Integrated Sensing: Biomimetic Sensors for Autonomous Underwater Vehicles

水覆盖了大约70%的地球表面。然而，地球上的这大部分地区尚未被充分探索和了解。这主要是由于水下环境带来的巨大挑战，包括高压、不可预测的水流、接近冰点的温度、电磁波和光的衰减以及恶劣的化学成分。各种科学、军事和工业任务都需要在海洋环境中发挥作用的工具。自主水下航行器（auv）是执行复杂水下任务的重要平台。目前由于技术上的限制，一些任务并不适合auv。更先进的应用需要小型、集成、节能和潜在联网的auv，以提高效率并降低成本。实现这一愿景的关键一步是改进auv的传感器。该项目旨在开发受鱼类侧线系统启发的综合水下传感器。将建立传感器的原型，并通过计算和实验手段来研究这种传感器的流体力学行为。潜在的应用包括水动力尾迹的探测，化学羽流的追踪，以及流体和结构界面的水动力特性的测定。所提议的努力将集中在一个问题上——水动力尾迹的检测。计划的研究活动包括三个组成部分：(1)仿生集成微传感器的开发和改进；(2)利用全尺寸直接数值模拟和简化模型模拟对传感器性能进行验证和预测；(3)传感器性能与计算结果的实验验证。

Water covers approximately 70% of the earth surface. However, this majority of the planet is under-explored and poorly understood. This is largely a result of the significant challenge posed by the underwater environment, with its high pressure, unpredictable currents, nearly freezing temperatures, attenuation of electromagnetic waves and light, and harsh chemical compositions. A variety of scientific, military and industrial tasks call for tools that function in the ocean environment. Autonomous Underwater Vehicles (AUVs) are important platforms for carrying out sophisticated underwater tasks. Currently some tasks are not suitable for AUVs due to technical limitations. More advanced applications demand small, integrated, power efficient and potentially networked AUVs to increase the effectiveness and reduce the costs. A key step in moving toward this vision is improved sensors for AUVs. This project aims to develop integrated underwater sensors inspired by the fish lateral line system. Prototypes of sensors will be built and used to investigate the fluid mechanical behavior of such sensors through computational and experimental means. The potential applications include the detection of hydrodynamic wakes, tracing of chemical plumes, and determination of hydrodynamic properties at the interface of fluid and structures. The proposed effort will focus on one problem - that of detection of hydrodynamic wakes.Planned research activities consists of three integral components: (1) The development and improvement of biomimetic integrated microsensors; (2) The validation and prediction of sensor performance using full scale direct numerical simulation and reduced-model simulation; (3) The experimental validation of sensor performance and computational results.