The Detection of Unsteady Flow Separation with Bioinspired Hair-Cell Sensors
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Abstract
Biologists hypothesize that thousands of micro-scale hairs found on bat wings function as a network of air-flow sensors as part of a biological feedback flow control loop. In this work, we investigate hair-cell sensors as a means of detecting flow features in an unsteady separating flow over a cylinder. Individual hair-cell sensors were modeled using an Euler-Bernoulli beam equation forced by the fluid flow. When multiple sensor simulations are combined into an array of hair-cells, the response is shown to detect the onset and span of flow reversal, the upstream movement of the point of zero wall shear-stress, and the formation and growth of eddies near the wall of a cylinder. A linear algebraic hair-cell model, written as a function of the flow velocity, is also derived and shown to capture the same features as the hair-cell array simulation
