Airflow in the human upper airways

Application Challenge AC7-02 © copyright ERCOFTAC 2020

Best Practice Advice

Key Fluid Physics

In the present AC, experiments and simulations were conducted at a flowrate of 60 L/min through an upper airway geometry. At this flow conditions, the Reynolds number for air in the trachea is 4920, which is well within the turbulent regime. Geometric effects, such as the bent in the oropharyngeal region and the constriction at the laryngeal glottis (just upstream of the trachea, see fig. 25) enhance turbulence levels as the air moves from the inlet to the region of the trachea. Turbulent kinetic energy levels reach a peak in the shear layer formed between the high speed laryngeal jet and the surrounding (low speed) air (see fig. 25). The characteristics of the laryngeal jet formation bear a resemblance to the flow through a constricted pipe, which can be classified as a free shear flow where the wall serves to confine the spreading of the jet rather than producing turbulence (Tawhai & Lin, 2011). High turbulence levels persist in the region of the first bifurcation (stations H1-H2 & J1-J2 in fig. 12(b)).

Application Uncertainties

The differences between measurements and simulations can result from several uncertainties involved in the tests. A first source of uncertainty are the inlet conditions, which are not perfectly matched between the measurements and the computations. In the experiments, the lung model was placed in an open liquid tank with a piston diaphragm pump attached to a linear actuator to achieve a quasi-stationary inspiratory flow. The stroke of the piston followed a cyclic triangular function with an adjustable falling constant slope and thus constant velocity to match different flow rates during inspiration. The measured mean velocity at the inlet of the model, shown in Fig. 7, is asymmetric, probably due to the action of the piston diaphragm pump. In the computations, instead of reproducing the measured inlet conditions, either uniform or turbulent inlet velocity profiles were prescribed. Due to a leakage flow between the upper and lower part of the model in the experiments, the achieved flowrate within the main bifurcation and bronchi region was about 10% lower than in the upper part of the model. As a result, a maximum flowrate of $Q_{w/g}$ = 28.56 L/min could be achieved in the measurements. This value is slightly lower than $Q_{w/g}$ = 31.75 L/min, which is the target value for an equivalent air flowrate of 60L/min through the model. Although the flow is well within the turbulent regime, the theoretical maximum Reynolds number decreases from 4921 to 4286.

Computational Domain and Boundary Conditions

The geometry of the extrathoracic airways must be included because turbulence is generated in this region that propagates in the first airway generations. Concerning the boundary conditions, the inlet velocity profile is important and thus realistic inlet conditions should be used. At the outlets, it is important to apply correct pressures such that the ventilation of the airway tree is physiologically realistic (Yin et al., 2010). In the present AC, in order to simplify the experimental setup and be able to perform the flow measurements, uniform pressures were prescribed at all outlets.

Concerning the inlet conditions for the turbulent variables in RANS calculations, the application of a turbulence intensity of 5% for the k-ω SST model at the extended inlet (10xDinlet) yielded higher turbulent kinetic energy values close to the inlet of the model compared to the mapped inlet condition (Inlet 1). The k-ε models were found to provide overall higher turbulence levels than the k-ω SST model, especially at the near-wall regions.

Discretisation and Grid Resolution

Turbulence Models

Recommendations for Future Work

Acknowledgements

References

Armenio, V., Piomelli, U. & Fiorotto, V. 1999

Effect of the subgrid scales on particle motion. Physics of Fluids 11 (10), 3030 – 3042.

etc

Contributed by: P. Koullapis^a, J. Muela^b, O. Lehmkuhl^c, F. Lizal^d, J. Jedelsky^d, M. Jicha^d, T. Janke^e, K. Bauer^e, M. Sommerfeld^f, S. C. Kassinos^a —
^aDepartment of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, Cyprus
^bHeat and Mass Transfer Technological Centre, Universitat Politècnica de Catalunya, Terrassa, Spain
^cBarcelona Supercomputing center, Barcelona, Spain
^dFaculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic
^eInstitute of Mechanics and Fluid Dynamics, TU Bergakademie Freiberg, Freiberg, Germany
^fInstitute Process Engineering, Otto von Guericke University, Halle (Saale), Germany