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Dynamic mode Decomposition of Numerical and Experimental Data

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Even though modern experimental techniques produce flow fields that rival numerically generated data in terms of spatial and temporal resolution, the methods that analyze and quantify these experimental data lag far behind the possibilities available for numerical simulations. The reason for this discrepancy is the necessity of a model equation to extract relevant flow information using standard decomposition techniques. A new data-based method will be introduced and demonstrated that, using only snapshots, is capable of identifying dynamically relevant temporal and spatial scales in form of spectral information and modal structures. Applications of this method to experimental and numerical data will range from simple flames to wake flows, from acoustically active flows to a jet in crossflow.

This talk is part of the BPI Seminar Series series.

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