Experimental Detection of Organised Motion in Complex Flows with Modified Spectral Proper Orthogonal Decomposition

Abstract

Spectral proper orthogonal decomposition (SPOD) has seen renewed interest in recent years due to its unique ability to decouple organised motion at different timescales from large datasets with limited available information. This paper investigated the unsteady components of the flow field within a simplified turbine centre frame (TCF) model by applying SPOD to experimental, time-resolved flow speed data captured by particle image velocimetry (PIV). It was observed that conventional methods failed to capture the two significant active bands in the power spectrum predicted by preliminary hot wire anemometry measurements. Therefore, a modification to the SPOD procedure, which employs subsampling of the time sequence recorded in the experiment to artificially lower the PIV data acquisition frequency, was developed and successfully deployed to analyse the TCF flow field. The two dynamically active bands were identified in the power spectra, resulting in a closer match to the preceding analyses. Within these bands, SPOD’s ability to capture spatial coherence was leveraged to detect several plausible coherent, fluctuating structures in two perpendicular planes. A partial three-dimensional reconstruction of the flow phenomena suggested that both bands were associated with a distinct mode of organised motion, each contributing a significant percentage of the system’s total fluctuating energy.