CAREER: High fidelity numerical simulations of turbulent flow separation at high Reynolds numbers with passive scalar transport.

提出的研究将为流体动力学中一个尚未被很好理解的问题提供基础知识：流动分离及其与热量和污染物输送的关联。当流体流过一个物体（如飞机的机翼）时，突然从物体表面“分离”，就会发生流动分离。然后在分离区域形成一种旋流运动，称为尾流或涡流，从而增加流体对物体的阻力。流动分离是不需要的，并且会严重降低飞机和涡轮机等工程设备的性能。高分辨率数值模拟的使用将使更有效的湍流模型得以发展。这些模型将促进流动、热量和污染物输送控制工具的发展，以减轻不必要的流动分离效应。拟议的研究和教育目标将在波多黎各联邦的一个西班牙裔服务机构进行。这个项目的教育部分促进了高性能计算、计算思维和建模的使用。这些概念将被引入到本科和研究生课程使用翻转课堂的概念。处理后的数据和产生的代码将向公众开放，供分析和验证。此外，计算机和可视化设备将作为研究、学习和拓展部门夏令营的工具，供K-12学生和教师使用。本研究的主要目的是在数值上阐明边界层分离过程中被动标量现象背后的细节，这些现象是由流动分离的两个最常见的原因造成的：流向和壁面曲率驱动的压力梯度，以组合形式和孤立形式。这项研究将涵盖几乎整个光谱，特别是在近壁区域，在那里实验技术和湍流模型显示出严重的局限性。通过识别和跟踪拉格朗日相干结构（LCS），探索LCS运动学与被动标量场之间的关系，可以准确地解释分离过程。这些研究工作将应用大量的计算资源，需要最先进的千兆级、并行和图形处理单元（GPU）编程。具体目标包括：1)在实验雷诺数强减速条件下对空间发展的湍流边界层进行直接数值模拟（DNS）； 2)通过低/高阶统计分析了解分离过程中的输运现象，并与用于增强/虚拟现实的iOS/Android应用程序一起创建LCS数据库；3)在大涡模拟（LES）中开发独特的数据驱动的子网格尺度（SGS）模型。专注于被动标量的未知领域。该项目由流体动力学项目和促进竞争研究的既定项目（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The proposed research will provide foundational knowledge on an issue in fluid dynamics that is not well understood: flow separation and its association with heat and contaminant transport. Flow separation occurs when fluid flow past an object (e.g., wing of an aircraft) abruptly "detaches" from the surface. A swirling motion, called wakes or vortices, is then formed in the separated region which result in increasing the fluid drag force on the object. Flow separation is unwanted and can seriously reduce performance of engineered devices such as aircraft and turbines. The use of high-resolution numerical simulations will permit the advancement of more efficient turbulence models. Such models will facilitate the development of flow, heat, and contaminant transport control tools to mitigate unwanted flow separation effects. The proposed research and educational objectives will be carried out at a Hispanic Serving Institution, located in the Commonwealth of Puerto Rico. The educational component of this project promotes the use of high-performance computing, computational thinking, and modeling. Such concepts will be introduced to undergraduate and graduate courses using flipped classroom concept. The post-processed data and resulting codes will be made accessible to the public for analysis and validation. Additionally, a computing and visualization facility will be developed as a tool for research, learning, and outreach in departmental Summer Camps for K-12 students and teachers. The principal aim of this study is to numerically elucidate the details behind passive scalar phenomena during boundary layer separation, resulting from the two most frequent causes of flow detachment: streamwise and wall-curvature driven pressure gradient, in combination and isolated forms. The study will cover nearly the entire spectrum, particularly in the near wall region, where experimental techniques and turbulence models exhibit severe limitations. By identifying and tracking Lagrangian Coherent Structures (LCS) and exploring the relationship between LCS kinematics and passive scalar fields, it may be possible to accurately explain the separation process. These research efforts will apply the use of tremendous computational resources, requiring state-of-the-art petascale, parallel and Graphics Processing Unit (GPU) programming. Specific objectives include i) perform Direct Numerical Simulation (DNS) of spatially-developing turbulent boundary layers under strong deceleration at experimental Reynolds numbers, ii) understand the transport phenomena in the separation process by means of low/high order statistics analysis and create an LCS data bank along with iOS/Android apps for augmented/virtual reality, iii) develop a unique data-driven modeling of sub-grid scale (SGS) in Large Eddy Simulation (LES), focusing on the uncharted area of passive scalar. This project is jointly funded by the Fluid Dynamics Program and the Established Program to Stimulate Competitive Research (EPSCoR).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.