Bomphrey, R. | bioRxiv Science

bioRxiv2021

Complete neuroanatomy and sensor maps of Odonata wings for fly-by-feel flight control

Can mechanosensors in animal wings allow reconstruction of the wing aeroelastic states? Little is known about how flying animals utilize wing mechanosensation to monitor the dynamic state of their highly deformable wings. Odonata, dragonflies and damselflies, are a basal lineage of flying insects with excellent flight performance, and their wing mechanics have been studied extensively. Here, we present a comprehensive map of the wing sensory system for two Odonata species, including both the external sensor morphologies and internal neuroanatomy. We identified eight morphological classes of sensors; most were mechanosensors innervated by a single neuron. Their innervation patterns and morphologies minimize axon length and allow morphological latency compensation. We further mapped the major veins of another 13 Odonata species across 10 families and identified consistent sensor distribution patterns, with sensor count scaling with wing length. Finally, we constructed a high-fidelity finite element model of a dragonfly wing for structural analysis. Our dynamic loading simulations revealed features of the strain fields that wing sensor arrays could detect to encode different wing deformation states. Taken together, this work marks the first step toward an integrated understanding of fly-by-feel control in animal flight.

neuroscience↗

bioRxiv2020

Virtual manipulation of bird tail postures demonstrates drag minimisation when gliding

Aerodynamic function of the avian tail has previously been studied using observations of bird flight, physical models in wind tunnels, theoretical modelling and flow visualization. However, none of these approaches has provided rigorously quantitative evidence concerning tail functions since: appropriate manipulation and controls cannot be achieved using live animals; and the aerodynamic interplay with wings and body challenges reductive theoretical or physical modelling approaches. Here, we have developed a comprehensive analytical drag model, calibrated by high-fidelity computational fluid dynamics (CFD), and used it to investigate the aerodynamic action of the tail by virtually manipulating its posture. The bird geometry used for CFD was reconstructed previously using stereo photogrammetry of a freely gliding barn owl and validated against wake measurements. Using this CFD-calibrated drag model, we predicted the drag production for 16 gliding flights with a range of tail postures. These observed postures are set in the context of a wider parameter sweep of theoretical postures, where the tail spread and elevation angles were manipulated virtually. The observed postures of our gliding bird corresponded to near minimal total drag.Author Summary The aerodynamic contribution of bird tails is challenging to study; strong interactions between wings, body and tail make models isolating the contributions of different body parts difficult to interpret. Further, methods for direct manipulation are limited, and confounding compensation is likely in live, free-flying birds. To circumvent these issues, we applied high-fidelity CFD to a range of measured gliding owl geometries in order to develop a comprehensive analytical drag model. This enabled the drag implications of virtually-manipulated tail postures to be explored. The theoretical postures that cause minimum drag match those used by owls. The drag model demonstrates the importance of the viscous component of drag, which is of particular relevance to fliers at the scale of birds and, increasingly, smaller UAVs.View Full Text

animal behavior and cognition↗