A computational fluid dynamics model of viscous coupling of hairs

The mechanics and interactions of electrically sensitive mechanoreceptive hair arrays of arthropods

Recent investigations highlight the possibility of electroreception within arthropods through charged mechanosensory hairs. This discovery raises questions about the influence of electrostatic interaction between hairs and surrounding electrical fields within this sensory modality. Here, we investigate these questions by studying electrostatic coupling in arrays of hairs. We establish the notion of sensitivity contours that indicate regions within which point charges deflect hairs beyond a given threshold. We then examine how the contour’s shape and size and the overall hair behaviour change in response to variations in the coupling between hairs. This investigation unveils synergistic behaviours whereby the sensitivity of hairs is enhanced or inhibited by neighbouring hairs. The hair spacing and ratio of a system’s electrical parameters to its mechanical parameters influence this behaviour. Our results indicate that electrostatic interaction between hairs leads to emergent sensory properties for biologically relevant parameter values. The analysis raises new questions around the impact of electrostatic interaction on the current understanding of sensory hair processes, such as acoustic sensing, unveiling new sensory capabilities within electroreception such as amplification of hair sensitivity and location detection of charges in the environment.

Bumblebee hairs as electric and air motion sensors: theoretical analysis of an isolated hair

Foraging bumblebees are electrically charged. Charge accumulation has been proposed to enable their ability to detect and react to electrical cues. One mechanism suggested for bumblebee electro-sensing is the interaction between external electric fields and electric charges accumulating on fine hairs on the cuticular body. Such hairs exhibit several functional adaptations, for example, thermal insulation, pollen capture and notably, the sensing of air motion such as flow currents or low frequency sound particle velocity. Both air motion and electric fields are ubiquitous in the sensory ecology of terrestrial arthropods, raising the question as to whether cuticular hairs respond to both stimuli. Here, a model-theoretical approach is taken to investigate the capacity of bumblebee filiform hairs as electric sensors and compare it to their response to air motion. We find that oscillating air motion and electric fields generate different mechanical responses, depending on stimulus frequency and body geometry. Further, hair morphology can enhance one sensing mode over the other; specifically, higher surface area favours electric sensitivity. Assuming a maximum stable charge on the hair that is limited only by electric breakdown of air, it is expected that an applied oscillating electric field strength of approximately 300 V m-1 produces comparable mechanical response on the hair as a 35 mm s-1 air flow oscillating at 130 Hz-an air disturbance signal similar to that produced by wingbeats of insects within a few bodylengths of the bumblebee. This analysis reveals that bumblebee filiform hairs can operate as bi-modal sensors, responding to both oscillating electric and air motion stimuli in the context of ecologically relevant scenarios.

Biomechanics in Soft Mechanical Sensing: From Natural Case Studies to the Artificial World

Living beings use mechanical interaction with the environment to gather essential cues for implementing necessary movements and actions. This process is mediated by biomechanics, primarily of the sensory structures, meaning that, at first, mechanical stimuli are morphologically computed. In the present paper, we select and review cases of specialized sensory organs for mechanical sensing-from both the animal and plant kingdoms-that distribute their intelligence in both structure and materials. A focus is set on biomechanical aspects, such as morphology and material characteristics of the selected sensory organs, and on how their sensing function is affected by them in natural environments. In this route, examples of artificial sensors that implement these principles are provided, and/or ways in which they can be translated artificially are suggested. Following a biomimetic approach, our aim is to make a step towards creating a toolbox with general tailoring principles, based on mechanical aspects tuned repeatedly in nature, such as orientation, shape, distribution, materials, and micromechanics. These should be used for a future methodical design of novel soft sensing systems for soft robotics.

Functional role of airflow-sensing hairs on the bat wing

The wing membrane of the big brown bat (Eptesicus fuscus) is covered by a sparse grid of microscopic hairs. We showed previously that various tactile receptors (e.g., lanceolate endings and Merkel cell neurite complexes) are associated with wing-hair follicles. Furthermore, we found that depilation of these hairs decreased the maneuverability of bats in flight. In the present study, we investigated whether somatosensory signals arising from the hairs carry information about airflow parameters. Neural responses to calibrated air puffs on the wing were recorded from primary somatosensory cortex of E. fuscus Single units showed sparse, phasic, and consistently timed spikes that were insensitive to air-puff duration and magnitude. The neurons discriminated airflow from different directions, and a majority responded with highest firing rates to reverse airflow from the trailing toward the leading edge of the dorsal wing. Reverse airflow, caused by vortices, occurs commonly in slowly flying bats. Hence, the present findings suggest that cortical neurons are specialized to monitor reverse airflow, indicating laminar airflow disruption (vorticity) that potentially destabilizes flight and leads to stall.

NEW & NOTEWORTHY

Bat wings are adaptive airfoils that enable demanding flight maneuvers. The bat wing is sparsely covered with sensory hairs, and wing-hair removal results in reduced flight maneuverability. Here, we report for the first time single-neuron responses recorded from primary somatosensory cortex to airflow stimulation that varied in amplitude, duration, and direction. The neurons show high sensitivity to the directionality of airflow and might act as stall detectors.

Morphology and deflection properties of bat wing sensory hairs: scanning electron microscopy, laser scanning vibrometry, and mechanics model

Bat wings are highly adaptive airfoils that enable demanding flight maneuvers, which are performed with astonishing robustness under turbulent conditions, and stability at slow flight velocities. The bat wing is sparsely covered with microscopically small, sensory hairs that are associated with tactile receptors. In a previous study we demonstrated that bat wing hairs are involved in sensing airflow for improved flight maneuverability. Here, we report physical measurements of these hairs and their distribution on the wing surface of the big brown bat, Eptesicus fuscus, based on scanning electron microscopy analyses. The wing hairs are strongly tapered, and are found on both the dorsal and ventral wing surfaces. Laser scanning vibrometry tests of 43 hairs from twelve locations across the wing of the big brown bat revealed that their natural frequencies inversely correlate with length and range from 3.7 to 84.5 kHz. Young's modulus of the average wing hair was calculated at 4.4 GPa, which is comparable with rat whiskers or arthropod airflow-sensing hairs.

Application of a lattice Boltzmann-immersed boundary method for fluid-filament dynamics and flow sensing

Complex fluid-structure interactions between elastic filaments, or cilia, immersed in viscous flows are commonplace in nature and bear important roles. Some biological systems have evolved to interpret flow-induced motion into signals for the purpose of feedback response. Given the challenges associated with extracting meaningful experimental data at this scale, there has been particular focus on the numerical study of these effects. Porous models have proven useful where cilia arrangements are relatively dense, but for more sparse configurations the dynamic interactions of individual structures play a greater role and direct modelling becomes increasingly necessary. The present study reports efforts towards explicit modelling of regularly spaced wall-mounted cilia using a lattice Boltzmann-immersed boundary method. Both steady and forced unsteady 2D channel flows at different Reynolds numbers are investigated, with and without the presence of a periodic array of elastic inextensible filaments. It is demonstrated that the structure response depends significantly on Reynolds number. For low Reynolds flow, the recirculation vortex aft of successive filaments is small relative to the cilia spacing and does not fully bridge the gap, in which case the structure lags the flow. At higher Reynolds number, when this gap is fully bridged the structure and flow move in phase. The trapping of vortices between cilia is associated with relatively lower wall shear stress. At low to intermediate Reynolds, vortex bridging is incomplete and large deflection is still possible, which is reflected in the tip dynamics and wall shear stress profiles.

Air motion sensing hairs of arthropods detect high frequencies at near-maximal mechanical efficiency

Using measurements based on particle image velocimetry in combination with a novel compact theoretical framework to describe hair mechanics, we found that spider and cricket air motion sensing hairs work close to the physical limit of sensitivity and energy transmission in a broad range of relatively high frequencies. In this range, the hairs closely follow the motion of the incoming flow because a minimum of energy is dissipated by forces acting in their basal articulation. This frequency band is located beyond the frequency at which the angular displacement of the hair is maximum which is between about 40 and 600 Hz, depending on hair length (Barth et al. [1] Phil. Trans. R. Soc. Lond. B 340, 445-461 (doi:10.1098/rstb.1993.0084)). Given that the magnitude of natural airborne signals is known to decrease with frequency, our results point towards the possible existence of spectral signatures in the higher frequency range that may be weak but of biological significance.

Why do insects have such a high density of flow-sensing hairs? Insights from the hydromechanics of biomimetic MEMS sensors

Insects and arachnids are often quite hairy. The reasons for this high density of sensory hairs are unknown. Previous studies have predicted strong hydrodynamic coupling between densely packed airflow-sensitive hairs. Flow perturbation owing to single hairs and between tandem hairs, however, has never been experimentally measured. This paper aims to quantify the extent of flow perturbation by single and tandem hairs directly, using biomimetic microelectromechanical system (MEMS) hairs as physical models and particle image velocimetry (PIV) for flow visualization. Single and tandem MEMS hairs of varying interhair distances were subjected to oscillatory flows of varying frequency. Decreasing hair-to-hair distance markedly reduced flow velocity amplitude and increased the phase shift between the far-field flow and the flow between hairs. These effects were stronger for lower flow frequencies. We predict strong hydrodynamic coupling within whole natural hair canopies exposed to natural stimuli, depending on arthropod and hair sizes, and hair density. Thus, rather than asking why arthropods have so many hairs, it may be useful to address why hairs are packed together at such high densities, particularly given the exquisite sensitivity of a single hair.