Bioinspired Sensory Systems for Shear Flow Detection

Abstract

Aquatic organisms such as copepods exhibit remarkable responses to changes in ambient flows, especially shear gradients, when foraging, mating and escaping. To accomplish these tasks, the sensory system of the organism must decode the local sensory measurements to detect the flow properties. Evidence suggests that organisms sense differences in the hydrodynamic signal rather than absolute values of the ambient flow. In this paper, we develop a mathematical framework for shear flow detection using a bioinspired sensory system that measures only differences in velocity. We show that the sensory system is capable of reconstructing the properties of the ambient shear flow under certain conditions on the flow sensors. We discuss these conditions and provide explicit expressions for processing the sensory measurements and extracting the flow properties. These findings suggest that by combining suitable velocity sensors and physics-based methods for decoding sensory measurements, we obtain a powerful approach for understanding and developing underwater sensory systems.