Instantaneous skin-friction pattern analysis using automated critical point detection on near-wall PIV data

Near-wall PIV provides qualitative and quantitative information that can be used to analyse the skin-friction pattern of the flow around a wall-mounted cube. This is addressed by a brief comparison between oil-flow visualizations and near-wall mean velocity fields. This approach is expanded to the analysis of instantaneous pseudo shear-stress patterns obtained from PIV. A post-processing algorithm based on proper orthogonal decomposition and critical point identification is devised for this purpose. It is shown to be very robust and efficient. A statistical analysis of its results enables us to automatically extract the salient features of the resulting POD filtered instantaneous velocity fields: their critical points type, distribution and connectivity. It provides valuable insights into the time-dependent behaviour of the flow. Issues associated with the interpretation of such results are discussed.