Stochastic Modeling of Turbulence over Rough Walls: Theory, Experiments, and Simulations

粗糙壁上湍流的随机建模：理论、实验和模拟

• 批准号: 2412025
• 负责人: Michele Guala
• 金额: $ 49.05万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2412025&HistoricalAwards=false
• 关键词: Stochastic; Modeling; Turbulence; over; Rough

Most of the surfaces over which turbulent flows evolve are hydrodynamically rough. The effect of roughness is very challenging to simulate rigorously because the geometry and the nearby velocity field has to be reproduced with a very fine resolution, which is computationally expensive. For some applications, including wind energy, pollution dispersion, canopy flows in urban areas, the ground region is a minor, but unfortunately necessary and costly, component of the simulation. The standard approach is to bypass the complexity of the roughness layer and assume that the logarithmic mean velocity profile extends all the way to the surface, thus losing some of the variability of the near surface velocity field. A more active wall modeling strategy could be envisioned. Recently, the evolution and derivation of the logarithmic mean velocity profile, has been connected to the vertical distribution of Uniform Momentum Zones. These are large flow regions that tend to move coherently with the same velocity, tend to get thicker with the distance from the wall, and are separated by thin regions of intense gradients. The Uniform Momentum Zones, and these internal shear layers separating them, are the simplest modeling framework for wall turbulence. The outreach component of the proposal includes a summer program for undergrad students from Native American Tribal College, international collaboration with a colleague in Australia, and experimental data sharing, open to everyone in the research community. The goal of this project is to formulate, and validate experimentally, a Uniform Momentum Zones-based stochastic model able to reproduce the velocity field, characteristic of near-surface turbulence, preserving its variability and dynamics, all the way to the ground. To build and test this new model, experiments are needed, on different rough surfaces, to map the Uniform Momentum Zones distribution in three dimensions and guide the stochastic model. A new interface with large scale numerical simulations will be also implemented as a new, dynamic boundary condition. This will enable researchers to replace the computationally expensive, near-surface domain with an affordable synthetic velocity field, and improve future simulations of complex atmospheric flows, or similarly high Reynolds number turbulent boundary layers, like those developing around ships or planes. The ultimate goal is to enable and test the formulation of the stochastic model based on the surface roughness geometry and on easily measurable flow variables, to ensure predictive capabilities with minimal input information.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

湍流进化的大多数表面在流体动力学上是粗糙的。严格模拟粗糙度的效果非常具有挑战性，因为必须以非常精细的分辨率来重现几何形状和附近的速度场，这在计算上昂贵。对于某些应用，包括风能，污染分散，城市地区的冠层流，地面区域是次要的，但不幸的是，模拟的组成部分是必要的且昂贵的。标准方法是绕过粗糙度层的复杂性，并假设对数平均速度曲线一直延伸到表面，从而失去了近表面速度场的一些可变性。可以设想更活跃的墙壁建模策略。最近，对数平均速度轮廓的演化和推导已连接到均匀动量区域的垂直分布。这些是较大的流动区域，倾向于以相同的速度连贯地移动，往往会随着距墙的距离而变得更厚，并且被强烈梯度的薄区域隔开。均匀的动量区域以及将它们分开的这些内部剪切层是壁湍流的最简单建模框架。该提案的外展部分包括一个针对美国原住民部落学院的本科生，与澳大利亚同事的国际合作以及对研究界每个人开放的实验数据共享的夏季计划。该项目的目的是在实验中制定并验证一个统一的基于动量区域的随机模型，能够再现速度场，即近表面湍流的特征，并保留其变异性和动力学。 为了构建和测试这一新模型，需要在不同的粗糙表面上进行实验，以在三维中绘制均匀的动量区域分布并指导随机模型。具有大型数值模拟的新接口也将作为新的动态边界条件实现。这将使研究人员能够用负担得起的合成速度场替换计算上昂贵的，近乎表面的域，并改善对复杂大气流的未来模拟，或类似的高雷诺数数量的湍流边界层，例如围绕船只或平面周围开发的边界层。最终目标是基于表面粗糙度几何形状和易于测量的流量变量启用和测试随机模型的制定，以确保具有最少输入信息的预测能力。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和广泛的影响来评估的，并被视为值得通过评估的支持。