Towards manipulating three-dimensional bluff-body wakes.

在建筑物、地面车辆或暴露的管道的背风处，风向的变化和阵风都是湍流崖体尾迹的例子。流体撞击到阀体前部并沿着两侧分离，从而形成逆流区域。循环区域的动力学特征是速度和压力的波动。波动幅度取决于环流区产生的运动涡的强度和相互作用。这些动力会对机体产生有害的非定常力，增加阻力并增强下游的分散。相比之下，崖体附属物用于化学反应器或燃烧室，以增强混合，从而提高产品产量或清洁燃烧。因此，操纵崖体尾流来抑制或放大动力的能力是工程学的兴趣所在。*******提出的研究计划是理解和操纵尾流的框架。对尾流动力学的物理基础有一个基本的了解。为此，将对来流和体形对涡旋强度及其相互作用的影响进行表征。在此基础上，将研究由沿障碍物表面的脉动射流引入的局部强迫对尾迹动力学的影响。这些操作如何影响非定常力、阻力和下游混合将被表征。这些研究是通过开发新的技术来实现的，这些技术可以基于紧凑的数学公式来表示和模拟涡旋相互作用，预测对局部强迫的响应，并优化操纵参数以抑制或放大尾流波动。优化将基于机器学习原理。这些技术来自数学、信号处理和人工智能领域，突出了本研究的跨学科性质。*******该计划中开发的知识和模型适用于广泛的湍流分离流，因此对研究界具有根本的兴趣。开发的建模技术与工业应用相关。这些产生了新的流量监测和早期检测技术，适用于难以接近或偏远环境的过程控制和损害减轻，例如化学反应器和暴露的管道。在尾流操纵中获得的知识预计将对以下方面具有重要意义：地面运输，降低燃料消耗和提高高速稳定性；对于化学反应器或燃烧器，混合控制效率，产品质量和产量。紧凑建模和机器学习有助于自主系统的设计。总体而言，该计划因此提供了一个开发技能和培训新兴技术高素质人才的环境

Shifting wind patterns and gusting in the lee of buildings, ground vehicles or exposed pipelines are examples of turbulent bluff-body wakes. The flow impinges on the front of the body and detaches, or separates, along the sides resulting in reverse flow regions. The recirculating region dynamics are characterized by fluctuating velocity and pressure. The fluctuation amplitude depends on the strength and interaction of moving vortices generated in the recirculating region. These dynamics induce deleterious unsteady forces on the body, increase drag and enhance dispersion downstream. In contrast, bluff-body appendages are used in chemical reactors or combustors to enhance mixing and benefit higher product yield or cleaner combustion. Hence, the ability to manipulate bluff-body wakes to suppress or amplify dynamics is of engineering interest.*******The proposed research program is a framework for understanding and manipulating wake flows. A fundamental understanding the physics underlying the wake dynamics is to be gained. To this end, the influence of the on-coming flow and body shape on the strength of vortices and their interactions will be characterized. From this baseline, changes to the wake dynamics due to local forcing, introduced through pulsating jets along the obstacle surface, will be investigated. How these manipulations affect the unsteady forces, drag and downstream mixing will be characterized. These investigations are enabled by new techniques developed to represent and model the vortex interactions, based on compact mathematical formulations, predict the response to local forcing and optimize the manipulation parameters for suppressing or amplifying wake fluctuations. Optimization will be based on machine learning principles. These techniques are drawn from mathematics, signal processing and artificial intelligence communities, highlighting the interdisciplinary nature of this research.*******The knowledge and models developed in the program are applicable to a broad class of turbulent separated flows and thus of fundamental interest to the research community. The developed modelling techniques are relevant to industrial applications. These yield new technologies for flow monitoring and early-detection, which are suited for process control and damage mitigation for inaccessible or remote environments, such as chemical reactors and exposed pipelines. The knowledge gained in wake manipulation is anticipated to be significant for: ground transportation, reducing fuel consumption and increasing high-speed stability; and for chemical reactors or combustors, where mixing controls efficiency, product quality and yield. Compact modelling and machine learning can contribute to the design of autonomous systems. Overall, this program thus offers a context for developing skills and training highly qualified personnel for emerging technologies.***