Rapid meso-scale 3D PIV and PTV with plenoptic macro photography

Describing fluid flows and particle motion at mesoscale with multi-camera setups presents numerous challenges, including limited illumination, constrained space, shallow depth of field, and particular calibration requirements. We propose a novel optical train design with a feature-based calibration method tailored for commercial macro lenses. By incorporating a microlens array (MLA) into the intermediate plane between the macro lens and camera sensor, we achieve effortless calibration of a singular camera cage system without any additional operations on the camera system, effectively minimizing experimental noise. We conducted a ray tracing-based simulation employing a realistic macro lens model to assess the uncertainty associated with GPU-accelerated ray intersection and cloud point classification methods. We performed a Lagrangian particle tracking around a jet flow as a proof-of-concept.