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Flying insects are equipped with complex olfactory systems, which they utilize to seek food, identify mates, and evade predators. It is suspected that insects flap their wings to draw odor plumes toward their antennae, a behavior akin to mammals' sniffing, aimed at enhancing olfactory sensitivity. However, insects' wing kinematics change drastically as their flight speed increases, and it is unknown how these changes affect the insect's odorant perception. Addressing this gap in knowledge is crucial to a full understanding of the interplay between insects' aerodynamic performance and sensory perception. To this end, we simulated odor-tracking hawkmoth flight at 2 and 4 m/s using an in-house computational fluid dynamics solver. This solver incorporated both the Navier–Stokes equations that govern the flow, as well as the advection-diffusion equation that governs the odor transport process. Findings indicate that hawkmoths enhance odor intensity along their antennae using their wings, with peak odor intensity being 39% higher during 2 m/s flight compared to 4 m/s flight. This demonstrates there is a trade-off between rapid transport and olfaction, which is attributable to differences in wing kinematics between low- and high-speed flights. Despite literature suggesting hawkmoths are limited to steady forward flights at speeds below 5 m/s—about half of what is theoretically predicted based on body mass—this study reveals that slower flight speeds improve their olfactory capabilities during navigation. Our findings offer insights into the evolution of flight and sensory capabilities in hawkmoths, as well as provide inspiration for the development of bio-inspired odor-guided navigation technologies. 

Abstract As insects fly, their wings generate complex wake structures that play a crucial role in their aerodynamic force production. This study focuses on utilizing reduced order modeling techniques to gain valuable insights into the fluid dynamic principles underlying insect flight. Specifically, we used an immersed-boundary-method-based computational fluid dynamics (CFD) solver to simulate a hovering hawkmoth’s wake, and then identified the most energetic modes of the wake using proper orthogonal decomposition (POD). Furthermore, we employed a sparse identification of nonlinear dynamics (SINDy) approach to find a simple reduced order model that relates the most energetic POD modes. Through this process, we formulated multiple different models incorporating varying numbers of POD modes. To compare the accuracy of these models, we utilized a force survey method to estimate the aerodynamic forces produced by the hawkmoth’s wings. This force survey method uses an impulse-based approach to calculate the aerodynamic lift and drag based solely on the velocity and vorticity information provided by the model. By comparing the estimated aerodynamic force with the actual force production calculated by the CFD solver, we were able to find the simplest model that still provides an accurate representation of the complex wake produced by the hovering hawkmoth wings. We also evaluated the stability and accuracy of this model as the number of flapping cycles increases with time. The reduced order modeling of insect flight has important implications for the design and control of bio-inspired micro-aerial vehicles. In addition, it holds the potential to reduce the computational cost associated with high-fidelity CFD simulations of complex flows. 

Abstract A limiting factor in the design of smaller size uncrewed aerial vehicles is their inability to navigate through gust-laden environments. As a result, engineers have turned towards bio-inspired engineering approaches for gust mitigation techniques. In this study, the aerodynamics of a red-tailed hawk’s response to variable-magnitude discrete transverse gusts was investigated. The hawk was flown in an indoor flight arena instrumented by multiple high-speed cameras to quantify the 3D motion of the bird as it navigated through the gust. The hawk maintained its flapping motion across the gust in all runs; however, it encountered the gust at different points in the flapping pattern depending on the run and gust magnitude. The hawk responded with a downwards pitching motion of the wing, decreasing the wing pitch angle to between −20^∘and −5^∘, and remained in this configuration until gust exit. The wing pitch data was then applied to a lower-order aerodynamic model that estimated lift coefficients across the wing. In gusts slower than the forward flight velocity (low gust ratio), the lift coefficient increases at a low-rate, to a maximum of around 2–2.5. In gusts faster than the forward flight velocity (high gust ratio), the lift coefficient initially increased rapidly, before increasing at a low-rate to a value around 4–5. In both regimes, the hawk’s observed height change due to gust interaction was similar (and small), despite larger estimated lift coefficients over the high gust regime. This suggests another mitigation factor apart from the wing response is present. One potential factor is the tail pitching response observed here, which prior work has shown serves to mitigate pitch disturbances from gusts. 

Flying insects possess sophisticated olfactory systems that they use to find food, locate mates, and avoid predators. It is suspected that insects flap their wings to draw odor plumes toward their antennae. This behavior enhances their olfactory sensitivity and is analogous to sniffing in mammals. However, insects’ wing kinematics change drastically as their flight speed increases, and it is unknown how these changes affect the insect’s odorant perception. To address this question, we simulated odor-tracking hawkmoth fight at 2 m/s and 4 m/s using an in-house immersed-boundary-method-based CFD solver. The solver was used to solve the Navier-Stokes equations that govern the flow, as well as the advection-diffusion equation that governs the odor transport process. Results show that hawkmoths use their wings to significantly increase the odor intensity along their antennae. However, peak odor intensity is 39% higher during 2 m/s flight than 4 m/s flight. We therefore suspect that insects have greater olfactory performance at lower forward flight speed. Findings from this study could provide inspiration for bio-inspired odor-guided navigation technology. 

Many bird species commonly aggregate in flocks for reasons ranging from predator defense to navigation. Available evidence suggests that certain types of flocks—the V and echelon formations of large birds—may provide a benefit that reduces the aerodynamic cost of flight, whereas cluster flocks typical of smaller birds may increase flight costs. However, metabolic flight costs have not been directly measured in any of these group flight contexts [Zhang and Lauder,J. Exp. Biol.226, jeb245617 (2023)]. Here, we measured the energetic benefits of flight in small groups of two or three birds and the requirements for realizing those benefits, using metabolic energy expenditure and flight position measurements from European Starlings flying in a wind tunnel. The starlings continuously varied their relative position during flights but adopted a V formation motif on average, with a modal spanwise and streamwise spacing of [0.81, 0.91] wingspans. As measured via CO₂production, flight costs for follower birds were significantly reduced compared to their individual solo flight benchmarks. However, followers with more positional variability with respect to leaders did less well, even increasing their costs above solo flight. Thus, we directly demonstrate energetic costs and benefits for group flight followers in an experimental context amenable to further investigation of the underlying aerodynamics, wake interactions, and bird characteristics that produce these metabolic effects. 

It is generally accepted among biology and engineering communities that insects are unstable at hover. However, existing approaches that rely on direct averaging do not fully capture the dynamical features and stability characteristics of insect flight. Here, we reveal a passive stabilization mechanism that insects exploit through their natural wing oscillations: vibrational stabilization. This stabilization technique cannot be captured using the averaging approach commonly used in literature. In contrast, it is elucidated using a special type of calculus: the chronological calculus. Our result is supported through experiments on a real hawkmoth subjected to pitch disturbance from hovering. This finding could be particularly useful to biologists because the vibrational stabilization mechanism may also be exploited by many other creatures. Moreover, our results may inspire more optimal designs for bioinspired flying robots by relaxing the feedback control requirements of flight.