Low cost camera array for large-scale, slow-flow wind tunnel visualization

Quantitative flow visualization for large scale environments often include costly equipment with relatively small fields of view compared to the experimental measurement volume. To avoid the tedious task of moving a single camera to different locations or the expensive purchase of multiple cameras, we are presenting a nine-camera Raspberry Pi array that is able to capture bubbles moving through a 18 m³ volume in a slow-flow turbulent atmospheric boundary layer wind tunnel at the University of New Hampshire. This low-cost visualization method has allowed us to track bubbles moving through an increased measurement volume, compared to a traditional high-speed camera with a much smaller measurement volume.

In this presentation we show the preliminary diagnostic set-up and validation for slow flow conditions (1m/s) and discuss limitations of using the Raspberry-Pi camera and board combination. We also discuss the next steps for the project including measurements for different types of flow tracers, like fog, and potential future applications.