A validated lumped-element model for bioinspired acoustic flow sensing toward the performance limit

TL;DR

This paper presents a validated lumped-element model for bioinspired acoustic flow sensors, accurately predicting their performance and guiding the design of high-performance flow and sound detection devices.

Contribution

The authors develop and experimentally validate a simple yet accurate lumped-element model for broadband microcantilever motion in fluid, enhancing sensor design capabilities.

Findings

Model accurately predicts flow-induced motion from 100 Hz to 10 kHz.

Strong agreement between model predictions and experimental measurements.

Provides a theoretical framework for designing advanced flow and sound sensors.

Abstract

Flow sensing is fundamental to both biological survival and technological innovation. Inspired by biological mechanoreceptors, artificial flow sensors detect subtle fluid motion using slender, viscous-driven structures. Among these, acoustic flow sensors that mimic nature's velocity-sensitive ears have the potential to transform vector sound detection. Yet, despite their potential, understanding of how design parameters determine ultimate sensor performance remains limited. To effectively guide flow sensor design, we develop and experimentally validate a lumped-element model that captures the broadband motion of slender microcantilevers immersed in fluid, combining analytical simplicity with quantitative accuracy. The model predicts flow-induced motion, thermomechanical noise, and the minimum detectable signal level, showing strong agreement with experimental measurements in air over a broad frequency range from 100 Hz to 10,000 Hz. This validated model provides a straightforward theoretical framework for designing high-performance micro- and nanomechanical sensors for flow and vector sound detection.