Symmetry-reduced low-dimensional representation of large-scale dynamics in the asymptotic suction boundary layer

An important feature of turbulent boundary layers are persistent large-scale coherent structures in the flow. Here, we use Dynamic Mode Decomposition (DMD), a data-driven technique designed to detect spatio-temporal coherence, construct optimal low-dimensional representations such dynamics asymptotic suction layer (ASBL). In ASBL, fluid is removed by through bottom wall, resulting constant thickness streamwise direction. That is, advection mean flow ceases be dynamical importance and can interpreted as continuous shift symmetry However, this results technical difficulties, DMD known perform poorly presence symmetries. We address issue using symmetry-reduced (Marensi et al., 2023), find ASBL indeed potentially self-sustained, featuring ejection sweeping events at large scale. Interactions with near-wall captured when including only few more modes.