Abstract
I will describe a non-iterative ray tracing methodology coupled with a robust post-capture microlens array-sensor alignment procedure tailored explicitly for characterizing particle and fluid dynamics. This approach facilitates a rapid reconstruction of sparsely distributed particle concentrations within the context of light field particle image velocimetry and particle tracking velocimetry. Unlike traditional intensity-based 3D reconstruction techniques, we employ a ray counting methodology to reconstruct three-dimensional structures. It accounts for the propagation of rays throughout the experimental volume, thereby mitigating memory constraints and significantly reducing computational time. A physics-based simulation encompassing a variety of lens configurations, including microscopy, is used to evaluate and quantify uncertainty. An optical cage system is designed to house these lenses and facilitate the capture and analysis of three-dimensional flow patterns and particle trajectories.
About the Speaker
Ph.D. candidate in Theoretical and Applied Mechanics with an MS in Mechanical Engineering at Purdue University. My research primarily centers on developing multi-view and sensor calibration within a range of environments and characterizing 3D motion and deformation tracking and detection using parallelized algorithms. Leveraging my expertise in vision sensors and advanced 3D reconstruction techniques, I have effectively tackled various challenging problems in fluid dynamics.
Host: Professor Leonardo Chamorro
