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: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=739985
• 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起着至关重要的作用。它通过实现时间和空间的分辨率速度，使航空航天、汽车、医学成像和微流体研究受益。然而，精确的无创压力场测量技术，通常是基于速度测量(V-压力)重建压力场，仍处于早期发展阶段，且健壮性较差。可靠的V压技术有着广泛的应用。例如，识别汽车的空气声学噪声源，以及通过超声波无创测量血压。此外，V型压力的严格不确定度量化(UQ)仍然是作为一种定量技术被采用的重要需要。作为类比，人们可以想到手册中没有准确信息的不精确的实验室天平：这样的天平不能被认为是定量的。此外，关于垂直压力误差传播的详细理论还没有得到彻底的发展；关于误差传播动力学的一个坚实的共识对于下一代垂直压力技术的开发和优化是至关重要的。为了推进垂直压力技术的发展，该方案重点解决了三个内在联系的子问题：(1)建立一个全面的、基本的垂直压力误差传播理论。将建立一个系统的框架，使测量中的误差和真实值脱钩，并使直接分析成为可能，而不是像以前的大多数研究那样，假定误差可以忽略不计。(2)开发了一种可先验用于不确定性估计的实验优化协议。由于其分析基础，该协议具有广泛的适用性(即适用于各种数值格式和测速技术)，并将使流体力学领域受益。(3)开发新的基于数据同化(DA-)的垂直压力算法。新的DA算法扩展了气象学和控制领域的技术，将提供准确的气压估计和自信的UQ。提出的方案具有理论、实践和培训的优点：研究成果满足了对基本误差传播理论和未来V-压力技术发展的UQ的迫切需要。这项研究的分析基础将为实验流动诊断提供一个独特的视角。该研究项目的成功将提供真正的定量非侵入性仪器技术，在任何重要的流动诱导压力和载荷(例如，诊断车辆、建筑物和风力涡轮机上的风载荷分布)处推动广泛的创新。拟议的课程集分析、数值和实验流体力学于一身，将提供独特的跨学科培训，使学生具备多才多艺的技能，以推动加拿大和全球未来的工业和学术界的发展。