Title

Collective sensitivity of artificial hair sensors to flow direction

Document Type

Article

Publication Date

2-9-2021

Department

Department of Mechanical Engineering-Engineering Mechanics

Abstract

We study the collective response of synthetic hair sensors to changes in the airflow direction. Specifically, we examine whether an array of isotropic sensors, which are unable to detect the direction of an incident flow when operating in isolation, can together sense not only the magnitude but also the orientation of a freestream flow passing over and through them. To conduct our inquiry, we consider a fundamental scenario involving a boundary-layer flow past a flat plate decorated with a 3 × 3 array of sensors. Numerical modeling is used to simulate the interaction between the fluid flow and flexible hair sensors. We find that, indeed, it is feasible to achieve collective directional sensitivity by engineering the arrangement of the sensors. We also propose a supervised machine learning approach capable of deducing the direction of the freestream flow from the deformation signals outputted by individual sensors in the array.

Publication Title

AIAA Journal

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