Indoor chemical reactions with human surfaces can meaningfully affect indoor pollutant dynamics and human exposure to reactants and products. Computational Fluid Dynamics models have been used to simulate ozone-human surface reactions in indoor environments. However, the model uncertainties due to near-human grid size and turbulence model are not well understood. The objective of this study is to assess performance of turbulence models and near-human surface grids in predicting local airflow and ozone transport near the human surface under a representative range of indoor airflow conditions. The results show that Large Eddy Simulation (LES) with a fine near-human grid size (e.g., y+ = 1) can yield reasonable results of airflow and mass transfer near the body. The SST k–ω model performs well for the simulation of near-human airspeed, whereas the standard k–ε model can predict lower airspeeds above the human head than the measurements. Both standard k–ε and SST k–ω models may underestimate the turbulent kinetic energy of the thermal plume and ozone deposition velocity at the human surface. The results also suggest that near-human grid sizes of y+ >10 can lead to unreasonable estimates of airflow and mass transfer rate near the human surface.
All Science Journal Classification (ASJC) codes
- Environmental Engineering
- Civil and Structural Engineering
- Geography, Planning and Development
- Building and Construction