Experimental and Computational Study on Flapping Wings with Bio-Inspired Hover Kinematics

Vandenheede, Ruben; Bernal, Luis P.; Morrison, Christian L.; Gogulapati, Abhijit; Friedmann, Peretz P.; Kang, Chang Kwon; Shyy, Wei

doi:10.2514/1.j052644

Cited by 15 publications

(7 citation statements)

References 23 publications

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“…The accuracy of the approach is expected to decrease when such effects have a predominant effect of the forces. The aerodynamic model exhibits reasonable agreement with CFD-based aerodynamics and experiments in both the time-averaged values and the time histories of the forces for the range of kinematic and aerodynamic parameters considered in the current work [10][11][12].…”

Section: B Unsteady Aerodynamic Modelsupporting

confidence: 59%

“…The model, developed in previous studies by the authors [10,11], exhibits acceptable correlation with CFD simulations and experiments for a wide range of kinematic, structural, and aerodynamic parameters [10][11][12]. The components of the aeroelastic model and the corresponding validation and verification studies are described in [10][11][12]. Therefore, the discussion presented in this paper is limited to an overview.…”

Section: Overview Of the Nonlinear Aeroelastic Modelmentioning

confidence: 99%

“…In the current study, the aerodynamic force and power of the flapping wing are computed using an approximate aeroelastic model developed by the authors [10,11]. The model produced acceptable correlation with computational fluid dynamics (CFD) simulations and experiments for a range of kinematic, structural, and aerodynamic parameters [10][11][12]. It also yields a significant reduction in computational cost compared to CFD-based approaches.…”

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confidence: 99%

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Optimization of Flexible Flapping-Wing Kinematics in Hover

2014

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Hover-capable flapping-wing micro air vehicles are well suited for missions in confined spaces. The best design practices for flapping wings and their kinematics are largely unknown, especially for flexible wings. To address this issue, numerical optimization is applied to the design of the kinematics and structural sizing of a flapping wing using a surrogate-based approach. The surrogates are generated using kriging interpolation of the time-averaged thrust generated and power required by the wings. The thrust and power data are computed using a nonlinear approximate aeroelastic model developed in previous studies by the authors. A numerical optimization algorithm is used to identify designs that produce the desired combination of thrust and power. The design variables consist of parameters describing the flap-pitch kinematics and the stiffness of the flexible wings. A trend study of thrust and power indicate that the phase angle between flap and pitch motions significantly affects the wing performance when the stroke amplitudes and the frequency are fixed. Smaller amounts of pitch actuation produced peak thrust in flexible wings when compared to the rigid wings. Several flexible configurations produce higher thrust when compared to the best thrust-producing rigid configuration. However, rigid wings have higher propulsive efficiency when compared to flexible wings for the same amount of generated thrust. Thus, the actual design of a flapping wing will depend on the relative importance given to thrust production and propulsive efficiency.

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Section: B Unsteady Aerodynamic Modelsupporting

confidence: 59%

Section: Overview Of the Nonlinear Aeroelastic Modelmentioning

confidence: 99%

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confidence: 99%

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Optimization of Flexible Flapping-Wing Kinematics in Hover

2014

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“…The cases depicted in figure 5 assume a constant pitch angle within the translational phase of each stroke that is the same for the upstroke and downstroke. Multiple studies on insect kinematics [2,49,[65][66][67][68] have demonstrated that this is not typically true of actual insects. Rather, the pitch angle varies substantially within each half-stroke and the motion is not necessarily symmetric between each half-cycle.…”

Section: Stability Overviewmentioning

confidence: 99%

Wing-wake interaction destabilizes hover equilibrium of a flapping insect-scale wing

Bluman

Kang

2017

Bioinspir. Biomim.

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Wing-wake interaction is a characteristic nonlinear flow feature that can enhance unsteady lift in flapping flight. However, the effects of wing-wake interaction on the flight dynamics of hover are inadequately understood. We use a well-validated 2D Navier-Stokes equation solver and a quasi-steady model to investigate the role of wing-wake interaction on the hover stability of a fruit fly scale flapping flyer. The Navier-Stokes equations capture wing-wake interaction, whereas the quasi-steady models do not. Both aerodynamic models are tightly coupled to a flight dynamic model, which includes the effects of wing mass. The flapping amplitude, stroke plane angle, and flapping offset angle are adjusted in free flight for various wing rotations to achieve hover equilibrium. We present stability results for 152 simulations which consider different kinematics involving the pitch amplitude and pitch axis as well as the duration and timing of pitch rotation. The stability of all studied motions was qualitatively similar, with an unstable oscillatory mode present in each case. Wing-wake interaction has a destabilizing effect on the longitudinal stability, which cannot be predicted by a quasi-steady model. Wing-wake interaction increases the tendency of the flapping flyer to pitch up in the presence of a horizontal velocity perturbation, which further destabilizes the unstable oscillatory mode of hovering flight dynamics.

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“…In order to accelerate and ensure the convergence of the FSI the Aitken relaxation method has been incorporated 19 . Full details of this algorithm and careful validation analysis against well-documented experimental results can be found in our previous work 19,[42][43][44] .…”

Section: B Numerical Modelsmentioning

confidence: 99%

Aerodynamic Performance of Flexible Flapping Wings at Bumblebee Scale in Hover Flight

Sridhar

Kang

2015

53rd AIAA Aerospace Sciences Meeting

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Aeroelastic response at bumblebee scale is explored using a well-validated Navier-Stokes equation solver, fully-coupled with a structural dynamics solver. Hover flight at Re=1.0×10 3 is considered, which results in a purely passive wing rotation due to the dynamic balance between aerodynamic loading, elastic restoring force, and inertial force of the wing. A systematic study with effects of variation of motion amplitude and wing stiffness on the resulting aerodynamic and structural dynamic response is reported. The aeroelastic response is non-periodic and varies cycle to cycle. Highest time-averaged lift of 1.43 is obtained at a moderate amplitude and lowest wing stiffness. Optimal efficiency corresponds to the largest motion amplitude with a moderate wing stiffness. Dual vortical structures are observed at both ends of the wing during a stroke, leading to multiple wing-wake interactions. The vortical evolution is more chaotic than at Re=1.0×10 2 that corresponds to the fruit fly scale. Nevertheless, the time history of lift for optimal efficiency motions are remarkably similar for both scales. Moreover, the time averaged lift scales with the shape deformation parameter, reinforcing the observation made at both fruit fly and water tunnel scales. Finally, the reduced frequency for the optimal efficiency motion is close to experimentally observed values for hovering bumblebees, suggesting that bumblebee wing kinematics may aim to be aerodynamically optimal. Nomenclature c = Chord [m] C L = Coefficient of lift [1] C P = Coefficient of power input [1] E = Young's Modulus [Pa] f = Motion frequency [1/s] f 1 = First natural frequency of the wing [1/s] F = Fluid force acting on the wing per unit length [N/m] h = Plunge motion of the wing [m] h a = Plunge amplitude [m] h s = Thickness of the wing [m] k = Reduced frequency, / fc U  [1] p = Pressure [Pa] Re = Reynolds number, / Uc  [1] St = Strouhal number, ~/ a fh U [1] t = Time [s] U = Maximum plunge velocity: 2 a fh  for hover [m/s 2 ] u = Velocity [m/s] v = Wing displacement: v=w+h [m] w = Wing displacement relative to the imposed motion h [m]  = Passive pitch angle [degrees]  a = Passive pitch amplitude [degrees]  m = Mid-stroke passive pitch angle [degrees]  e = End-of-the-stroke passive pitch angle [degrees] Φ = Stroke angle [degrees]  = Phase lag between passive pitch and plunge motion [degrees]  = Non-dimensional relative shape parameter [1]  = Propulsive efficiency: / L P C C [1]  = Kinematic viscosity of the fluid [m 2 /s] 0  = Effective inertia: * * 2 ( / ) s h k   [1] 1  = Effective stiffness: * 2 / (12 ) s f Eh U  [1]  f = Density of the fluid [kg/m 3 ]  s = Density of the wing structure [kg/m 3 ]  = Vorticity, non-zero component of u [1/s] () * = Non-dimensional variables (  ) = Time-averaged variables

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Experimental and Computational Study on Flapping Wings with Bio-Inspired Hover Kinematics

Cited by 15 publications

References 23 publications

Optimization of Flexible Flapping-Wing Kinematics in Hover

Optimization of Flexible Flapping-Wing Kinematics in Hover

Wing-wake interaction destabilizes hover equilibrium of a flapping insect-scale wing

Aerodynamic Performance of Flexible Flapping Wings at Bumblebee Scale in Hover Flight

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