CFD PREDICTION OF PARTICLE DEPOSITION IN LARGE-SCALE HUMAN LUNG MODELS

Computational fluid dynamics (CFD) has evolved as a useful tool for the prediction of airflow and particle transport within the human lung airway. A large number of published studies have demonstrated the use of CFD coupled with Lagrangian particle tracking methods to determine local and regional deposition rates in small subsections of the bronchopulmonary tree. However, simulation of particle transport and deposition in large-scale models encompassing more than a few generations is less common, due primarily to the sheer size and complexity of the human lung airway geometry Fully coupled flowfield solution and particle tracking in the entire lung, for example, is currently an intractable problem and will remain so for the foreseeable future. This paper adopts a previously reported methodology for simulating large-scale regions of the lung airway [1], which was shown to produce results similar to fully resolved geometries using approximate, reduced geometry models. The methodology is here extended to particle transport and deposition simulations. Lagrangian particle-tracking simulations are performed in combination with Eulerian simulations of the air flow in an idealized representation of the human lung airway tree. Results using the reduced models are compared to fully resolved models for an eight-generation region of the conducting zone. Agreement between fully resolved and reduced geometry simulations indicates that the new method can provide an accurate alternative for large-scale CFD simulations while reducing the computational cost of these simulations by an order of magnitude or more.