Optimal estimation and uncertainty quantification for velocimetry-based pressure field reconstruction

基于测速的压力场重建的最优估计和不确定性量化

• 批准号: RGPIN-2020-04486
• 负责人: Pan, Zhao
• 金额: $ 1.97万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=716092
• 关键词: Optimal; estimation; uncertainty; quantification; velocimetry

Particle image velocimetry is a non-intrusive velocity measurement technique that is critical in modern fluid mechanics research. It has benefited aerospace, automotive, medical imaging, and micro-fluids research by enabling resolving velocities in both time and space. However, accurate non-invasive pressure field measurement techniques, which typically reconstruct the pressure field based on velocity measurements (V-Pressure), are still in the early stages of development and can suffer from poor robustness. Reliable V-Pressure techniques have wide applications. Examples include identifying aeroacoustic noise sources of a car and noninvasive blood pressure measurement from ultrasonography. In addition, rigorous uncertainty quantification (UQ) of V-Pressure remains a significant need for being adopted as a quantitative technique. As an analogy, one can think of an imprecise laboratory scale that does not have accuracy information in the manual: such a scale cannot be considered quantitative. Moreover, the detailed error propagation theory of V-Pressure has not been thoroughly developed; a solid consensus about the error propagation dynamics is critical to the development and optimization of next-generation V-Pressure techniques. To advance V-Pressure, the proposed program focuses on solving three inherently connected sub-problems: (1) Formulate a comprehensive, fundamental theory of error propagation of V-Pressure. A systematic framework will be established to decouple the error and true value in the measurements and enable direct analysis, rather than, as in most previous studies, assume negligible error. (2) Develop an experimental optimization protocol that can be used a priori for uncertainty estimation. Due to its analytical basis, the protocol has broad applicability (i.e. adaptive to various numerical schemes and velocimetry techniques) and will benefit the fluid mechanics community. (3) Develop novel data assimilation- (DA-) based V-Pressure algorithms. Extending techniques in the fields of meteorology and controls, the new DA algorithms will provide accurate pressure estimates with confident UQ. The proposed program has theoretical, practical, and training merits: research outcomes meet the immediate need for fundamental error propagation theory and UQ for future V-Pressure techniques development. The analytical basis of the research will provide a unique view of experimental flow diagnostics. The success of the research program will offer true quantitative non-invasive instrumental techniques that promote broad innovations anywhere flow-induced pressure and loads are important (e.g. diagnosing wind load distribution on vehicles, buildings, and wind turbines). The proposed program is at the intersection of analytical, numerical, and experimental fluid mechanics, and will offer a unique interdisciplinary training that will equip students with versatile skill sets for advancing future Canadian and global industry and academia.

粒子图像测速技术是一种非侵入式速度测量技术，在现代流体力学研究中具有重要意义。它使航空航天、汽车、医学成像和微流体研究受益匪浅，因为它能够分辨时间和空间的速度。然而，通常基于速度测量（V-Pressure）来重建压力场的精确的非侵入式压力场测量技术仍处于开发的早期阶段，并且可能具有较差的鲁棒性。可靠的V-Pressure技术具有广泛的应用。例子包括识别汽车的气动噪声源和超声检查的无创血压测量。此外，严格的不确定性量化（UQ）的V-压力仍然是一个显着的需要被采纳为定量技术。作为一个类比，人们可以想到一个不精确的实验室规模，在手册中没有准确性信息：这样的规模不能被视为定量。此外，V-Pressure的详细误差传播理论尚未得到彻底发展;关于误差传播动力学的坚实共识对于下一代V-Pressure技术的开发和优化至关重要。为了推进V-Pressure，建议的计划侧重于解决三个内在关联的子问题： (1)制定一个全面的，基本的理论误差传播的V压力。将建立一个系统的框架，以消除测量中的误差和真实值，并进行直接分析，而不是像大多数以前的研究那样，假设误差可以忽略不计。 (2)开发一个实验优化协议，可以用于先验的不确定性估计。由于其分析基础，该协议具有广泛的适用性（即适应各种数值方案和测速技术），并将有利于流体力学界。 (3)开发新的基于数据同化（DA）的V-Pressure算法。新的DA算法扩展了气象和控制领域的技术，将提供准确的压力估计和自信的UQ。 所提出的方案具有理论，实践和培训优点：研究成果满足未来V-压力技术发展的基本误差传播理论和UQ的迫切需要。分析基础的研究将提供一个独特的观点，实验流量诊断。该研究计划的成功将提供真正的定量非侵入性仪器技术，促进任何重要的流致压力和载荷的广泛创新（例如诊断车辆，建筑物和风力涡轮机上的风载荷分布）。该计划是在分析，数值和实验流体力学的交叉点，并将提供一个独特的跨学科培训，将为学生提供多功能的技能，以推动未来的加拿大和全球工业和学术界。