The Importance of Flapping Kinematic Parameters in the Facilitation of the Different Flight Modes of Dragonflies

Liu, Xiaohui; Hefler, Csaba; Shyy, Wei; Qiu, Huihe

doi:10.1007/s42235-021-0020-4

Cited by 15 publications

(28 citation statements)

References 38 publications

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“…It is worth mentioning that the previously-reported curved rib design with a higher thicknesses (h = 3.85mm) also outperforms the basic design in out-ofplane stiffness. In addition to the stiffness, the V 2 design with lower height has higher natural frequencies, which implies less risk of resonance under dynamic loads or a higher flapping frequencies for designing flying micro-robots (Figure S53 in Supporting Information) [16,60,61,62]. All these improvements are merely achieved by replicating the dragonfly wing pattern with no adopted computationally-expensive optimization techniques.…”

Section: Application Of Designing An Airplane Wingmentioning

confidence: 99%

Dragonfly-Inspired Wing Design Enabled by Machine Learning and Graphic Statics

Akbarzadeh

Zheng

Mofatteh

et al. 2022

Preprint

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This research relates the morphology of the structural network of a dragonfly wing to the static equilibrium of forces using a geometry-based equilibrium method known as graphic statics. It then develops machine learning algorithms to generate similar structural networks for designing airplane wings using the in-plane equilibrium information of the dragonfly wing. This approach can generate a structural network in equilibrium with no prior information related to the topology or geometry of the network just by receiving the boundary geometry of the wing. This research shows that the internal network of the dragonfly wing can be assumed to be compression or tension-only system on a 2D plane. Consequently, another diagram is constructed to represent the geometric equilibrium of the forces in the initial network. This diagram is called the force diagram in the context of graphic statics. A new wing geometry is reconstructed from the force diagram, with its members sized according to the force magnitude. Both form of the network and its force diagram are used to train machine learning models for the generation of the structural network of the wing. The developed methodology is also capitalized to generate microstructural patterns inspired by other species with networks of convex polygons. We numerically and experimentally examine one application of this method in designing the cellular core, 3D printed by fused deposition modeling, of the airfoil wing, which suggests up to 25% improvement in the out-of-plane stiffness. Our findings suggest this ML-assisted approach enables leveraging million years of evolution in nature to develop the next generation of high-performance, lightweight structures.

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Section: Application Of Designing An Airplane Wingmentioning

confidence: 99%

Dragonfly-Inspired Wing Design Enabled by Machine Learning and Graphic Statics

Akbarzadeh

Zheng

Mofatteh

et al. 2022

Preprint

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“…Dragonfly flight is aerodynamically advanced, and great maneuverability and different flight modes can be achieved by the precise angling and independent motion of the fore-and hindwings (Salami et al, 2019;Liu et al, 2021). When migrating, globe skimmers have been observed to travel at velocities of 3.1-7 m/s depending on tailwind (Srygley, 2003;Feng et al, 2006).…”

Section: Flight Speedmentioning

confidence: 99%

Unraveling the World’s Longest Non-stop Migration: The Indian Ocean Crossing of the Globe Skimmer Dragonfly

Hedlund

Lehmann

et al. 2021

Front. Ecol. Evol.

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Insect migration redistributes enormous quantities of biomass, nutrients and species globally. A subset of insect migrants perform extreme long-distance journeys, requiring specialized morphological, physiological and behavioral adaptations. The migratory globe skimmer dragonfly (Pantala flavescens) is hypothesized to migrate from India across the Indian Ocean to East Africa in the autumn, with a subsequent generation thought to return to India from East Africa the following spring. Using an energetic flight model and wind trajectory analysis, we evaluate the dynamics of this proposed transoceanic migration, which is considered to be the longest regular non-stop migratory flight when accounting for body size. The energetic flight model suggests that a mixed strategy of gliding and active flapping would allow a globe skimmer to stay airborne for up to 230–286 h, assuming that the metabolic rate of gliding flight is close to that of resting. If engaged in continuous active flapping flight only, the flight time is severely reduced to ∼4 h. Relying only on self-powered flight (combining active flapping and gliding), a globe skimmer could cross the Indian Ocean, but the migration would have to occur where the ocean crossing is shortest, at an exceptionally fast gliding speed and with little headwind. Consequently, we deem this scenario unlikely and suggest that wind assistance is essential for the crossing. The wind trajectory analysis reveals intra- and inter-seasonal differences in availability of favorable tailwinds, with only 15.2% of simulated migration trajectories successfully reaching land in autumn but 40.9% in spring, taking on average 127 and 55 h respectively. Thus, there is a pronounced requirement on dragonflies to be able to select favorable winds, especially in autumn. In conclusion, a multi-generational, migratory circuit of the Indian Ocean by the globe skimmer is shown to be achievable, provided that advanced adaptations in physiological endurance, behavior and wind selection ability are present. Given that migration over the Indian Ocean would be heavily dependent on the assistance of favorable winds, occurring during a relatively narrow time window, the proposed flyway is potentially susceptible to disruption, if wind system patterns were to be affected by climatic change.

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“…Through the evolution over millions of years, remarkable flight abilities have developed with complex modes of locomotion [2]. The evolution of aerial locomotion was accompanied by the acquisition of anatomical and physiological adaptations in flapping flying [3][4][5]. The adaptions in birds include the fusion of parts of the skeleton, the pneumaticity of bones, and equipment of wings with strong yet lightweight feathers [6].…”

Section: Introductionmentioning

confidence: 99%

The Role of Vanes in the Damping of Bird Feathers

et al. 2023

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Bird feathers sustain bending and vibrations during flight. Such unwanted vibrations could potentially cause noise and flight instabilities. Damping could alter the system response, resulting in improving quiet flight, stability, and controllability. Vanes of feathers are known to be indispensable for supporting the aerodynamic function of the wings. The relationship between the hierarchical structures of vanes and the mechanical properties of the feather has been previously studied. However, still little is known about their relationship with feathers’ damping properties. Here, the role of vanes in feathers’ damping properties was quantified. The vibrations of the feathers with vanes and the bare shaft without vanes after step deflections in the plane of the vanes and perpendicular to it were measured using high-speed video recording. The presence of several main natural vibration modes was observed in the feathers with vanes. After trimming vanes, more vibration modes were observed, the fundamental frequencies increased by 51–70%, and the damping ratio decreased by 38–60%. Therefore, we suggest that vanes largely increase feather damping properties. Damping mechanisms based on the morphology of feather vanes are discussed. The aerodynamic damping is connected with the planar vane surface, the structural damping is related to the interlocking between barbules and barbs, and the material damping is caused by the foamy medulla inside barbs.

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The Importance of Flapping Kinematic Parameters in the Facilitation of the Different Flight Modes of Dragonflies

Cited by 15 publications

References 38 publications

Dragonfly-Inspired Wing Design Enabled by Machine Learning and Graphic Statics

Dragonfly-Inspired Wing Design Enabled by Machine Learning and Graphic Statics

Unraveling the World’s Longest Non-stop Migration: The Indian Ocean Crossing of the Globe Skimmer Dragonfly

The Role of Vanes in the Damping of Bird Feathers

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