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: $ 3.79万
• 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: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760439
• 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.

粒子图像测速是一种非侵入式速度测量技术，在现代流体力学研究中至关重要，它可以解析时间和空间上的速度，从而使航空航天、汽车、医学成像和微流体研究受益。有创压力场测量技术通常基于速度测量（V-Pressure）重建压力场，但仍处于发展的早期阶段，并且可能存在鲁棒性差的问题。可靠的 V-Pressure 技术具有广泛的应用。示例包括识别汽车的空气声学噪声源和通过超声检查进行无创血压测量。此外，V 压力的严格不确定性量化 (UQ) 仍然是被采用作为一种定量技术的重要需求。不精确的实验室量表，手册中没有准确的信息：这种量表不能被认为是定量的，而且，V-Pressure 的详细误差传播理论尚未得到彻底的发展。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，所提出的计划重点解决三个内在相关的子问题： (1) 制定全面的 V-Pressure 误差传播基础理论。将建立一个系统框架来解耦测量中的误差和真实值并进行直接分析，而不是像以前的大多数研究那样假设可忽略的误差 (2) 开发可用于的实验优化协议。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）开发基于 V 的新型数据同化。 - 压力算法。新的 DA 算法扩展了气象学和控制领域的技术，将提供准确的压力估计，并具有可信的 UQ 所提出的程序具有理论、实践和培训优点：研究成果满足了基本误差的迫切需要。该研究的分析基础将为实验流动诊断提供独特的视角，该研究计划的成功将提供真正的定量非侵入性仪器技术，从而促进流动领域的广泛创新。诱导压力和载荷很重要（例如，诊断车辆、建筑物和风力涡轮机上的风载荷分布）。拟议的项目是分析、数值和实验流体力学的交叉点，并将提供独特的跨学科培训，为学生提供装备。具有多功能性推动未来加拿大和全球工业界和学术界发展的技能。