Investigation of Data Acquisition Conditions for Dynamic Mode Decomposition in Unsteady PSP Measurement

T. Ikami, Koji Fujita, H. Nagai, Yutaro Matsuda, Y. Egami
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Abstract

Pressure-Sensitive-Paint (PSP) can measure a surface pressure field. Recently, fast-PSPs have been developed and applied to a visualization of the unsteady aerodynamic phenomenon. In general, the amount of unsteady aerodynamic visualization data is enormous. The Dynamic Mode Decomposition (DMD) technique can efficiently extract spatial and dynamic characteristics from enormous data. However, some data acquisition conditions for correctly discussing the flow field using DMD are still unclear. In particular, it is important to know the appropriate sampling frequency for specific aerodynamic phenomena. In this study, Karman vortexes in the wake of a square cylinder are visualized by the fast-PSP. Moreover, by using the unsteady PSP data, the time resolution of the input data is changed, and the influence on the DMD analysis for the Karman vortices is investigated. We find that the time resolution does not affect the flow structure of the DMD mode. On the other hand, the dynamic characteristics of the flow structure approach the true value when the time resolution is increased.
非定常PSP测量中动态模态分解数据采集条件研究
压敏涂料(PSP)可以测量表面压力场。近年来,快速psps技术得到了发展,并应用于非定常气动现象的可视化。一般来说,非定常气动可视化数据的数量是巨大的。动态模态分解(DMD)技术可以有效地从海量数据中提取空间和动态特征。然而,利用DMD正确讨论流场的一些数据采集条件尚不清楚。特别是,对于特定的空气动力学现象,知道合适的采样频率是很重要的。在这项研究中,卡门涡在一个方形圆柱体的尾迹是可视化的快速psp。此外,利用非定常PSP数据,改变输入数据的时间分辨率,并研究其对卡门涡DMD分析的影响。我们发现时间分辨率不影响DMD模式的流结构。另一方面,随着时间分辨率的提高,流动结构的动态特性趋于真实值。
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