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Algorithmic and Visual Aids for Physical Discovery Using Bispectral Mode Decomposition

Abstract

Triadic interactions are the fundamental mechanism of energy transfer in fluid flows and arise due to the quadratic non-linearity of the Navier-Stokes equation. The bispectral mode decomposition (BMD) is a direct means of revealing flow structures that are associated with these interactions and accomplishes this by computing modes generated by the interaction of two separate modes. The mode bispectrum, summed mode spectrum, and bispectral modes are the primary results produced through the use of the BMD, with local maxima in the mode bispectrum and summed mode spectrum representing the most prominent triadic interactions of the flow.

However, these results are often difficult to analyze due to uncertainty in determining what constitutes a local maxima. In this work, a radial search algorithm that has been developed is applied to both the mode bispectrum and summed mode spectrum of open cavity flow data to find their respective maxima. Once found, these maxima are reconstructed into two new visual aids, the sparse mode bispectrum and an arrangement of the bispectral modes. The sparse mode bispectrum condenses the results of radially searching the mode bispectrum and summed mode spectrum, while local maxima found through the radial search of the mode bispectrum have their corresponding bispectral modes arranged in the relative shape of the mode bispectrum. These visualizations aim to present the most important information and results from the BMD according to the radial search algorithm, allowing for the identification of the most pertinent flow physics while also easing the use of the BMD.

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