Prediction of Particle Deposition onto Indoor Surfaces by CFD with a Modified Lagrangian Method

Abstract: Accurate prediction of particle deposition indoors is important to estimate exposure risk of building occupants to particulate matter. The prediction requires accurate modeling of airflow, turbulence, and interactions between particles and eddies close to indoor surfaces. This study used a 2 ′ −v f turbulence model with a modified Lagrangian method to predict the particle deposition in enclosed environments. The 2 ′ −v f model can accurately calculate the normal turbulence fluctuation 2′v, which mainly represents the anisotropy of turbulence near walls. Based on the predicted 2′v, we proposed an anisotropic particle-eddy interaction model for the prediction of particle deposition by the Lagrangian method. The model performance was assessed by comparing the computed particle deposition onto differently oriented surfaces with the experimental data in a turbulent channel flow and in a naturally convected cavity available from the literature. The predicted particle deposition velocities agreed reasonably with the experimental data for different sizes of particles ranging from 0.01μm to 50μm in diameter. This study concluded that the Lagrangian method can predict indoor particle deposition with reasonable accuracy provided the near-wall turbulence and its interactions with particles are correctly modeled