Aquatic animals have developed effective strategies to reduce their body drag over a long period of time. In this work, the influence of the scales of fish on the laminar-to-turbulent transition in the boundary layer is investigated. Arrays of biomimetic fish scales in typical overlapping arrangements are placed on a flat plate in a low-turbulence laminar water channel. Transition to turbulence is triggered by controlled excitation of a Tollmien–Schlichting (TS) wave. It was found that the TS wave can be attenuated with scales on the plate which generate streamwise streaks. As a consequence, the transition location was substantially delayed in the downstream direction by 55% with respect to the uncontrolled reference case. This corresponds to a theoretical drag reduction of about 27%. We thus hypothesize that fish scales can stabilize the laminar boundary layer and prevent it from early transition, reducing friction drag. This technique can possibly be used for bio-inspired surfaces as a laminar flow control means.

The surface topology of the scale pattern from the European Sea Bass (Dicentrarchus labrax ) was measured using a digital microscope and geometrically reconstructed using Computer Assisted Design modelling. Numerical flow simulations and experiments with a physical model of the surface pattern in a flow channel mimic the flow over the fish surface with a laminar boundary layer. The scale array produces regular rows of alternating, streamwise low-speed and high-speed streaks inside the boundary layer close to the surface, with maximum velocity difference of about 9%. Low-velocity streaks are formed in the central region of the scales whereas the high-velocity streaks originated in the overlapping region be- tween the scales. Thus, those flow patterns are linked to the arrangement and the size of the overlapping scales within the array. Because of the velocity streaks, total drag reduction is found when the scale height is small relative to the boundary layer thickness, i.e. less than 10%. Flow simulations results were compared with surface oil-flow visualisations on the physical model of the biomimetic surface placed in a flow channel. The results show an excellent agreement in the size and arrangement of the streaky structures. The existence of streaks is also proven on sea bass (Dicentrarchus labrax ) and common carp (Cyprinus carpio) by surface flow visualisation. From comparison to recent literature about micro-roughness effects on laminar boundary layer flows it is hypothesized that the fish scales could delay transition which would further reduce the drag.

Pinnipeds like seals and sea lions use their whiskers to hunt their prey in dark and turbid situations. There is currently no theoretical model or hypothesis to explain the interaction between whiskers and hydrodynamic fish trails. The current study, however, provides a theoretical and experimental insight into the mechanism behind the detection of the Strouhal frequency from a Von-Karman vortex street, similar to that of the inverted hydrodynamic fish trail. Herein the flow around a 3D printed sea lion head, with integrated whiskers of comparable geometry and material properties to a real seal lion, is investigated when exposed to vortex streets generated by cylindrical bluff bodies. The whiskers respond to the vortices with a jerky motion, analogous to the stick-slip response of rat whiskers; this motion is found to be the time derivative of the Gaussian function. Compared to the displacement response, the time-derivative of the whisker response decodes the Strouhal frequency of the Von-Karman wake, which improves the sensing efficiency in noisy environments. The study hypothesizes that the time derivative of the whisker bending moment is the best physical variable that can be used as the input to the pinnipeds neural system.

This work describes a novel mechanism of laminar flow control of straight and backward swept wings with a comb-like leading edge (LE) device. It is inspired by the LE comb on owl feathers and the special design of its barbs, resembling a cascade of complex 3D-curved thin finlets. The details of the geometry of the barbs from an owl feather were used to design a generic model of the comb for experimental and numerical flow studies with the comb attached to the LE of a flat plate. Due to the owls demonstrating a backward sweep of the wing during gliding and flapping from live recordings, our examinations have also been carried out at differing sweep angles. The results demonstrate a flow turning effect in the boundary layer inboards, which extends downstream in the chordwise direction over distances of multiples of the barb lengths. The inboard flow-turning effect described here, counter-acts the outboard directed cross-span flow typically appearing for backward swept wings. This flow turning behaviour is also shown on SD7003 airfoil using precursory LES investigations. From recent theoretical studies on a swept wing, such a way of turning the flow in the boundary layer is known to attenuate crossflow instabilities and delay transition. A comparison of the comb-induced cross-span velocity profiles with those proven to delay laminar to turbulent transition in theory shows excellent agreement, which supports the laminar flow control hypothesis. Thus, the observed effect is expected to delay transition in owl flight, contributing to a more silent flight.

Various marine animals possess the ability to track their preys and navigate dark aquatic environments using hydrodynamic sensing of the surrounding flow. In the present study, a deep-learning model is applied to a biomimetic sensor for underwater position detection of a wake-generating body. The sensor is composed of a bundle of spatially-distributed optical fibers that act as artificial seal-like whiskers and interact with the body’s wake in the form of time-variant (bending) deflections. Supervised learning is employed to relate the vibrations of the artificial whiskers to the position of an upstream cylinder. The labeled training data are prepared based on the processing and reduction of the recorded bending responses of the artificial whiskers while the cylinder is placed at various locations. An iterative training algorithm is performed on two neural-network models while using the 10-fold cross-validation technique. The models are able to predict the coordinates of the cylinder in the two-dimensional (2D) space with a high degree of accuracy. The current implementation of the sensor can passively sense the wake generated by the cylinder at Re ≃ 6000 and estimate its position with an average error smaller than the characteristic diameter D of the cylinder and for inter-distances (in the water tunnel) up to 25-times D.

(1) Background: Sensing of critical events or flow signatures in nature often presents itself as a coupled interaction between a fluid and arrays of slender flexible beams, such a wind-hairs or whiskers. It is hypothesized that important information is gained in highly noisy environments by the inter-correlation within the array. (2) Methods: The present study uses a model sea lion head with artificial whiskers in the form of slender beams (optical fibres), which are subjected to a mean flow with overlaid turbulent structures generated in the wake of a cylinder. Motion tracking of the array of fibres is used to analyse the correlation of the bending deformations of pairs of fibres. (3) Results: Cross-correlation of the bending signal from tandem pairs of whiskers proves that the detection of vortices and their passage along the animals head is possible even in noisy environments. The underlying pattern, during passage of a vortex core, is a jerk-like response of the whiskers, which can be found at later arrival-times in similar form in the downstream whisker’s response. (4) Conclusions: Coherent vortical structures can be detected from cross-correlation of pairs of cantilever-beam like sensors even in highly turbulent flows. Such vortices carry important information within the environment, e.g., the underlying convection velocity. More importantly in nature, these vortices are characteristic elementary signals left by prey and predators. The present work can help to further develop flow, or critical event, sensory systems which can overcome high noise levels due to the proposed correlation principle.