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.

这项小型企业创新研究（SBIR）I期项目的更广泛影响是加速了使用计算流体动力学（CFD）软件的创新工业设计概念的开发，涉及复杂的湍流流量。尽管CFD软件在多个行业中具有广泛的应用，但该公司特别感兴趣的是具有强烈涡流唤醒的身体，例如生物启发的可再生能源提取设备和电动垂直起飞/着陆（EVTOL）车辆。预计该项目可能会导致能源提取设备的及时且具有成本效益的设计，而无需在设计阶段构建和测试原型。该项目还可以增强城市空气流动车辆的安全性和操作信封。拟议的基于云的CFD软件将提供初创企业和较小的公司（无需访问高性能计算资源），并能够在合理的时间范围内执行CFD分析。提议的Navier-Stokes方程式的新颖改革还将对下一代工程师和科学家的教育产生持久影响雷诺（Reynolds）（RE）数字，没有任何启发性的湍流建模。该软件将由提案的先前工作基础，该提案开发了一种新型的基于屈曲的大型涡流模拟（LES）方法，用于高湍流。 LES方法使用屈曲（涡度卷曲）向量作为Navier-Stokes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。该方法还使用过度通知的耗散，而不是用于未解决的小规模湍流运动的参数化子网格模型。基于屈肌的LES方法将通过将其与涡流面板方法耦合到身体表面，将其扩展到复杂的几何形状。涡流面板方法可准确预测壁涡度壁边界对壁边界的剪切应力，而无需计算要求细网以解决高回流中发生的薄边界层。所提出的方法代表了一种使用面板方法的新技术，该方法具有丰富的空气动力学历史，可为涡旋唤醒的大型涡流模拟提供边界条件。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准来评估通过评估而被认为是珍贵的。