Particle image velocimetry is the most widely used optical technique for measuring two-dimensional velocity fields in fluids. However, with the standard cross-correlation algorithm, improving the spatial resolution of instantaneous velocity fields and obtaining dense velocity fields in real time and at high frequencies remains challenging. Optical flow velocimetry (OFV) provides an alternative route to per-pixel velocimetry. In this study, we show that dense velocity fields (one vector per pixel) with high effective spatial resolution can be obtained in real time at frequencies up to kHz using an optical flow approach. First, using synthetic images on two cases (a well-defined Rankine vortex and a homogeneous isotropic turbulence DNS dataset), we show that resolving large displacement gradients down to small scales is feasible when the particle seeding is appropriately tuned. Second, we show that real-time processing rates can be achieved through algorithmic and GPU-oriented optimizations, together with appropriate choices of optical flow parameters. With this implementation, 21 Mp velocity fields are measured in real time (live) at 90 Hz, while 4 Mp velocity fields can be measured up to 460 Hz and 1 Mp velocity fields can be measured up to 1400 Hz. The approach is further validated on experimental measurements of the flow past a circular cylinder, where dense instantaneous fields are obtained and used to compute derived quantities in real time over long durations. These processing rates enable real-time computation of derived flow quantities during experiments, including long-duration monitoring, low-frequency dynamics captured from sustained high-rate acquisition, and closed-loop flow-control strategies based on OFV measurements. In addition to enabling live operation, the approach accelerates standard off-line postprocessing, reducing turnaround time and computational cost.

Close

PrevNext

View figure in article

• Turbulence
• Particle image velocimetry