SBIR Phase I: A Flexion-Based Computational Fluid Dynamics Tool for the Fast Computation of Turbulent Flow over Complex Geometries

SBIR 第一阶段：基于弯曲的计算流体动力学工具，用于快速计算复杂几何形状的湍流

• 批准号: 2133757
• 负责人: Okey Nwogu
• 金额: $ 25.6万
• 依托单位: OMEGA HYDRODYNAMICS RESEARCH LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-15 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2133757&HistoricalAwards=false
• 关键词: SBIR; Phase; Flexion; Based; Computational

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the acceleration of the development of innovative industrial design concepts involving complex turbulent fluid flow using computational fluid dynamics (CFD) software. Although CFD software has broad applications in several industries, the company’s particular interest is in bodies with strong vortical wakes such as bio-inspired renewable energy extraction devices and electric vertical takeoff/landing (eVTOL) vehicles. It is anticipated that the project may lead to the timely and cost-effective design of energy extraction devices without the need to build and test prototypes during the design phase. The project may also enhance the safety and operating envelope of urban air mobility vehicles. The proposed cloud-based CFD software will provide startups and smaller companies (without access to high-performance computing resources) with the ability to perform CFD analysis in reasonable timeframes. The proposed novel reformulation of the Navier-Stokes equations will also have a lasting impact on the education of the next generation of engineers and scientists as they gain a better understanding of the advantages of the new set of equations for turbulent flows.This Small Business Innovation Research (SBIR) Phase I project seeks to develop a fast high-fidelity computational fluid dynamics (CFD) software for predicting unsteady flow separations over complex geometries at large Reynolds (Re) numbers without any heuristic turbulence modeling. The software will build upon prior work by the proposer who developed a novel flexion-based Large Eddy Simulation (LES) method for high Re turbulent flows. The LES method uses the flexion (vorticity curl) vector as the primary dependent variable in the Navier-Stokes equations to better track sharp vorticity-gradient regions in high Re flows. The method also uses hyperviscous dissipation instead of a parameterized sub-grid model for unresolved small-scale turbulent motions. The flexion-based LES method will be extended to complex geometries by coupling it with a vortex panel method for the body surface. The vortex panel method leads to accurate predictions of the shear stress on wall boundaries from the wall vorticity without the computationally demanding requirement of a fine mesh to resolve the thin boundary layers that occur in high Re flows. The proposed approach represents a new technique of using panel methods, which have a rich history in aerodynamics, to provide boundary conditions for large eddy simulations of the vortical wake.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.

该小型企业创新研究 (SBIR) 第一阶段项目的更广泛影响是加速开发涉及使用计算流体动力学 (CFD) 软件的复杂湍流流体的创新工业设计概念。该公司特别感兴趣的是具有强烈垂直尾流的物体，例如仿生可再生能源提取装置和电动垂直起降（eVTOL）车辆，预计该项目可能会带来及时且经济高效的能源提取设计。设备无需在设计阶段构建和测试原型，该项目还可以提高城市空中交通车辆的安全性和运行范围。拟议的基于云的 CFD 软件将为初创公司和小型公司提供服务（无需使用高性能计算）。 ）资源）能够在合理的时间范围内执行 CFD 分析，所提议的纳维-斯托克斯方程的新颖重新表述也将对下一代工程师和科学家的教育产生持久影响，因为他们可以更好地了解其优势。新的方程组为这个小型企业创新研究 (SBIR) 第一阶段项目旨在开发一种快速高保真计算流体动力学 (CFD) 软件，用于预测大雷诺 (Re) 数下复杂几何形状的不稳定流动分离，而无需任何启发式湍流建模。该软件将建立在提案者之前的工作基础上，该提案者开发了一种新颖的基于弯曲的大涡模拟（LES）方法，用于高回流湍流。LES 方法使用弯曲（涡度）。旋度）向量作为纳维-斯托克斯方程中的主要因变量，以更好地跟踪高 Re 流中的尖锐涡度梯度区域。该方法还使用超粘性耗散而不是参数化子网格模型来解决未​​解决的小规模湍流运动。基于 LES 的方法将通过与身体表面的涡流板方法相结合而扩展到复杂的几何形状。涡流板方法可以实现准确的预测。该方法代表了一种使用面板方法的新技术，该方法在空气动力学领域有着丰富的历史。 ，为涡流尾流的大涡流模拟提供边界条件。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。