Near-wall Lagrangian particle tracking velocimetry using event-based imaging

Abstract

We describe the implementation of a particle tracking velocimetry (PTV) system based on event-based vision (EBV) and demonstrate its application for the characterization of a turbulent boundary layer (TBL) in air. One configuration uses a single event-camera to image a narrow light sheet extending wall-normal from the wall to obtain the time-resolved velocity profile. In the other configuration a thin light sheet grazes the surface of a glass window illuminating only the viscous sublayer of the turbulent boundary layer. The data simultaneously captured by three synchronized event-cameras is used to reconstruct the 3d particle tracks within a few 100 µm of the wall. Particle movement within the viscous sub-layer permit the estimation of the local, instantaneous wall shear stress under the assumption of linearity between particle velocity and wall shear stress. Thereby 2d distributions of the instantaneous wall shear stress are obtained. PTV tracking algorithms that are orders magnitude faster than correlation-based schemes provide data quality on par with currently used, considerably more expensive, high-speed PIV hardware.