Data-driven control of the turbulent flow past a cylinder

A data-driven approach is employed to control vortex shedding on a circular cylinder for Reynolds numbers 100 and 20,000. The methodology used in this study identifies the spatial location of the non-linear forcing which drives the oscillatory wake by performing a Proper Orthogonal Analysis (POD) based on a Singular Value Decomposition (SVD) constructed from a set of data-snapshots of the flow-field. The location containing the highest forcing is then targeted with a passive device to control the flow. It is shown, that for Re= 100 a suppression of 15% of the highest forcing is adequate to fully control vortex shedding while for Re= 20,000 a suppression of 50% is necessary to inhibit vortex formations. Turbulent flow results are obtained by extending the DNS data-driven methodology to a RANS formulation. Results obtained in this study are in good agreement with previous experimental approaches in controlling vortex shedding on cylinders.