arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2011.04632physics.flu-dynphysics.comp-phphysics.data-an
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涡主导流中单个涡的运动学和诱导气动载荷的定量分析:计算和数据驱动的方法

Quantitative analysis of the kinematics and induced aerodynamic loading of individual vortices in vortex-dominated flows: a computation and data-driven approach

Karthik Menon, Rajat Mittal

摘要:

本文提出了一种基于物理的数据驱动计算框架,用于涡主导问题中涡运动学和涡致载荷的定量分析。这种流动的特点是少数涡结构的主要影响,但这些流动的复杂性使得难以在单个涡的水平上对这种影响进行定量分析。本文提出的方法将机器学习启发的聚类方法与气动载荷的严格数学划分相结合,以实现对涡运动学和涡致气动载荷的详细定量分析。我们证明了这种方法的实用性,将其应用到一个合奏的165个不同的Navier-Stokes模拟流过去的正弦俯仰翼型。目前的方法使见解,包括在这个流的周期加倍路径的混沌的识别,和精确的量化的作用,前缘涡驱动气动弹性俯仰振荡。

英文摘要:

A physics-based data-driven computational framework for the quantitative analysis of vortex kinematics and vortex-induced loads in vortex-dominated problems is presented. Such flows are characterized by the dominant influence of a small number of vortex structures, but the complexity of these flows makes it difficult to conduct a quantitative analysis of this influence at the level of individual vortices. The method presented here combines machine learning-inspired clustering methods with a rigorous mathematical partitioning of aerodynamic loads to enable detailed quantitative analysis of vortex kinematics and vortex-induced aerodynamic loads. We demonstrate the utility of this approach by applying it to an ensemble of 165 distinct Navier-Stokes simulations of flow past a sinusoidally pitching airfoil. Insights enabled by the current methodology include the identification of a period-doubling route to chaos in this flow, and the precise quantification of the role that leading-edge vortices play in driving aeroelastic pitch oscillations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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