Pollutant dispersion in a large indoor space: Part 1 -- Scaled experiments using a water-filled model with occupants...

Scale modeling is a useful tool for analyzing complex indoor spaces. Scale model experiments can reduce experimental costs, improve control of flow and temperature conditions, and provide a practical method for pretesting full-scale system modifications. However, changes in physical scale and working fluid (air or water) can complicate interpretation of the equivalent effects in the full-scale structure. This paper presents a detailed scaling analysis of a water tank experiment designed to model a large indoor space, and experimental results obtained with this model to assess the influence of furniture and people in the pollutant concentration field at breathing height. Theoretical calculations are derived for predicting the effects from losses of molecular diffusion, small scale eddies, turbulent kinetic energy, and turbulent mass diffusivity in a scale model, even without Reynolds number matching. Pollutant dispersion experiments were performed in a water-filled 30:1 scale model of a large room, using uranine dye injected continuously from a small point source. Pollutant concentrations were measured in a plane, using laser-induced fluorescence techniques, for three interior configurations: unobstructed, table-like obstructions, and table-like and figure-like obstructions. Concentrations within the measurement plane varied by more than an order of magnitude, even after the concentration field was fully developed. Objects in the model interior had a significant effect on both the concentration field and fluctuation intensity in the measurement plane. PRACTICAL IMPLICATION: This scale model study demonstrates both the utility of scale models for investigating dispersion in indoor environments and the significant impact of turbulence created by furnishings and people on pollutant transport from floor level sources. In a room with no furniture or occupants, the average concentration can vary by about a factor of 3 across the room. Adding furniture and occupants can increase this spatial variation by another factor of 3.