Conditional averaging of PIV plane wake data using a cross-correlation approach

A new approach is investigated for conditional averaging of a series of random snapshots of periodic velocity fields obtained from PIV measurements. This approach departs from conventional conditional averaging approaches that require a reference signal for extracting phase information and uses the cross-correlation between the velocity fields as a phase identifier. The methodology is applied on the natural and forced turbulent wake of a circular cylinder, the latter serving also as a validation/verification case. The results show that the vortex formation and shedding processes in the wake are drastically affected by inflow oscillations and reveal the underlying vortex dynamics. Additionally, detailed velocity measurements are reported for the two cases investigated.