blades, R is the blade radius, μ is the advance ratio, and VC is the climb velocity. λ is the inflow ratio, and it is assumed that the inflow is a uniform (or linear) inflow. The pitch angle is θ = θ0 + θ1ccos ϕ + θ1s sin ϕ. According to the relationship of velocities shown in Fig. 1(a), the inflow angle is φ=arctanUPUT, and the angle of attack is α = θ - φ.

The majority of the flap model, based on the assumption of small flap angle and inflow angle, is a linearization model that uses the approximate relationships sin ββ and cos β ≈ 1, with arctan φφ.

The lift and drag forces are produced by the flow at the blade sections, L and D, which are normal and parallel to U. L=12ρU2cCl(α,M)dr,D=12ρU2cCd(α,M)dr,U2=UT2+UP2,ρ is air density, and c is the blade chord at the position analyzed. The lift coefficient Cl and drag coefficient Cd are intricate functions of the angle of attack and Mach number. The components of the total aerodynamic force are normal to the disk plane Fz = L cos φ - D sin φ. The normal force Fz is typically simplified, as small inflow angle is assumed, in the forms FzL cos φ and FzL. This method is effective in the case of a small angle, but causes considerable errors in the case of a large angle. To account for this, a nonlinear/general form is adopted in this paper.

2.1.2 Establishment of flap equation

This paper uses a rigid blade to build the blade flap equation, focusing primarily on the moment of inertia and the aerodynamic torque related to the center of the disk plane produced by the flapping movement. The forces acting on blade elements are primarily inertial force FI, centrifugal force FC, and aerodynamic force FA, the direction of which is opposite the flapping motion and radially outward, normal to the blade, as shown in Fig. 2.

Force at the flapping blade.
Figure 2

Force at the flapping blade.

For a blade with an offset flap hinge, the dimensionless flap-hinge offset is e and the radial position is R. The inertial force is FI=mΩ2(reR)d2βdϕ2dr and the moment arm related to the hinge is r - eR. The centrifugal force is FC = 2r cos β dr and the moment arm related to the hinge is (r - eR) sin β. The aerodynamic force is FA = Fz and the moment arm related to the hinge is r - eR. Thus, the moment equilibrium regarding the flap hinge of the full blade can be described by integrating the blade element at different positions along the radius:

Ω2eRR(m(reR)2d2βdϕ2+m(reR)rcosβsinβ)dr  =eRRFA(reR)dr(2)

The differential form of the flap equation at radial position r0 is:

d2βdϕ2+Psinβcosβ=(r0eR)FAΩ2IΔβΔR(3)

where P=1+3e2(1e) reflects uniform mass distribution, IΔβ=r00.5ΔRr0+0.5ΔRm(reR)2dr,ΔR=(1e)Rn, and the value of n is the determined by precision.

2.2 Snel dynamic stall model

Under increased angle of attack and Mach number, flow separation and stall occur on the airfoil surface, impacting the distribution of the lift. In other words, the relationship between lift coefficient, angle of attack, and Mach number becomes irregular, rendering it impossible to obtain the coefficients of a simple polynomial.

Calculating the load of a helicopter blade under dynamic stall conditions is highly challenging. Vortex theory and Navier-Stokes numerical calculation, which both show reasonable accuracy, are commonly applied to solve this problem. However, the complexity of these calculation processes affects their real-time performance [14] . A simplified stall model that is quick (without sacrificing accuracy) is necessary to remedy this.

The lift coefficient under steady state is easy to obtain through experimentation, so a semi-empirical model is often adopted based on data obtained from experiments. Many semi-empirical dynamic stall models have been applied to aircraft research -- the two most commonly utilized are the Beddoes-Leishman model and the ONERA model. The Beddoes-Leishman model mainly focuses on simplifying calculations, deriving a series of ordinary differential equations to calculate the lift coefficient. The ONERA semi-empirical model uses both a first and second-order differential equation to describe the unstable behavior of a rotor. The inviscid contribution is described by the first-order differential equation, and the second-order differential equation calculates stall delay plus lift increments. These two models often contain some of the necessary parameters, but determination of these parameters is typically based on dynamic or static measurement data for specific airfoils, which makes the models all together rather inconvenient. The Snel stall model is adopted in this paper to remedy this [15].

The Snel stall model, first proposed by H. Snel [16, 17], is typically applied to the elastic stall effect of wind turbines. The model, which is based on lift coefficient under steady state, consists of two parts: one describing the forcing frequency response, and one describing the higher frequency of a self-excited nature. The lift coefficient is expressed as follows:

Cl=Cl(steady)+ΔCl,1+ΔCl,2(4)

where ∆Cl,1 and ∆Cl,2 are obtained by first and second-order differential equations, respectively [18] . The differential equations are:

{ΩτdΔCl,1dϕ+C10ΔCl,1=F1(ϕ)(Ωτ)2d2ΔCl,2dϕ2+C21ΩdΔCl,2dϕ+C20ΔCl,2=F2(ϕ)(5)

where time is a constant parameter τ=c2V, c denotes the chord of the airfoil, and V is the relative velocity, V=Ωr(1+Rrμsinϕ).

According to the Snel model, C10 can be denoted:

C10={1+0.5Δ8(1+60Ωτdαdϕ),2πsin(ααZ)dαdϕ01+0.5Δ8(1+80Ωτdαdϕ),2πsin(ααZ)dαdϕ>0(6)

where = 2π sin(α - αZ) - Cl(steady), αZ is the zero lift angle of attack, Cl(steady) is the lift coefficient in the steady state, and F1(ϕ) is the frequency of the forcing term of the first-order differential equation, obtained as follows:

F1(ϕ)=ΩτdΔdϕ(7)

According to the description by V. K. Truong and H. Snel, C21 can be written as follows:

C21={12τ[0.01(Δ0.5)+2(Cl,2)2],dαdϕ>00.4τ,dαdϕ0(8)

C20 is expressed:

C20=0.04[1+3(Cl,2)2][1+3Ω2(dαdϕ)2](9)

The forcing term of the first-order differential equation concerns the difference between lift coefficient and potential flow and steady state:

F2(ϕ)=0.018(Δ)+0.006ΩdΔdϕ(10)

According to the model, it is possible to determine the lift coefficient even in a stall condition. The magnitude of drag is small compared to lift, according to J. G. Leishman [19] . As for the definition of the drag coefficient, an approximate expression is effective:

CD={a0+a1Cl+a2Cl2,|α|<αS1135105cos2(ααz),|α|αS(11)

where αS is the threshold value for the stall, and the values of a0, a1, and a2 can be obtained dependent on the specific airfoil.

3 Results and discussion

Each blade is, effectively, a series of infinitely thin cross sections at different positions in the radial direction. Here, the blade is divided into 100 pieces, n = 100, and the blade element ∆r at radial position r0 is selected for analysis.

3.1 Materials of simulation experiment

OA212 airfoils (in uniform mass distribution,) are used for the following simulation experiment. The radius is R = 8.5 m, the dimensionless flap-hinge offset is e = 0.039, the mass distribution is m = 13.0465 kg/m, CTσ=0.0726, the zero lift angle of attack is 0°, the threshold value for the stall is 13°, and the chord length is 0.5273 m. The postion r0 = 0.75R is selected for experimentation, and ∆r = 0.01R.

3.2 Validating the Snel stall model

To validate the Snel stall model as it applies to flap motion, the linear inflow model proposed by Pitt and Peters is adopted [20], expressed as follows: λ=λ0(1+2.0489tanγ2rcosϕ) where λ0 is the average inflow under momentum theory, and γ is the wake skew angle. The lift coefficient curve can be obtained as shown in Fig. 3 by utilizing the Runge-Kutta method under the following conditions: μ = 0.3, α = 15° + 10° sin ϕ, θ0 = 13°, θ1c = 4°, θ1s = -10°, and VC = 0 m/s.

Lift coefficient curve.
Figure 3

Lift coefficient curve.

The red line in Fig. 3 denotes the lift coefficient measured by the experiment in the steady state, and the blue line represents the lift coefficient obtained by the Snel stall model. Fig. 3 makes clear that the lift coefficient obtained by the Snel stall model is almost ubiquitously equal to the data obtained by experimentation when angle of attack is small and linear. As angle of attack increases compared to the threshold value, the flow near the surface of the airfoil becomes unstable, causing the lift coefficient to first drop sharply, then stabilize.

The relationship between flap angle and azimuth angle, with different collective pitch θ0 under conditions of θ1c = 4°, θ1s = -0°, and μ = 0.4, was obtained by solving the flap equation using the boundary value combined with the Snel stall model and B-L model (Beddoes-Leishman) [21, 22], as shown in Fig. 4.

θ0 = 9° (a), θ0 = 21° (b).
Figure 4

θ0 = 9° (a), θ0 = 21° (b).

The relationship between flap angle and azimuth angle with differing collective pitch θ0 values under conditions of θ1c = 2°, θ1s = -6°, and μ = 0.6 (ignoring the effect of reverse flow) is shown in Fig. 5.

θ0 = 5° (a), θ0 = 17° (b).
Figure 5

θ0 = 5° (a), θ0 = 17° (b).

As shown in Figs. 4 and 5, the flap response curve obtained using the Snel stall model is almost consistent with the curve obtained using the classic B-L model, which verifies the credibility and effectiveness of the Snel stall model as applied to helicopter rotors. Further, the Snel model does not require known parameters, which enhances its applicability.

3.3 Analysis of flap response

Successful analysis of the rotor involves gathering different flap response curves by altering collective pitch θ0 under the conditions of θ1c = 4°, θ1s = -10°, and μ = 0.4, as shown in the figure below (ignoring the effect of reverse flow).

When θ0 is 0°, 6°, or 12°, as shown in Fig. 6, the flapping angle first increases then decreases. When the azimuth angle reaches about 300°, the flapping angle begins to increase. With further increase in collective pitch, the amplitude of the flapping angle is usually small, and the azimuth corresponding to the minimum and maximum flap angles tends to be larger, which implies the effect of lag under increased collective pitch.

Flap angle at μ = 0.4 and different θ0.
Figure 6

Flap angle at μ = 0.4 and different θ0.

When θ0 reaches 18° or 24°, the flapping angle first declines then increases, then begins to decline until the azimuth reaches 200° ~ 250°. The azimuth corresponding to minimum and maximum flap angles tends to increase under the influence of these two periods, which suggests the effect of lag on the flapping response is more apparent under increased collective pitch; conversely, the amplitude of the flapping angle tends to increase. In order to thoroughly analyze this phenomenon, the relationship between angle of attack and azimuth is detailed next.

Fig. 7 shows where angle of attack is larger under the conditions described above, suggesting that the amplitude of flapping angle tends to increase first, then decrease until the angle of attack reaches a specific value.

Angle of attack at μ = 0.4 and θ0 = 18° (a), θ0 = 24° (b).
Figure 7

Angle of attack at μ = 0.4 and θ0 = 18° (a), θ0 = 24° (b).

Fig. 8(a) shows that with constant collective pitch value and increasing advance ratio, the amplitude of the flap angle tends to shrink, and the azimuth corresponding to the minimum and maximum flap angle tends to grow (this also demonstrates the effects of lag). When the azimuth reaches π, the flap angle reaches a constant value. For ϕ ∈ [0π], the flap angle decreases with increase in advance ratio. However, for ϕ ∈ [π, 2π], the flap angle instead increases with increase in advance ratio.

Flap angle (a) and inflow angle (b) at θ0 = 12° and different μ.
Figure 8

Flap angle (a) and inflow angle (b) at θ0 = 12° and different μ.

As shown in Fig. 8(b), inflow angle is barely affected by advance ratio around ϕ = 180°, and decreases with increased advance ratio. The angle of attack is negatively related to the inflow angle, which suggests that the angle of attack increases with increased advance ratio. This information is valuable for pilots who can then change the angle of attack of a blade, and the lift, as necessary.

4 Conclusion

A flap equation suitable for both small and large angles was established in this study based on a thorough analysis of blade elements. The Snel dynamic stall model was applied to a helicopter for the first time here in order to calculate lift coefficient under dynamic stall conditions. To demonstrate the effectiveness of the Snel model, an OA212 airfoil was used for simulation experiments. By utilizing the model established under different conditions, the characteristics of the flap response of the helicopter rotor were also analyzed in depth. Results showed that the model has favorable applicability, accuracy, and effectiveness.

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About the article

Received: 2015-03-13

Accepted: 2015-07-29

Published Online: 2016-07-13

Published in Print: 2016-01-01


Citation Information: Open Physics, Volume 14, Issue 1, Pages 239–246, ISSN (Online) 2391-5471, DOI: https://doi.org/10.1515/phys-2016-0019.

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© W. Han et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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