Investigation of grid effects on surfaces with sensor hairs for selective acquisition of characteristic flow-field patterns (coincidence detector)

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Hair-like sensor structures which detect fluid motions close to a body are typically arranged in groups on many animals. Particular features are noticeable, e.g., the orientation of sensor hairs and their characteristic arrangement. Based on the most recent investigations of such creatures it can be assumed that such specific orientations and group arrangements of hairs - comparable to a grid or an array of rod-like wall-bound structures - may, on one hand, pre-condition the sensor signals, on the other hand, play a role in signal filtering. Both effects together will be called grid effects herein. Signal acquisition is specifically adapted to characteristic flow-field patterns of the respective environment (predator/prey) and signal processing is presumably considerably simplified (key word coincidence detector). Even under the influence of turbulent background noise this data-acquisition technique is apparently still selective enough to perform specific tasks, like detection of prey patterns or triggering of evasive actions. In engineering such grid effects are so-far completely unemployed, e.g. for flow diagnostics in turbulent or separated flows. For the investigation of these effects, carefully selected experimental and numerical investigations of the actions of characteristic flow-field structures on synthesised, structured hairy surfaces in unsteady and turbulent boundary-layer flows will be studied. The investigations will be performed under controlled boundary conditions, like orientation, elasticity and group arrangements of the sensor hairs. The present proposal is inspired by examples from biology. It is not intended to study grid effects in biology.