论文标题
光谱分析模态方法（SAMMS）使用非时期分辨PIV
Spectral Analysis Modal Methods (SAMMs) using Non-Time-Resolved PIV
论文作者
论文摘要
我们提出光谱分析模态方法（SAMM），使用非时期分辨粒子图像速度（PIV）数据与不稳定的表面压力测量相结合，以在频域中执行POD。特别地，时间分辨的不稳定表面压力测量与在0.6腔流量中以15 Hz获取的非时空平面PIV测量同步。利用Tinney等人的光谱线性随机估计（LSE）方法。 （2006年），我们首先估计速度场与不稳定压力传感器之间的跨相关性，然后进行快速的傅立叶变换以获得压力速度跨频谱密度矩阵。这导致了线性多输入 /多输出（MIMO）模型，该模型决定了输入腔壁压力与输出速度场之间的最佳传递函数。开发和应用了两种SAMM的变体。第一个称为“ Samm-Spod”，将MIMO模型与Towne等人的Spod算法相结合。 （2018）。 The second, called "SAMM-RR'', adds independent sources and uses a sorted eigendecomposition of the input pressure cross-spectral matrix to enable an efficient reduced-rank eigendecomposition of the velocity cross-spectral matrix. In both cases, the resulting rank-1 POD eigenvalues associated with the Rossiter frequencies exhibit very good agreement with those obtained using independent time-resolved PIV measurements.结果表明，SAMMS提供了执行时空POD的方法，而无需高速PIV系统，同时避免了与传统时间域LSE相关的潜在陷阱。
We present spectral analysis modal methods (SAMMs) to perform POD in the frequency domain using non-time-resolved Particle Image Velocity (PIV) data combined with unsteady surface pressure measurements. In particular, time-resolved unsteady surface pressure measurements are synchronized with non-time-resolved planar PIV measurements acquired at 15 Hz in a Mach 0.6 cavity flow. Leveraging the spectral linear stochastic estimation (LSE) method of Tinney et al. (2006), we first estimate the cross correlations between the velocity field and the unsteady pressure sensors via sequential time shifts, followed by a Fast Fourier transform to obtain the pressure-velocity cross spectral density matrix. This leads to a linear multiple-input / multiple-output (MIMO) model that determines the optimal transfer functions between the input cavity wall pressure and the output velocity field. Two variants of SAMMs are developed and applied. The first, termed "SAMM-SPOD", combines the MIMO model with the SPOD algorithm of Towne et al. (2018). The second, called "SAMM-RR'', adds independent sources and uses a sorted eigendecomposition of the input pressure cross-spectral matrix to enable an efficient reduced-rank eigendecomposition of the velocity cross-spectral matrix. In both cases, the resulting rank-1 POD eigenvalues associated with the Rossiter frequencies exhibit very good agreement with those obtained using independent time-resolved PIV measurements. The results demonstrate that SAMMs provide a methodology to perform space-time POD without requiring a high-speed PIV system, while avoiding potential pitfalls associated with traditional time-domain LSE.
