Abstract
Flow velocity measurements using particle tracking velocimetry carried out in a scale model of a vertical-slot fish pass are analysed using proper orthogonal decomposition. Based on the analysis, the oscillating main stream and related time-varying processes are identified as dominant repeating flow processes. In particular, the time coefficients of the modes are examined in detail. Firstly, the cross-correlation functions of the time coefficients are used to identify the modes best representing this process. Secondly, the time series of coefficients themselves are used to identify the temporal occurrences of the repeating process even when the occurrences are neither identical nor periodical. The presented methodology reduces the examination of the full measured velocity dataset to an analysis of a limited number of coefficient time series, which can be used to detect the occurrences of flow processes repeating at irregular time intervals, and hence to describe their temporal evolution.
Published Version
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