Speaker
Description
Laboratory-scale rotating-tank experiments are used for demonstration purposes and for investigating scaling laws in geophysical fluid dynamics. Quantitative studies using affordable outreach-focused rotating tank setups are challenging and usually depend on manual measurements and narrative-based protocols prepared by the exerimenters. This talk outlines a processing pipeline for videos of a rotating tank which allows for optical quantitative investigation of dye concentration, velocity, and trajectories of submerged particles in a 'Weather in a Tank' rotating table (MIT). The pipeline supports detection and correction of rotation and perspective, and provides object tracking optical-flow diagnostics. It emits transformed and corrected video output, as well gridded numerical datasets of dye concentration, of velocity and vorticity estimates, and tabular numerical datasets of particle trajectories. The talk also outlines the mainly agentic-AI-based development process of the end-to-end processing pipeline. It highlights challenges and surprises related to general scientific knowledge and geometric reasoning of the coding agent.