论文标题
TR-PIV数据的多尺度正交分解（MPOD） - 关于固定和瞬态气缸尾流的案例研究
Multiscale Proper Orthogonal Decomposition (mPOD) of TR-PIV data-- a Case Study on Stationary and Transient Cylinder Wake Flows
论文作者
论文摘要
粒子图像速度计（PIV）测量的数据驱动的分解被广泛用于多种目的，包括检测相干特征（例如涡流结构），过滤操作（例如，过滤效果或随机噪声降低或随机噪声缓解），数据减少和压缩。这项工作介绍了一种新型分解方法的应用，称为多尺度正交分解（Mendez J Fluid Mech 870：988-1036，2019）在时间分辨PIV（TR-PIV）测量中。该方法结合了多分辨率分析（MRA）和标准正确的正交分解（POD），以实现所得模式的分解收敛和光谱纯度之间的折衷。 选定的测试用例是在固定条件和瞬态条件下流过气缸的流量，产生了频率变化的Karman Vortex街。将MPOD的结果与标准POD，离散傅立叶变换（DFT）和动态模式分解（DMD）进行比较。根据其模式的分解收敛和时频定位评估MPOD。由于流动的三维性质，多尺模态分析允许在固定气缸唤醒中揭示Beat现象，并正确地识别了瞬态测试案例中各种固定机制的过渡。
Data-driven decompositions of Particle Image Velocimetry (PIV) measurements are widely used for a variety of purposes, including the detection of coherent features (e.g., vortical structures), filtering operations (e.g., outlier removal or random noise mitigation), data reduction and compression. This work presents the application of a novel decomposition method, referred to as Multiscale Proper Orthogonal Decomposition ( Mendez J Fluid Mech 870:988-1036, 2019) to Time-Resolved PIV (TR-PIV) measurement. This method combines Multiresolution Analysis (MRA) and standard Proper Orthogonal Decomposition (POD) to achieve a compromise between decomposition convergence and spectral purity of the resulting modes. The selected test case is the flow past a cylinder in both stationary and transient conditions, producing a frequency-varying Karman vortex street. The results of the mPOD are compared to the standard POD, the Discrete Fourier Transform (DFT) and the Dynamic Mode Decomposition (DMD). The mPOD is evaluated in terms of decomposition convergence and time-frequency localization of its modes. The multiscale modal analysis allows for revealing beat phenomena in the stationary cylinder wake, due to the three-dimensional nature of the flow, and to correctly identify the transition from various stationary regimes in the transient test case.
