On-site airflow measurement of a laboratory fume hood using customized large-scale image-based velocimetry. Issue 6 (July 2020)

• Record Type: Journal Article
• Authors: Schuster, Romain; Heitz, Dominique; Georgeault, Philippe; Mémin, Etienne
• Other Names: Kosonen Risto guest-editor.
• Is Part Of: Indoor + built environment. Volume 29:Issue 6(2020)
• Page Start: 810
• Page End: 819
• Publication Date: 2020-07
• Subjects: Laboratory fume hood -- Large-scale velocimetry -- Optical flow -- Air leakage detection -- Turbulence intensity; Indoor air pollution -- Periodicals; Sick building syndrome -- Periodicals; Buildings -- Environmental engineering -- Periodicals; Environmental health -- Periodicals; 613.5
• DOI: 10.1177/1420326X19865928
• Languages: English
• ISSNs: 1420-326X

Abstract

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.