In this study, the effects of variations of two morphological parameters on the breathing process were explored. Bifurcation angle (BA) and carina rounding radius (CRR) were evaluated using independent geometric models and specific boundary conditions. Both morphological parameters were analysed using computational models implemented in OpenFOAM following the assumptions of incompressible and isothermal air as the working fluid. The details of each of these models and their respective methodological aspects are presented below.
2.1. Bifurcation angle (BA). Morphological definition
The analysis of the bifurcation angle was carried out using a Weibel 3-D model of airways, which included the first three generations of human morphology (see [
51]). Those generations represent the trachea, main bronchus and secondary bronchus. To simplify the analysis, the notation for airways provided by Christou et al [
9] was adopted. The values selected for the geometric parameters of the model are shown in
Table 1 and illustrated in
Figure 1.
To avoid problems related to flow development in the regions close to the outlets, the length of each of the last generation branches was extended to ensure a minimum length of five times the related outlet diameter. The bifurcation points were considered as straight joints, i.e. the carina rounding radius for these geometries was set equal to zero.
To evaluate the effect of the bifurcation angle (BA), two values of
and
were selected from experimental measurements of physiologically relevant subcarinal angles reported by Haskin & Goodman [
19]. As shown in
Table 2, these angles correspond to the average measured for people between 50 and 60 years old, and the average for people 61 years old or older, respectively. In order to extend the analysis, a model with an additional value for BA of
was also explored, according to the mean angle with minimum resistance discussed by Horsfield & Cumming [
22]. Each selected angle value was prescribed as the bifurcation angle for all model generations in each of the numerical experiments.
2.3. Governing equations and computational model.
The ventilation process within human beings takes place at relatively low Reynolds numbers regimes, and at very low Mach numbers, even for agitated breathing situations ([
31,
32]). Therefore, for both BA and CRR experiments, the fluid flow through the synthetic human airways was assumed to be laminar and incompressible. Additionally, isothermal air was assumed as the working fluid, in line with the predefined flow conditions. The governing equations selected for this fluid flow regime were the conservation of mass equation and the Navier-Stokes (conservation of momentum) equations, which, for incompressible and isothermal flow, can be formulated as,
where
and
are the
i-th velocity component and the velocity vector field, respectively Equally, in Equation (
3),
is the fluid pressure and
its kinematic viscosity with
standing for the density of the fluid. For the purposes of this work, the Reynolds number has been defined as
Where . Air properties were defined at ambient temperature of 15o, with and .
The two breathing processes, i.e., inhalation and exhalation, were decoupled and studied as independent processes. The main objective of this work was to characterize and establish general patterns of airflow within a portion of the human airways. By simulating the processes independently we were able to guarantee the stabilization of the flow and thus the stabilization of the patterns reported in the present manuscript, mainly aiming at getting a general description and overview of the flow. It is also noteworthy that a large body of research in this field has been performed employing this consideration of independent processes, including experimental and numerical studies (see [
10,
15,
57,
58,
60,
61,
62]). For instance, Zhao & Lieber [
61,
62] characterized the flow through the airways experimentally for the inhalation and exhalation states independently; Yang et al [
57] characterized airway inflow patterns as a single process, and Zhang et al [
60] described the effect of tracheal curvature on respiratory inhalation as an independent stage. A large number of numerical studies on particle dispersion, such as those developed by Yu et al [
58] and Comer et al [
10], consider a single breathing state to characterize the phenomena and obtain patterns of behavior. Accordingly, considering the large portion of published work on the modeling of the human respiratory process based on the one-way respiration flow assumption, instead of a more realistic oscillatory flow, and the success of this approach in modeling a number of different airflow conditions, the same methodology was used to explore the cases considered in the present work. To ensure proper flow development in the inhalation process simulations, a parabolic velocity profile was adopted. This profile was prescribed as symmetrical around the inlet axis, i.e. the trachea, and is given by:
Where
is the inlet velocity,
is the maximun velocity,
r a radial position and
R the inlet radius. Human breathing rates range from
to
[
31,
32], which corresponds to a range of Reynolds numbers (
Re) between 200 and 2800. This range was observed by Adler & Brücker [
1] in an experimental investigation using a pulsatile flow, where a maximum value of
was reached. Different Reynolds number values were explored in the present study, however, for brevity only the results for two values, representative of the extremes of the breathing process and corresponding to
and
, are presented. At the Outlets, a uniform pressure boundary condition was prescribed for all outlets. As indicated by Bauer & Brücker [
4], this consideration allows the flow to adjust to different pressure gradients across different airway generations. Therefore, the velocity condition at the outlets is given by
In the surface of the wall a Dirichlet no-slip boundary condition was applied to the velocity field at all airway walls,
The exhalation study was performed only for BA analysis. While in inhalation stage the inlet was the trachea and the outlets were the bronchi, for exhalation stage the bronchi were the inlets and the trachea was the outlet. A parabolic velocity profiles (see Equation (
5)) were prescribed at each of the inlets. These profiles were defined symmetric with respect to the axial lines of each last generation branch, and their maximum value is equal to the maximum velocity obtained at the outlets in the respective inhalation cases. At the Outlet a uniform pressure condition was set up. The velocity condition is described by Equation (
6). Newly a Dirichlet no-slip boundary condition was applied to the velocity field at all airway walls, as described in Equation (
7).
All boundaries were considered rigid. Investigations such as those carried out by Wall & Rabczuk [
47], Wang et al [
48] and Koombua et al [
27] show that under normal breathing conditions, i.e., low Reynolds numbers and healthy airway geometries, the wall deformation is relatively small, and therefore the effect on airflow is not highly relevant. The study performed by Wall & Rabczuk [
47] shows that the difference between the numerical results obtained with fluid-structure interaction simulations versus CFD results was minimal, and in fact the flow fields were very similar for small Tidal breathing volumes, i.e., for considerations close to normal breathing in physiological conditions.
The governing equations were solved numerically using the open source computational fluid dynamics (CFD) suite OpenFOAM, which offers different schemes and numerical methods to solve different fluid flow phenomena. For the selected flow conditions and mathematical model, a finite volume method (FVM) approach was adopted. OpenFOAM (OF) offers a number of the so-called solvers and for the purposes of the present study the
pisoFoam solver was selected, which is suitable for unsteady and incompressible laminar flows. The simulation setup was configured to maintain a Courant number less than 1, with a time step size equal to
. This consideration ensures that the solution has a stable behavior during the simulation time [
13,
49,
53]. Temporal integration was performed by using a
backward scheme and the spatial discretisation was solved using second-order interpolation schemes for the gradient and divergence terms. The
Geometric Agglomerated Algebraic Multigrid Solver (GAMG) was used to solve the Poisson-pressure equations, whereas the velocity field was obtained using the
smoothSolver scheme available in OF. Pressure-velocity coupling was accomplished by using the PISO algorithm. All the numerical simulations of this study were performed in parallel using a Simple Domain Decomposition. The unstructured mesh generator
snappyHexMesh was employed to generate the computational grid for the different geometries covered in this work. An example of one of the finite volumen mesh for BA’s study is illustrated in
Figure 3a. As can be seen in the cross section of the branch, a finer refinement was implemented near the walls. The average number of tetrahedral cells in the different computational models was
. The finite volumen meshes for CRR’s study are shown in
Figure 3b. In order to obtain a zone of finer cells near the carina, particular sub-regions of refinement were defined. For this cases, the average number of tetrahedral cells was
.
To ensure that the resolution of the mesh was capable of capturing the associated flow phenomena, the computational mesh was configured so that the wall-normal distance of the cell centres neighbouring the airway walls was less than the resolution threshold of the viscous sublayer. This value was expressed in non-dimensional form in terms of wall-units, generically referred to as
. This parameter can be evaluated as,
where
is the fluid’s kinematic viscosity,
is the friction velocity defined as
the variable
y is the wall-normal distance from the cell centre to the bounding wall, and
the local wall shear stress. As the larger velocities appear in the trachea,
was computed in that branch, as shown in
Figure 4. The parameter
was calculated at the maximun velocity of our test set, i.e.
. The average value obtained by applying Equations (
8) and (
9) was
. Considering that this value is less than 1, it is possible to conclude that the meshes constructed and employed in the present work were fine enough to accurately capture the flow phenomenon for the different regimes considered here.