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.