Insects rely on their olfactory system to forage, prey, and mate. They can sense odorant plumes emitted from sources of their interests with their bilateral odorant antennae, and track down odor sources using their highly efficient flapping-wing mechanism. The odor-tracking process typically consists of two distinct behaviors: surging upwind at higher velocity and zigzagging crosswind at lower velocity. Despite extensive numerical and experimental studies on odor guided flight in insects, we have limited understandings on the effects of flight velocity on odor plume structure and its associated odor perception. In this study, a fully coupled three-way numerical solver is developed, which solves the 3D Navier-Stokes equations coupled with equations of motion for the passive flapping wings, and the odorant convection-diffusion equation. This numerical solver is applied to resolve the unsteady flow field and the odor plume transport for a fruit fly model at different flight velocities in terms of reduced frequency. Our results show that the odor plume structure and intensity are strong related to reduced frequency. At smaller reduced frequency (larger forward velocity), odor plume is pushed up during downstroke and draw back during upstroke. At larger reduced frequency (smaller forward velocity), the flapping wings induce a shield-like air flow around the antennae which may greatly increase the odor sampling range. Our finding may explain why flight velocity is important in odor guided flight.
- Award ID(s):
- 1631864
- NSF-PAR ID:
- 10189717
- Date Published:
- Journal Name:
- Fluids
- Volume:
- 5
- Issue:
- 2
- ISSN:
- 2311-5521
- Page Range / eLocation ID:
- 82
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
more » « less
Abstract Insects rely on their olfactory system to forage, prey, and mate. They can sense odorant plumes emitted from sources of their interests with their bilateral odorant antennae, and track down odor sources using their highly efficient flapping-wing mechanism. The odor-tracking process typically consists of two distinct behaviors: surging upwind and zigzagging crosswind. Despite the extensive numerical and experimental studies on the flying trajectories and wing flapping kinematics during odor tracking flight, we have limited understanding of how the flying trajectories and flapping wings modulate odor plume structures. In this study, a fully coupled three-way numerical solver is developed, which solves the 3D Navier-Stokes equations coupled with equations of motion for the passive flapping wings, and the odorant convection-diffusion equation. This numerical solver is applied to investigate the unsteady flow field and the odorant transport phenomena of a fruit fly model in both surging upwind and zigzagging crosswind cases. The unsteady flow generated by flapping wings perturbs the odor plume structure and significantly impacts the odor intensity at the olfactory receptors (i.e., antennae). During zigzagging crosswind flight, the differences in odor perception time and peak odor intensity at the receptors potentially help create stereo odorant mapping to track odor source. Our simulation results will provide new insights into the mechanism of how fruit flies perceive odor landscape and inspire the future design of odor-guided micro aerial vehicles (MAVs) for surveillance and detection missions.
-
null (Ed.)When walking along a city street, you might encounter a range of scents and odors, from the smells of coffee and food to those of exhaust fumes and garbage. The odors are swept to your nose by air currents that move scents in two different ways. They carry them downwind in a process called advection, but they also mix them chaotically with clean air in a process called turbulence. What results is an odor plume: a complex ever-changing structure resembling the smoke rising from a chimney. Within a plume, areas of highly concentrated odor particles break up into smaller parcels as they travel further from the odor source. This means that the concentration of the odor does not vary along a smooth gradient. Instead, the odor arrives in brief and unpredictable bursts. Despite this complexity, insects are able to use odor plumes with remarkable ease to navigate towards food sources. But how do they do this? Answering this question has proved challenging because odor plumes are usually invisible. Over the years, scientists have come up with a number of creative solutions to this problem, including releasing soap bubbles together with odors, or using wind tunnels to generate simpler, straight plumes in known locations. These approaches have shown that when insects encounter an odor, they surge upwind towards its source. When they lose track of the odor, they cast themselves crosswind in an effort to regain contact. But this does not explain how insects are able to navigate irregular odor plumes, in which both the timing and location of the odor bursts are unpredictable. Demir, Kadakia et al. have now bridged this gap by showing how fruit flies are attracted to smoke, an odorant that is also visible. By injecting irregular smoke plumes into a custom-built wind tunnel, and then imaging flies as they walked through it, Demir, Kadakia et al. showed that flies make random halts when navigating the plume. Each time they stop, they use the timing of the odor bursts reaching them to decide when to start moving again. Rather than turning every time they detect an odor, flies initiate turns at random times. When several odor bursts arrive in a short time, the flies tend to orient these turns upwind rather than downwind. Flies therefore rely on a different strategy to navigate irregular odor plumes than the ‘surge and cast’ method they use for regular odor streams. Successful navigation through complex irregular plumes involves a degree of random behavior. This helps the flies gather information about an unpredictable environment as they search for the source of the odor. These findings may help to understand how other insects use odor to navigate in the real world, for example, how mosquitoes track down human hosts.more » « less
-
more » « less
Odor-guided navigation is fundamental to the survival and reproductive success of many flying insects. Despite its biological importance, the mechanics of how insects sense and interpret odor plumes in the presence of complex flow fields remain poorly understood. This study employs numerical simulations to investigate the influence of turbulence, wingbeat-induced flow, and Schmidt number on the structure and perception of odor plumes by flying insects. Using an in-house computational fluid dynamics solver based on the immersed-boundary method, we solve the three-dimensional Navier–Stokes equations to model the flow field. The solver is coupled with the equations of motion for passive flapping wings to emulate wingbeat-induced flow. The odor landscape is then determined by solving the odor advection–diffusion equation. By employing a synthetic isotropic turbulence generator, we introduce turbulence into the flow field to examine its impact on odor plume structures. Our findings reveal that both turbulence and wingbeat-induced flow substantially affect odor plume characteristics. Turbulence introduces fluctuations and perturbations in the plume, while wingbeat-induced flow draws the odorant closer to the insect’s antennae. Moreover, we demonstrate that the Schmidt number, which affects odorant diffusivity, plays a significant role in odor detectability. Specifically, at high Schmidt numbers, larger fluctuations in odor sensitivity are observed, which may be exploited by insects to differentiate between various odorant volatiles emanating from the same source. This study provides new insights into the complex interplay between fluid dynamics and sensory biology and behavior, enhancing our understanding of how flying insects successfully navigate using olfactory cues in turbulent environments.
-
In nature, olfactory signals are delivered to detectors—for example, insect antennae—by means of turbulent air, which exerts concurrent chemical and mechanical stimulation on the detectors. The antennal lobe, which is traditionally viewed as a chemosensory module, sits downstream of antennal inputs. We review experimental evidence showing that, in addition to being a chemosensory structure, antennal lobe neurons also respond to mechanosensory input in the form of wind speed. Benchmarked with empirical data, we constructed a dynamical model to simulate bimodal integration in the antennal lobe, with model dynamics yielding insights such as a positive correlation between the strength of mechanical input and the capacity to follow high frequency odor pulses, an important task in tracking odor sources. Furthermore, we combine experimental and theoretical results to develop a conceptual framework for viewing the functional significance of sensory integration within the antennal lobe. We formulate the testable hypothesis that the antennal lobe alternates between two distinct dynamical regimes, one which benefits odor plume tracking and one which promotes odor discrimination. We postulate that the strength of mechanical input, which correlates with behavioral contexts such being mid-flight versus hovering near a flower, triggers the transition from one regime to the other.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/fluids5020082
