A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flow

Abstract

For underwater vehicles to successfully detect and navigate turbulent flows, sensing the fluid interactions that occur is required. Fish possess a unique sensory organ called the lateral line. Sensory units called neuromasts are distributed over their body, and provide fish with flow-related information. In this study, a three-dimensional fish-shaped head, instrumented with pressure sensors, was used to investigate the pressure signals for relevant hydrodynamic stimuli to an artificial lateral line system. Unsteady wakes were sensed with the objective to detect the edges of the hydrodynamic trail and then explore and characterize the periodicity of the vorticity. The investigated wakes (Kármán vortex streets) were formed behind a range of cylinder diameter sizes (2.5, 4.5 and 10 cm) and flow velocities (9.9, 19.6 and 26.1 cm s 21 ). Results highlight that moving in the flow is advantageous to characterize the flow environment when compared with static analysis. The pressure difference from foremost to side sensors in the frontal plane provides us a useful measure of transition from steady to unsteady flow. The vortex shedding frequency (VSF) and its magnitude can be used to differentiate the source size and flow speed. Moreover, the distribution of the sensing array vertically as well as the laterally allows the Kármán vortex paired vortices to be detected in the pressure signal as twice the VSF.

Biomimetic Survival Hydrodynamics and Flow Sensing

“…They concluded that fish might be able to extract sensory information from complex stimuli like vortices by comparing the activity of a whole array of neuromasts A number of authors have established the feasibility of tracking vortices and vortical wakes: Yang et al (2006) for vortical wakes; Ren & Mohseni (2012) for regular or reverse Kármán vortex street using CN-like sensors distributed over the surface of a body, which provide sufficient information to extract the circulation of individual vortices, the wavelength of the Kármán street, the distance between the body and the fish h and the speed of propagation of the street. Likewise, Akanyeti et al (2011);Venturelli et al (2012); Salumae &Kruusmaa (2013), andChambers et al (2014) demonstrated using an array of pressure sensors that it is feasible to extract features from the flow such as the vortex shedding frequency, traveling speed, wake wavelength, and turbulence intensity. Fernandez et al (2011a) determined the strength and position of a free vortex pair translating near a streamlined body using sparse pressure sensor measurements and a potential flow model with an extended Kalman filter, comparing it to simultaneous PIV measuremnts.…”

Artificial fish skin of self-powered micro-electromechanical systems hair cells for sensing hydrodynamic flow phenomena

“…Tiny hair cell bundles constitute the basic functional elements of all these sensors which translate mechanical stimuli into the electrical signals across the cell membrane [1,4,5]. The lateral-line system in fish and amphibians basically uses arrays of hair cell sensors for flow velocity and flow direction sensing [6,7] and the hair cells in limb joints of insects allow them to detect the orientation of their angled leg joints [8,9]. Despite the rich functionality and diversity in sensing applications, the fundamental sensing principle of all the biological hair cells is similar.…”

Form and function of the teleost lateral line revealed using three-dimensional imaging and computational fluid dynamics

“…Previous studies investigated local flow fields that surround swimming fishes [35], spatial noise suppression by complex lateral line systems [36], bulk water flow sensing [37], spatial integration by canal structures [38], detection of Kármán vortex streets [39], dipole source localization [40,41], as well as hydrodynamic imaging [42][43][44][45]. However, in order not to influence the results through the presence of a measuring probe such as a hydrophone or a hot-wire anemometer, the evaluation of parameters has to be performed by means of mathematical modelling.…”