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Dynamic mode decomposition (DMD) is a data-driven technique widely used toanalyze and model fluid problems including transonic buffet flows. Despite itsstrengths, DMD is known to suffer from sensitivities to the selected settingsand the characteristics of the employed data. In this work, we closely examinethe aforementioned sensitivities, identify possible pitfalls, and provide bestpractices to robustly perform DMD on a flow exhibiting transonic shock buffet.Specifically, we assess various DMD variants and test their sensitivity to thePOD rank truncation and the sampling rate. A critical enabler to our analysisis a new presentation of the DMD algorithm as a modular framework consisting offive distinct steps. The tests also highlight the existing dangers of aliasing,when the sampling rate is too low. Finally, a list of practical recommendationsand guidelines on how to accurately and robustly perform DMD on a transonicbuffet flow is provided.

A robust dynamic mode decomposition methodology for an airfoil undergoing transonic shock buffet