EAGER: A New Aerial Platform for Turbulence Measurements in the Atmospheric Surface Layer

EAGER：用于测量大气表层湍流的新型空中平台

• 批准号: 2332467
• 负责人: Stephan De Wekker
• 金额: $ 12.61万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2332467&HistoricalAwards=false
• 关键词: EAGER; New; Aerial; Platform; Turbulence

This project seeks to advance research in the measurement of winds. Why is it important? Having refined measurements of winds improves weather forecasting. For instance, if we can better predict how winds behave during disaster situations such as wildfires and train derailments that involve toxic gas pollution, we can forecast the behavior and impact of wind factors in local areas and prevent or minimize health risks to the public. This would allow better coordination of emergency response and resources and minimize the economic impact at the local, state, and national levels. To achieve these goals, drone technology will be used in this project. One major benefit of drones is that they can access locations in the atmosphere near the ground that are unsafe to humans or difficult to access otherwise, such as mountainous terrain, lakes, and glaciers. Another benefit of drone technology is that a drone can hover over difficult terrain for a long time, allowing data collection to develop and test wind forecasting models. This type of in-person research in difficult terrain is currently impossible or very difficult to achieve, which has resulted in major weaknesses in wind behavior understanding and in wind forecasting models. Collecting wind data with drones is not only very novel, but also cost-effective. The wind collection technology using drones would address the current research weaknesses and help protect the public in their daily lives or in emergency situations. The project aims to explore the ability of commercial off-the-shelf (COTS) multirotor drones to measure turbulence. The approach is innovative because it only relies on the use of easily retrievable data from COTS drones. There is no need for custom-built frames and tuning of flight control parameters, making the approach cost-efficient and easily accessible to the scientific community without an engineering and/or technical background. The major goals are to investigate 1) the accuracy of these drone-based turbulence measurements, and 2) the dependency of the accuracy on drone size and weight. Measurements will be performed next to a large array of start-of-the-art sonic anemometers over flat terrain in the NSF funded M2HATS field study, offering an unprecedented opportunity for an intercomparison experiment. Eight multi-rotor vehicles will be used, including two different types of COTS multirotor drones to retrieve data necessary to estimate turbulence.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在推进测风方面的研究。这个问题为什么重要呢？对风速进行精确的测量可以改善天气预报。例如，如果我们能够更好地预测风在涉及有毒气体污染的野火和火车脱轨等灾害情况下的行为和影响，我们就可以预测当地风因素的行为和影响，防止或最大限度地减少对公众的健康风险。这将允许更好地协调应急响应和资源，并将地方、州和国家层面的经济影响降至最低。为了实现这些目标，该项目将使用无人机技术。无人机的一个主要好处是，它们可以进入大气中靠近地面的地点，这些地点对人类不安全或以其他方式难以进入，如山区、湖泊和冰川。无人机技术的另一个好处是，无人机可以在困难的地形上盘旋很长时间，允许数据收集来开发和测试风速预报模型。这种在复杂地形下的面对面研究目前是不可能或很难实现的，这导致了在风行为理解和风预测模型方面的主要弱点。用无人机收集风能数据不仅非常新颖，而且性价比很高。使用无人机的风力收集技术将解决目前的研究弱点，并有助于在日常生活或紧急情况下保护公众。该项目旨在探索商用现成(COTS)多旋翼无人机测量湍流的能力。这种方法是创新的，因为它只依赖于使用COTS无人机上容易检索的数据。不需要定制框架和调整飞行控制参数，使这种方法具有成本效益，并易于科学界在没有工程和/或技术背景的情况下使用。主要目标是调查1)这些基于无人机的湍流测量的准确性，以及2)精度对无人机大小和重量的依赖关系。在NSF资助的M2HATS实地研究中，测量将在平坦地形上的一大批最先进的声波风速计旁边进行，这为相互比较实验提供了前所未有的机会。八架多旋翼飞行器将被使用，包括两种不同类型的COTS多旋翼无人机来检索估计湍流所需的数据。这一奖项反映了NSF的法定使命，通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。