Low-dimensional representation and sensor based estimation of bluff body wakes and vortex induced vibrations

该建议的重点是发展低维模型的湍流尾流和涡流引起的振动，这是服从基于传感器的训练/估计监测应用。这项研究的主要应用包括：（i）保持土木结构和机械工程设备的完整性，可能会受到显着的非定常横流负载，（ii）在工业应用中的非定常流的监测和控制，（iii）非定常流体动能的收获风和水流通过利用流致振动。由于对安全基础设施和可持续能源的需求，这些在工程和科学领域具有越来越重要的意义。该研究计划的长期目标（10年以上）是开发一种可推广的方法，使多传感器系统能够进行实时预测和鲁棒部署的训练。研究计划可分为两个阶段。第一阶段的研究重点是先进的多尺度分解技术，包括时域谱本征正交分解（SPOD）和多尺度本征正交分解（mPOD）的湍流尾流和涡激振动。在这些技术中的基本假设是，它是可能的，并希望控制的光谱性质的数据减少，使得动态相关的多尺度现象可以表示在不同的模式，使一个改进的解释的物理过程中发生的流。此外，这些方法可以改善相干结构与非相干波动的分离。第一阶段的目标是通过相关和实际的工程问题来实验性地测试上述假设。第二阶段的研究涉及基于传感器的估计湍流尾流和涡激振动。在第一阶段内通过SPOD和mPOD建立的低维子空间将作为估计基础。几种技术，包括线性和二次随机估计，以及更现代的方法，使用人工神经网络将被用于开发传感器信号和所需的模式之间的映射函数进行估计。研究计划的重要实验部分将在申请人的业务研究水洞设施中进行，该设施配备了最先进的流量诊断设备。该研究计划将有助于在实际工程应用中的湍流尾流和涡激振动的物理解释和建模的根本进步，并支持这些流动的基于传感器的估计技术的发展。已开发的流量建模和基于传感器的估计技术的可推广性将成为加拿大行业合作伙伴实施多传感器系统监测（安全性，完整性）和控制技术的催化剂。

This proposal is focused on the development of low-dimensional models of turbulent wakes and vortex induced vibrations which are amenable to sensor-based training/estimation for monitoring applications. Major applications of this research include: (i) maintaining the integrity of civil structures and mechanical engineering devices which may undergo significant unsteady cross-flow loading, (ii) monitoring and control of unsteady flows in industrial applications, (iii) the harvesting of unsteady fluid kinetic energy wind and water flows through exploiting flow-induced vibrations. These are of emerging importance in engineering and science due to the need for safe infrastructure and sustainable energy sources. The long-term objective of this research program (10+ years) is to develop a generalizable methodology which enables multi-sensor systems to be trained for real-time predictions and robust deployments. The research program can be divided into two phases. Phase I research is focused on advanced multi-scale decomposition techniques including the time-domain Spectral Proper Orthogonal Decomposition (SPOD) and multiscale Proper Orthogonal Decomposition (mPOD) for turbulent wakes and vortex induced vibrations. The essential hypothesis in these techniques is that it is possible and desirable to control the spectral nature of the data reduction such that dynamically relevant multi-scale phenomena may be represented in distinct modes, enabling an improved interpretation of the physical processes occurring within the flow. Moreover, these approaches may improve the separation of coherent structures from incoherent fluctuations. The goal of Phase I is to experimentally test the aforementioned hypothesis through relevant and practical engineering problems. Phase II research involves sensor-based estimation of turbulent wakes and vortex induced vibrations. The low-dimensional subspace established through SPOD and mPOD within Phase I will serve as the estimation basis. Several techniques including Linear and Quadratic Stochastic Estimation, and more modern approaches using Artificial Neural Networks will be utilized in developing mapping functions between the sensor signals and the desired modes to be estimated. The significant experimental component of the research program will be carried out in the applicants operational research water tunnel facilities which are equipped with state-of-the-art flow diagnostic equipment. The research program will contribute fundamental advancement in physical interpretation and modeling of turbulent wakes and vortex induced vibrations in practical engineering applications and support the development of sensor-based estimation techniques for these flows. The demonstrated generalizability of the developed flow modeling and sensor-based estimation techniques will be a catalyst for industry partners in Canada to implement these techniques for multi-sensor system monitoring (safety, integrity) and control.