Viscous Extension of the Classical Theory of Unsteady Aerodynamics

经典非定常空气动力学理论的粘性推广

基本信息

批准号：
2005541
负责人：
Haithem Taha
金额：
$ 30万
依托单位：
University of California-Irvine
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-05-15 至 2024-04-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2005541&HistoricalAwards=false
关键词：
Viscous Extension Classical Theory Unsteady

项目摘要

The current state-of-the-art of fluid dynamic models of the flow over wing sections are either computationally too expensive to be used in preliminary design phases or overly simplified, neglecting some essential physics. The objective of this proposal is to fill this gap by developing efficient aerodynamic models that capture the main physics of the flow dynamics. Relying on a unique combination of the fundamental knowledge of basic unsteady aerodynamics and the recent advances in data science (for example, machine learning techniques), this project will yield more realistic computations of the aerodynamic loads. The developed theory will be indispensable for preliminary design of next generation flying vehicles (flying taxis, micro-air-vehicles, and drones) and wind turbines, which will improve national security and economic prosperity. The project will include the development of a graduate course on unsteady aerodynamics based on this research, plans are underway to develop a textbook on the subject, and undergraduate students will be involved byway of aerodynamic-related senior projects.Realizing that the lift generation and vorticity production are essentially viscous processes, a viscous extension of the classical theory of unsteady aerodynamics is proposed. This extension will be achieved by coupling the potential theory with a special boundary layer theory that resolves the flow details in the vicinity of the trailing edge. This approach will provide the circulation dynamics without any need for an auxiliary condition (i.e., Kutta-like condition). Moreover, to generalize this approach, machine learning tools will be employed to extract information about the circulation dynamics from high-fidelity simulations. This modeling approach can be conceptually described by a bow tie architecture: a compressive mapping taking a high-dimensional input space (e.g., flow field from high-fidelity simulation) to a smaller, more compact lower-dimensional core model (e.g., one-dimensional circulation dynamics). Then, the potential flow theory, with the accurate circulation dynamics, will be used to recover a high-dimensional output space of the flow field.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.

当前最先进的机翼流动流体动力学模型要么计算成本太高而无法在初步设计阶段使用，要么过于简化，忽略了一些基本的物理原理。该提案的目的是通过开发有效的空气动力学模型来捕获流动动力学的主要物理原理，从而填补这一空白。依靠基本非定常空气动力学的基础知识和数据科学的最新进展（例如机器学习技术）的独特结合，该项目将产生更真实的空气动力载荷计算。所开发的理论对于下一代飞行器（飞行出租车、微型飞行器和无人机）和风力涡轮机的初步设计是不可或缺的，这将提高国家安全和经济繁荣。该项目将包括基于这项研究开发非定常空气动力学研究生课程，并计划编写该主题的教科书，本科生将通过空气动力学相关的高级项目参与其中。认识到升力的产生和涡度生产本质上是粘性过程，因此提出了非定常空气动力学经典理论的粘性扩展。这种扩展将通过将势理论与特殊的边界层理论相结合来实现，该边界层理论可以解决后缘附近的流动细节。这种方法将提供循环动力学，而不需要任何辅助条件（即类库塔条件）。此外，为了推广这种方法，将采用机器学习工具从高保真模拟中提取有关循环动态的信息。这种建模方法可以从概念上用领结架构来描述：将高维输入空间（例如，来自高保真模拟的流场）压缩映射到更小、更紧凑的低维核心模型（例如，一维模型）维度循环动力学）。然后，利用势流理论，结合精确的环流动力学，恢复流场的高维输出空间。该奖项体现了NSF的法定使命，并通过利用基金会的智力优势和评估结果进行评估，认为值得支持。更广泛的影响审查标准。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Static and Dynamic Characteristics of the Aerodynamic Forces on Pitching Airfoils between 0 to 360 degrees Angle of Attack

0~360°迎角俯仰翼型气动力的静动态特性

DOI：
10.2514/6.2022-1663
发表时间：
2022-01
期刊：
AIAA SciTech
影响因子：
0
作者：
Fouda, Moatasem;Khalifa, Nabil M.;Rashad, Mahmoud M.;Shao, Mingdong;Elsharif, Mostafa;Taha, Haitham E.
通讯作者：
Taha, Haitham E.

Compressible Unsteady Aerodynamic Loads on Oscillating Airfoils in a Subsonic Flow

亚音速流中振荡翼型的可压缩非定常气动载荷