LAUSR

This study demonstrates the feasibility of conducting on-site large-scale image-based measurements for indoor airflows characterisation. To illustrate the potential of our method, we chose to study the suction flow generated by a laboratory fume hood in operating conditions. As a matter of fact, laboratory fume hoods are frequently subject to routine checks during which air speed measurements by hot-wire anemometry are performed. However, classical point-to-point hot-wire anemometry may be not sufficient to detect and locate potential leakages. To improve these controls, we developed and tested a new method based on particle image velocimetry principles, which is non-intrusive and authorizes a good spatio-temporal analysis. To face large-scale and on-site issues, we had to make some adaptations. For this reason, we used tracers like bubbles or smoke which have good scattering properties. We also developed our own low-cost light system. To compute velocities from image sequences, we developed an optical flow algorithm based on a large-scale flow model instead of using traditional correlation. The tested method gave good results with a good agreement with sparse hot-wire anemometry measurements but with a wider spatial distribution. In addition, the method provided turbulence intensity estimation and a good monitoring of dynamic flow features, which is important for the detection of leakages.