Analysis of flow field and turbulence predictions in a lung model applying RANS and implications for particle...

Airflow and aerosol deposition in the human airways are important aspects for applications such as pulmonary drug delivery and human exposure to aerosol pollutants. Numerical simulations are widely used nowadays to shed light in airflow features and particle deposition patterns inside the airways. For that purpose, the Euler/Lagrange approach is adopted for predicting flow field and particle deposition through point-particle tracking. Steady-state RANS (Reynolds-averaged Navier-Stokes) computations of flow evolution in an extended lung model applying different turbulence models were conducted and compared to measurements as well as high resolution LES (large-eddy simulations) for several flow rates. In addition, various inlet boundary conditions were considered and their influence on the predicted flow field was analysed. The results showed that the mean velocity field was simulated reasonably well, however, turbulence intensity was completely under-predicted by two-equation turbulence models. Only a Reynolds-stress model (RSM) was able predicting a turbulence level comparable to the measurements and the high resolution LES. Remarkable reductions in wall deposition were observed when wall effects were accounted for in the drag and lift force expressions. Naturally, turbulence is an essential contribution to particle deposition and it is well known that two-equation turbulence models considerably over-predict deposition due to the spurious drift effect. A full correction of this error is only possible in connection with a Reynolds-stress turbulence model whereby the predicted deposition in dependence of particle diameter yielded better agreement to the LES predictions. Specifically, with the RSM larger deposition is predicted for smaller particles and lower deposition fraction for larger particles compared to LES. The local deposition fraction along the lung model was numerically predicted with the same trend as found from the measurements, however the values in the middle region of the lung model were found to be somewhat larger.