Investigation of flow pattern in upper human airway including oral and nasal inhalation by PIV and CFD

Abstract

Breathing is one of the most essential processes in the human body. The basic functions of breathing are to exchange gases (supplying oxygen from ambient air and removing carbon dioxide from the blood) and also to exchange heat and moisture through mucous surfaces of the airway. During an average lifetime, human beings experience significant exposure to indoor air and countless of contaminants/particles via inhalation. In this study, experimental and numerical results of flow fields in a realistic respiratory model were obtained. Flow patterns in a realistic replica model of the human respiratory tract were investigated with particle image velocimetry (PIV) under three constant breathing conditions; 7.5, 15 and 30 L/min. Computational fluid dynamics (CFD) analyses were conducted on turbulent models with boundary conditions corresponding to the experimental models. We used four RANS turbulence models to predict airflow in a realistic human airway model: two low Reynolds (Re) number-type k–ε turbulence models, RNG k–ε model, and the SST k–ω model. The CFD results were compared with PIV data and showed relatively good agreement in trachea region in all cases.