Smart skin for control of wall-bounded turbulent flows

边界层是紧邻固体表面的流体薄层，其中流体速度从固体表面的速度过渡到整体流体速度。流体中的剪切应力产生这种速度梯度，并在表面上投影为“表面摩擦”。在大多数工业情况下，例如飞机上方或管道内部的流动，边界层中流体元素的运动是混乱的。这样的流体层被称为湍流边界层（TBL），并且具有产生更大的表面摩擦的更大的速度梯度。此外，当增加的压力梯度施加在TBL上时，如在扩散器中或在飞机机翼上，TBL可能与表面分离。这就产生了“压力阻力”和强烈的流体-结构相互作用。因此，TBL是飞机、潜水器、船舶和管道中的高燃料消耗、污染和结构振动的主要来源。由于这一整体效应，控制TBL的任何进展都将对我们的社会经济和环境保护需求产生深远影响。 这项研究计划的主题是使用一种新的“智能皮肤”控制附着和分离的TBL。为了实现这一目标，我们将首先通过实验来表征附着和分离的TBL中大规模运动的表面压力，以开发用于湍流控制的预测模型。同时，我们将开发可变形的表面，可以生成按需的局部表面凹陷或突起。线性致动器，具有与压力足迹相匹配的频率和位移，将集成在可变形的皮肤下。我们将在“智能皮肤”中安装一系列主动可变形面板和表面压力传感器。最后，将在一个闭环系统中评估“智能蒙皮”的性能，以便对附着和分离的TBL进行主动控制。从长远来看，拟议的计划将增加我们的TBL相干运动的基础知识，并提供如何控制TBL的指导方针。开发的“智能皮肤”将使操纵包括TBL在内的各种湍流成为可能。智能皮肤还将成为先进控制算法、人工智能和机器学习应用的测试平台。这种方法最终可以使我们处理湍流的方式现代化。它可以通过将湍流控制引入各种工业部门来实现突破，以提高效率并减少环境足迹。此外，该研究计划的多学科性质将培养高素质的人才谁是在各种学科的培训。

A boundary layer is a thin layer of fluid in the immediate vicinity of a solid surface where fluid velocity transitions from the velocity of the solid surface to the bulk fluid velocity. The shear stress in the fluid generates this velocity gradient, and projects as `skin-friction' on the surface. In most industrial situations, for example, the flow over an aircraft or inside a pipeline, the motions of fluid elements in the boundary layer are chaotic. Such a fluid layer is known as a turbulent boundary layer (TBL), and has a larger velocity gradient that generates greater skin-friction. In addition, when an increasing pressure gradient is imposed on a TBL, like in a diffuser or on an aircraft wing, the TBL may separate from the surface. This generates `pressure drag' and strong fluid-structure interactions. As a result, the TBL is the chief source of high fuel consumption, pollution, and structural vibration in aircrafts, submersibles, ships, and pipelines. Due to this integral effect, any progress in the control of TBLs will have a profound impact on our socio-economic and environmental protection needs. The subject of this research program is the control of attached and separated TBLs using a novel `smart skin'. To achieve this goal, we will first experimentally characterize the surface pressure of large-scale motions in attached and separated TBLs to develop a predictive model for turbulence control. In parallel, we will develop deformable surfaces that can generate on-demand local surface depression or protrusion. Linear actuators, with a frequency and displacement that matches the pressure footprint, will be integrated under a deformable skin. We will implement an array of active deformable panels and surface pressure sensors into a `smart skin'. Finally, the performance of the `smart skin' will be evaluated in a closed-loop system for active control of attached and separated TBLs. In the long-term, the proposed program will increase our fundamental knowledge of coherent motions in TBLs and provide guidelines on how to control TBLs. The developed `smart skin' will make it possible to manipulate a variety of turbulent flows including TBLs. The smart skin will also become a test-bench for the application of advanced control algorithms, artificial intelligence, and machine learning. Such an approach can ultimately modernize how we handle turbulence. It can make a breakthrough by bringing turbulence control to a variety of industrial sectors to increase efficiency and reduce environmental footprints. In addition, the multidisciplinary nature of this research program will train highly qualified personnel who are trained in a variety of disciplines.