Session A35: Biofluids: Flying Insects

Antenna Morphology Impacts Drag Forces During Olfaction

Insects navigate environments to avoid predators, forage for food, and find mates via olfactory sensing using chemoreceptors on their antennae. Different species have evolved unique antennae morphologies; differences include sensilla density & structure, antennae curvature, segmentation, and size. We categorized the biomechanics of prototypical antennae for a honeybee, cockroach, cockroach nymph, locust, and parasitic wasp. Using numerical simulations of airflow around the antennae of different insects, we computed antennal drag forces and compared them with that of an idealized cylinder shape. We find that morphological differences contribute to varying drag forces across species. Understanding drag forces are foundational to facilitating studies of antenna morphology impacting energetics during olfactory navigation.   

Flight and Smell: Exploring the Impact of Wing Structure and Kinematics on the Olfactory Function of Flies in Upwind Surging Flight

One of the most ancient, conserved behaviors in animals is using wind-borne odor plumes to track food, mates, and predators. Insects, particularly flies, exhibit a high level of proficiency in this, processing complex odor information like concentrations, direction, and speed, through their olfactory system for effective odor-guided navigation. Extensive research has illuminated the influence of wing structure and kinematics on the aerodynamics and flow field physics of flying insects in recent years. However, the interplay between the flow field and olfactory functions remains uncharted territory, inviting intriguing questions. For instance, do flies intentionally manipulate the flow field around their antennae using their wing structure and kinematics to enhance their olfactory abilities? To investigate this, we conducted CFD simulations on blue bottle flies (C. vomitoria) forward flight by using an in-house immersed-boundary-method-based CFD solver. By using high-speed video recordings, we reconstruct the wing shape and kinematics of the fly. Results suggested that flies utilize their wing structure and kinematics to manipulate flow physics to increase odor concentrations around their antennae. Remarkably, the flapping motion enabled a significant enhancement in the odor-mass flux reaching to their olfactory receptors compared to the case without flapping motion.   

Cubic scaling of thrust production with Strouhal number in tethered insect flight

A successful existing model for the scaling of the thrust coefficient of flapping wings was derived from Theodorsen’s theory, and results in a St² scaling and strong Reynolds number dependence. In the present work, we proposed a new model based on von Karman and Sears, that exhibits St³ scaling, the addition of reduced frequency, and limited Reynolds number dependence. Despite the significant differences in derivation and in algebraic form, the two models both exhibit comparable performance in modelling our sample data set, containing the thrust and wing kinematics of a large number (N=38) of individual mountain pine beetle specimens, recorded over 168 individual flights. The scaling of both models with Strouhal number produces similar thrust estimates across a limited range of Strouhal numbers near our experimental conditions, before diverging at large values (St > 10).

In addition to modelling thrust coefficient, our proposed model can provide an explicit estimate for circulation and circulation growth in the wake. Nevertheless, future work must investigate how scaling across reduced frequency and Reynolds number each masks the effect of the other term in these distinct models, as Theodorsen theory and von Karman and Sears theory share significant theoretical basis.   

Data-driven Bayesian olfactory search in turbulent flows

A number of animals depend on an ability to locate the source of chemical cues which are advected by a macroscopic flow, including certain flying insects and aquatic animals. This search problem is complicated by turbulence, which randomizes cue encounters and renders gradient estimation slow and inefficient. Previous work has shown the problem can be modeled as a partially observable Markov decision process (POMDP), which was then solved assuming a simple model for the statistics of encounters [1,2,3], but the question of searching in a more realistic flow—where correlations may be important, violating the Markov assumption—was left open. In this work, we perform high-fidelity direct numerical simulations of a flow with mean wind, while tracking Lagrangian tracers which are emitted from a point source. The tracers are taken as a proxy for a chemical cue, and the simulation data are used to extract the statistics of encounters (we discuss how best to do this). We solve an extended POMDP which includes short-range (exponential in time) correlations between consecutive encounters, and compare the search performance of the resulting strategies to those computed while ignoring correlations. We demonstrate, using both empirical results and physical arguments, that the presence of correlations fundamentally impedes the search, fattening the tail of the arrival time distribution. We also show how this effect depends on the movement speed of the agent and the threshold concentration for detection.

 

[1] A. Loisy and C. Eloy. Proceedings of the Royal Society A 478, 20220118 (2022). 

[2] A. Loisy and R. A. Heinonen. The European Physical Journal E 46, 17 (2023). 

[3] R. A. Heinonen, L. Biferale, A. Celani, and M. Vergassola. Physical Review E 107, 055105 (2023).    

Multi-objective optimization of the wing shape and kinematics of a hovering flapping wing.

 We investigate optimal wing shapes and kinematics of a hovering flapping flight using multi-objective optimization considering vertical force generation and flight power consumption. Given wing aspect ratio of 5 and Reynolds number of 100 (based on the wing mean chord length and wing tip velocity), a Pareto front of the optimal wing shapes and kinematics is obtained using a quasi-steady aerodynamic model (Oh et al. JFM, 2020) together with a non-dominated sorting genetic algorithm (NSGA-II). The results indicate that optimal wing shapes and kinematics can be classified into three different categories based on the purposes of flight (minimization of mechanical power coefficient, maximization of vertical force coefficient, and maximization of flight efficiency). Furthermore, these classifications are qualitatively valid even for different Reynolds numbers and aspect ratios. Lastly, the optimization results are compared to real insect flapping flights.   

Fluid-structure interaction modeling of fruit fly wings in hovering flight

Insect wings, known for their intricate structure and function, inherently deform during flapping motion. These deformations can be classified into chordwise cambering, spanwise bending, and root-to-tip twisting, arising due to non-uniform venation distribution, aerodynamic loading, and wing inertia. Crucially, these deformations contribute significantly to the aerodynamic performance of the wings. To investigate how insects passively achieve the desired deformation, in this study, a fully coupled three-dimensional fluid-structure interaction (FSI) solver was developed. The solver integrates an open-source Vega FEM code to solve solid structure dynamics equations with an in-house Navier-Stokes equations solver for determining the flow field. Numerical simulations on the deformation of flapping wing models during hovering were conducted. The wing root and leading-edge were assumed to be rigid, while the other part of the wing is flexible and deforms due to aerodynamic forces and wing inertia. Effects of various parameters, including stiffness, venation structure, and wing inertia, on the deformation and aerodynamic performance of the wing were analyzed. Results show that there exists an optimal wing stiffness that maximizes both the lift and lift-to-power ratio of the deformed wing. The vein structure stores the strain energy and enhances the aerodynamic performance. Our findings in flapping-wing deformations may provide us with new insights into insect-size flapping-wing robots.   

Reduced Order Modeling of Wake Structures in Hawkmoth Hovering Flight

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 reduced order model that correlates these energetic POD modes. Based on the wake predicted by the SINDy models, we estimated the lift generated by the hawkmoth's wings using a force survey method. By comparing the estimated aerodynamic force with the force production calculated by the CFD solver, we can evaluate the accuracy of various SINDy models. 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.   

Free Flight Simulations of Inertial Effects in Insect Flight

We investigate the role of inertial effects in insect flight. Previous work has examined how the hinge position of the wing and flight kinematic parameters optimize flight. Here, we use a free flight model (PNAS 2014, JFM 2018) to investigate the effect of body and wing inertia on dynamics and stability. We report two sets of simulation results. The first set varies the insect mass and pitching moment of inertia independently. The second set varies the wing to body mass ratio (WBMR) while constraining total insect mass to be constant. To understand the simulation results, we apply a simplified 2 point mass model (JFM 2018). This model explains observed minima in the pitching of the insect as we vary the WBMR due to the canceling of aerodynamic and inertial torque terms, and can be closely related to previous results which varied wing hinge position (JFM 2018). We further discuss simulation results that cannot be explained by the simple model, such as a maximum instability when varying the pitching moment of inertia. 

S. Chang and Z. J. Wang, Proc. Natl. Acad. Sci. U.S.A. 111, 11246–11251 (2014).

R.M. Noest and Z. J. Wang, Journal of Fluid Mechanics 849, 498 (2018).   

Bottom-up butterfly model with thorax-pitch control and wing-pitch flexibility

Despite the diversity in the morphology of butterflies, the wing and body kinematics of butterflies have several common features. In the present study, we construct a bottom-up butterfly model whose morphology and kinematics are simplified while preserving the important features of butterflies. The present bottom-up butterfly model is composed of two trapezoidal wings and a rod-shaped body having a thorax and abdomen, and its wings are flapped downward in the downstroke and backward in the upstroke by changing the geometric angle of attack. The geometric angle of attack is determined by the thorax-pitch angle and wing-pitch angle. The thorax-pitch angle is actively controlled by the abdomen undulation, and the wing-pitch angle is passively determined due to a rotary spring representing the basalar and subalar muscles connecting the wings and thorax. We investigate how effective the abdomen undulation is for the thorax-pitch control and how the wing-pitch flexibility affects aerodynamic-force generation and thorax-pitch control, through numerical simulations using the immersed boundary-lattice Boltzmann method. As a result, the thorax-pitch angle perfectly follows the desired angle by the abdomen undulation. In addition, there is an optimal wing-pitch flexibility that maximizes flying speeds in both forward and upward directions, but the effect of wing-pitch flexibility is not significant on the thorax-pitch control.