The long-term goal of this competing continuation proposal remains incorporating techniques from computational fluid dynamics into the design process for local exhaust ventilation (LEV). This work will evaluate the use of numerical air flow models to reduce worker exposure to aerosols and solvent vapors in an actual spray-painting operation. It will extend recent computational and laboratory studies to a more applied level. The numerical simulations will assess work practices used in combination with ventilation to control worker exposure. The primary hypothesis is that lowest exposure results when the worker is to the side of the object being painted, with the spray gun in the downstream hand; rather than standing in front of the work piece as is typically the case.
The specific aims are: (1) Improve existing algorithms to generate predictions of breathing zone concentration for the work practices described in the primary hypothesis above, and incorporating factors listed in specific aim (3). (2) Construct a working laboratory model of a spray operation using a moveable mannequin and compressed air spray gun. The model will be placed within our wind tunnel to simulate a spray booth. (3) Conduct experiments using the laboratory model to calibrate numerical predictions of exposure and validate the primary hypothesis; the following parameters will be examined: (a) wind tunnel air velocity, (b) mannequin mobility, ~ orientation of mannequin to air flow, (d) contaminant generation rate, and (e) whether the spray gun is in the upstream or downstream hand. Concentration measurements of tracer gas and aerosols will be made from the mannequin's breathing zone. (4) Use flow visualization to confirm numerically predicted flow patterns, and to demonstrate the effects of boundary layer separation. Smoke wires will be used to produce video recordings of the flow patterns. (5) Conduct a field validation of the model in actual spray paint booths. Personal samples will be taken to confirm the primary hypothesis, and evaluate the numerical predictions of worker exposure.
