Simulating avian wingbeat kinematics

Parslew, Ben; Crowther, William

doi:10.1016/j.jbiomech.2010.07.024

Cited by 43 publications

(76 citation statements)

References 22 publications

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“…The axis systems employed are similar to those used in a previous model [33] (figure 1). The velocity of the bird with respect to the Earth is given by the freestream velocity vector, V 1 .…”

Section: Bird Dynamicsmentioning

confidence: 99%

“…More recently, forward flight has been tackled through a model that predicts the amplitude and frequency of planar models of bird and bat wings [32]. A model of jointed avian wings has also been developed that encapsulates a broader subset of kinematics, including wing pronation-supination, flexion-extension and stroke-plane inclination [33]. However, it has only been applied to hover and cruising flight, and has neglected the inertial properties of the wing which influence the choice of optimal kinematics.…”

Section: Introductionmentioning

confidence: 99%

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Predicting power-optimal kinematics of avian wings

Parslew

2015

J. R. Soc. Interface.

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A theoretical model of avian flight is developed which simulates wing motion through a class of methods known as predictive simulation. This approach uses numerical optimization to predict power-optimal kinematics of avian wings in hover, cruise, climb and descent. The wing dynamics capture both aerodynamic and inertial loads. The model is used to simulate the flight of the pigeon, Columba livia, and the results are compared with previous experimental measurements. In cruise, the model unearths a vast range of kinematic modes that are capable of generating the required forces for flight. The most efficient mode uses a near-vertical stroke-plane and a flexed-wing upstroke, similar to kinematics recorded experimentally. In hover, the model predicts that the power-optimal mode uses an extended-wing upstroke, similar to hummingbirds. In flexing their wings, pigeons are predicted to consume 20% more power than if they kept their wings full extended, implying that the typical kinematics used by pigeons in hover are suboptimal. Predictions of climbing flight suggest that the most energy-efficient way to reach a given altitude is to climb as steeply as possible, subjected to the availability of power.

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Section: Bird Dynamicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predicting power-optimal kinematics of avian wings

Parslew

2015

J. R. Soc. Interface.

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“…The free-wake model presented here is derived from a model used for analysing helicopter rotor wakes (Bagai & Leishman, 1995; Parslew & Crowther, 2010). Vortex filaments are assumed to be shed from the trailing edge of the wing (Fig.…”

Section: Methodsmentioning

confidence: 99%

“…The local lift per unit span on a surface, L ′, is calculated using blade-element theory (Parslew, 2012; Parslew & Crowther, 2010); while this approach only captures quasi-steady aerodynamic lift the wake model can also be used with methods that include unsteady effects. The Kutta-Joukowski theorem gives the circulation around the wing as The instantaneous circulation is calculated for each blade-element, giving the shed and trailing circulation of filament segments shed from the trailing edge at a given time.…”

Section: Methodsmentioning

confidence: 99%

Theoretical modelling of wakes from retractable flapping wings in forward flight

Parslew

Crowther

2013

PeerJ

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A free-wake method is used to simulate the wake from retractable, jointed wings. The method serves to complement existing experimental studies that visualise flying animal wakes. Simulated wakes are shown to be numerically convergent for a case study of the Rock Pigeon in minimum power cruising flight. The free-wake model is robust in simulating wakes for a range of wing geometries and dynamics without requiring changes to the numerical method. The method is found to be useful for providing low order predictions of wake geometries. However, it is not well suited to reconstructing 3d flowfields as solutions are sensitive to the numerical mesh node locations.

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“…The fullbody mass and the length of each body part were measured from our motion capture subject. We were unable to measure the mass of individual body parts, so roughly approximated them based on mass ratios in bird anatomy references [Parslew and Crowther 2010].…”

Section: Bird Modelingmentioning

confidence: 99%

Data-driven control of flapping flight

Noh

Choi

et al. 2013

ACM Trans. Graph.

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We present a physically based controller that simulates the flapping behavior of a bird in flight. We recorded the motion of a dove using marker-based optical motion capture and high-speed video cameras. The bird flight data thus acquired allow us to parameterize natural wingbeat cycles and provide the simulated bird with reference trajectories to track in physics simulation. Our controller simulates articulated rigid bodies of a bird's skeleton and deformable feathers to reproduce the aerodynamics of bird flight. Motion capture from live birds is not as easy as human motion capture because of the lack of cooperation from subjects. Therefore, the flight data we could acquire were limited. We developed a new method to learn wingbeat controllers even from sparse, biased observations of real bird flight. Our simulated bird imitates life-like flapping of a flying bird while actively maintaining its balance. The bird flight is interactively controllable and resilient to external disturbances.

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Simulating avian wingbeat kinematics

Cited by 43 publications

References 22 publications

Predicting power-optimal kinematics of avian wings

Predicting power-optimal kinematics of avian wings

Theoretical modelling of wakes from retractable flapping wings in forward flight

Data-driven control of flapping flight

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