Numerical modeling of aerosol concentration.
NIOSH 2005 Aug; :1-13
This research focused on improving the use of computational fluid dynamics (CFD) and associated numerical methods to predict size-specific aerosol concentrations with emphasis on human exposure and health. The focus was on determining uncertainties in both simulated and measured concentrations to assess the performance of the three-dimensional, steady-state k-epsilon turbulence model. Currently this is the most commonly used CFD model in applied occupational hygiene studies. Both two and three-dimensional simulations were performed using several different turbulence models with the commercial software FIDAP. In addition an in-house, 2-d time dependent vortex code was run with particle tracking. Simulations employed circular and elliptical cylinders as surrogate human forms, but in addition, a highly realistic 3-d simulation of the human form was used for aspiration studies and compared with data taken with a mannequin in wind tunnel studies. This research identified a significant overestimation bias (a factor of 10 or more) in the use of the standard k-epsilon model to predict aerosol exposures when wake effects are important (worker in the back-to-flow orientation with proximal source). This error is likely to exist with all steady-state CFD simulations containing scalar coefficients of eddy viscosity (e.g. the RNG models as well). Reynolds -Stress turbulence closures may offer some improvement in the near term for steady-state approximations, but 3-d time-dependent simulations will eventually be needed. Resource requirements are prohibitive at present for meaningful error analysis to be conducted on such simulations. However, the steady-state k-epsilon model, with a laminar trajectory option for aerosols was very successful in predicting aspiration efficiencies in the facing-the-wind orientation (a configuration that is not impacted by unsteady wake effects noted above). This opens the door for dose calculations as a replacement for exposure modeling - a significant improvement for health effects studies. This research demonstrates verification tools needed to assess the uncertainties in the predictions of air velocity and aerosol concentration. An effective way to estimate 95% confidence intervals for aerosol concentration predictions was applied to minimize the computational effort required to distinguish a significant difference between measured and modeled concentrations. This should prove effective when assessing potential control alternatives with CFD simulations and for retrospective exposure assessments.
Particulates; Inhalation-studies; Airborne-particles; Air-contamination; Exposure-levels; Humans; Gravimetric-analysis; Aerosols; Aerosol-particles; Computer-models; Models
Michael R. Flynn, Sc.D., CIH, CB7431 Rosenau Hall, Environmental Sciences and Engineering, University of North Carolina Chapel Hill, NC 27599-7431
Final Grant Report
NTIS Accession No.
Research Tools and Approaches: Exposure Assessment Methods
National Institute for Occupational Safety and Health
University of North Carolina Chapel Hill