Experimental analysis demonstrates improved efficiency in measuring turbulent boundary layer dynamics, suggesting advantages of parallel computing and specific algorithms.
The wavenumber-frequency spectrum (W-F spectrum) of turbulent boundary layer wall pressure fluctuations holds considerable significance in various engineering applications. Experimental assessments of the W-F spectrum are predominantly conducted using a surface array, with data processed through the Direct Measurement Algorithm (DMA). In this study, a novel 1D DMA, based on the Cross Spectrum Matrix, was developed to obtain the W-F spectrum of TBL-WPFs using a linear surface array. This development was founded on the assumptions of temporal stationarity and spatial homogeneity; an averaging method is employed to reduce errors and enhance robustness. Additionally, the DMA is specifically designed for parallel computing, which significantly enhances efficiency. To validate the 1D DMA, an experiment was conducted in the wind tunnel, employing a 32-channel MEMS linear surface array, alongside hot-wire tests to determine the boundary layer characteristics. The W-F spectral results were compared to the Chase I model. The study concluded that the DMA can effectively capture the acoustic region of the W-F spectrum and can provide accurate measurement results for the sub-convective, convective, and viscous regions, thereby confirming the utility of the algorithm. Furthermore, the efficiency of parallel computing was analyzed, and the performance of the parallel computing capabilities of the DMA was evaluated. It is affirmed that parallel computing, when combined with the application of conjugacy, can decrease computational time to enhance efficiency, with its advantages becoming increasingly evident as the number of sensors in the surface array increases.
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Zhao et al. (2025) studied this question.
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