Scale Interactions in Wall Turbulence: Old Challenges Tackled with New Perspectives

提高基于流体的系统的效率的需求现在是至关重要的。在实验空气动力学中，最困难的测量之一是精确确定表面摩擦力。我们需要准确地预测它，这对设计高效的系统至关重要。雷诺数相似是描述湍流附壁流动基本性质的一个重要概念。与海崖体的阻力系数不同，湍流边界层的阻力系数随着雷诺数的增加而无限地减小，因为在任何雷诺数下，表面附近的小尺度运动都直接受到粘性的影响。因此，雷诺数相似性在设计中非常重要，也是工程师的重要工具。工程师从直接数值模拟或风洞试验（或两者）中获得信息，可能需要外推几个数量级，以便估算工程阻力或甚至气象雷诺数。也许雷诺数相似性最著名的例子是对数速度变化的区域（对数定律）在有壁流动中发现的，在足够高的雷诺数下，不管表面边界条件的性质或外部施加长度尺度的形式如何，都存在。在与实际应用有关的有壁流动中，当流动是湍流且雷诺数高时，流体动量和能量的传输和损失还没有很好地理解。因此，大多数预测和建模方法依赖于各种假设。其中最关键的两个是壁定律（对数定律）和汤森的局部平衡假说。这两个假设都隐含地假设流中的大尺度是弱的，它们独立于小尺度起作用。然而，这显然是不正确的，特别是在工程重要性的流动中，例如当表面粗糙或流动不平衡时。事实上，存在多尺度相互作用，这里称为内外相互作用（IOI），其中大尺度影响小尺度的动态，反之亦然。这些相互作用还没有得到很好的理解，因此对预测模型的任何修正都必须通过特殊的方法来实现。更好地理解IOI将有助于解释对数定律中常数的明显非普适性，并且肯定会影响雷诺平均纳维尔-斯托克斯（RANS）计算方法、大涡模拟（LES）和混合RANS-LES模型的发展。它也将是有用的，在发展模型的控制壁湍流，补充知识，直接数值模拟，我们认为，固有的不完整，由于限制低雷诺数。在实际应用的典型现实雷诺数下，精确的预测和控制模型必须解决IOI问题。在内部粗糙壁流动、粗糙壁边界层和自由湍流对边界层的影响等特定领域工作的研究人员也将从这一基础工作中受益。所有这些方面都大量存在于各种实际应用和自然系统中。例如，研究人员在探索石油和天然气管道、船体以及自然和城市地形等实际应用的建模策略时，会发现从粗糙度实验中获得的数据对验证工作非常有用。同样地，在湍流领域的研究人员会发现粗糙度和自由湍流实验的数据非常有用。

The need to improve the efficiency of fluid-based systems is now of paramount importance. In experimental aerodynamics, one of the most difficult measurements is an accurate determination of surface friction. Our need to predict it accurately is fundamentally important to the design of efficient systems. Reynolds number similarity is an essential concept in describing the fundamental properties of turbulent wall-bounded flow. Unlike the drag coefficient for bluff bodies, that for a turbulent boundary layer continues to decrease indefinitely with increasing Reynolds number because the small-scale motion near the surface is directly affected by viscosity at any Reynolds number. Therefore Reynolds number similarity is very important in design and is a vital tool for the engineer, who, plied with information from either direct numerical simulations or wind-tunnel tests (or both), may well have to extrapolate over several orders of magnitude in order to estimate quantities such as drag at engineering or even meteorological Reynolds numbers. Perhaps the most well-known example of Reynolds number similarity is the region of log velocity variation (the log law) found in wall-bounded flows which, at sufficiently high Reynolds numbers, exists regardless of the nature of the surface boundary condition or the form of the outer imposed length scale.In wall-bounded flows relevant to practical applications, where the flow is turbulent and the Reynolds number is high, the transport and loss of fluid momentum and energy is not well understood. Consequently, most predictive and modelling methods rely on a variety of assumptions. The two most critical ones are the Law of the Wall (the log law) and Townsend's local-equilibrium hypothesis. Both assumptions implicitly assume that large scales in the flow are weak and that they function independently of the small scales. However, this is clearly not true, especially in flows of engineering importance, such as when the surface is rough or when the flow is not in equilibrium. In fact, there is a multiscale interaction, referred to here as an inner-outer interaction (IOI), where the large scales influence the dynamics of the small scales and vice-versa. These interactions are not well understood and therefore any corrections to the predictive models to include these interactions are essentially achieved through ad-hoc means.A better understanding of IOI will help explain the apparent non-universality of the constants in the log law and will certainly influence the development of models for both Reynolds-Averaged Navier-Stokes (RANS) calculation methods, Large-Eddy Simulations (LES) and hybrid RANS-LES. It will also be useful in the development of models for the control of wall turbulence, complementing knowledge from Direct Numerical Simulations which, we believe, are inherently incomplete owing to the restriction to low Reynolds numbers. Accurate models for prediction and control at realistic Reynolds numbers typical of practical applications will have to address IOI. Researchers working in specific areas of internal rough-wall flows, rough-wall boundary layers and freestream turbulence effects on boundary layers will also benefit from this fundamental work. All these aspects are abundantly present in a variety of practical applications and natural systems. For example, researchers exploring modelling strategies for practical applications such as oil and natural-gas pipelines, ship hulls and the natural and urban terrains will find the the data obtained from the roughness experiments to be very useful for validation exercises. Similarly, researchers in the area of turbomachinery will find the data from the roughness and freestream turbulence experiments extremely useful.