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

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.

PIV measurements of the SimInhale benchmark case.

Particle Image Velocimetry (PIV) measurements with the aim of providing experimental data for the SimInhale benchmark case are presented within this work. We, therefore, present a refractive index matched, transparent model of the benchmark geometry, in which the velocity and turbulent kinetic energy fields are examined at flow rates comparable to 15, 30 and 60 L/min (Re ≈ 1000-4500) in air. Furthermore, these results are compared with Large Eddy Simulations (LES). The results reveal a Reynolds number independence of the qualitative velocity field in the range covered within this work. Good agreement is found between the PIV and LES data, with a slight over-prediction of turbulent kinetic energies by the simulations. The obtained experimental data will be part of a common, publicly accessible ERCOFTAC database along with additional results published recently.

An efficient computational fluid-particle dynamics method to predict deposition in a simplified approximation of the deep lung.

High-fidelity simulations of the complete airway tree are still largely beyond current computational capabilities. Towards large-scale simulations of the human lung, the current study introduces a numerical methodology to predict particle deposition in a simplified approximation of the deep lung during a full breathing cycle. The geometrical model employed consists of an idealised bronchial tree that represents generations 10 to 19 of the conducting zone and a heterogeneous acinar model created using a space-filling algorithm. The computational cost of the coupled simulation is reduced by taking advantage of the flow similarity across the central conducting regions in order to decompose the bronchial tree into representative subunits. Topological information is used to account for the correct gravitational force on the particles in the representative bifurcations, emulating their transport characteristics in the actual bronchial tree. Eventually, airflow and particle transport are simulated in a single representative bifurcation and a single acinar model, resulting in great savings in computational cost. An Eulerian-Lagrangian approach has been used for solving the flow and particle equations during sinusoidal breathing in the decomposed domain. The resulting deposition estimates agree rather well with the known deposition trends reported in the literature, while offering additional insights. For 1-5µm particles, deposition during exhalation is comparable to deposition upon inhalation, suggesting the use of breath-hold maneuvers to further increase sedimentation of these particles. Airway orientation relative to gravity was found to have a significant impact on deposition rates, especially for particles above 2µm and to be higher in the more distal generations, due to the wider range of angles relative to the direction of gravity. In the acinus, particles in the 2-5µm range have a quite high average deposition efficiency that reaches approximately 75% and shows considerable variation (12.4%) due to airway orientation. Finally, a simplified semi-analytical approach is introduced that can lead to even further reduction in computational costs, while incurring only a small loss in accuracy.

Regional aerosol deposition in the human airways: The SimInhale benchmark case and a critical assessment of in silico methods.

Regional deposition effects are important in the pulmonary delivery of drugs intended for the topical treatment of respiratory ailments. They also play a critical role in the systemic delivery of drugs with limited lung bioavailability. In recent years, significant improvements in the quality of pulmonary imaging have taken place, however the resolution of current imaging modalities remains inadequate for quantifying regional deposition. Computational Fluid-Particle Dynamics (CFPD) can fill this gap by providing detailed information about regional deposition in the extrathoracic and conducting airways. It is therefore not surprising that the last 15years have seen an exponential growth in the application of CFPD methods in this area. Survey of the recent literature however, reveals a wide variability in the range of modelling approaches used and in the assumptions made about important physical processes taking place during aerosol inhalation. The purpose of this work is to provide a concise critical review of the computational approaches used to date, and to present a benchmark case for validation of future studies in the upper airways. In the spirit of providing the wider community with a reference for quality assurance of CFPD studies, in vitro deposition measurements have been conducted in a human-based model of the upper airways, and several groups within MP1404 SimInhale have computed the same case using a variety of simulation and discretization approaches. Here, we report the results of this collaborative effort and provide a critical discussion of the performance of the various simulation methods. The benchmark case, in vitro deposition data and in silico results will be published online and made available to the wider community. Particle image velocimetry measurements of the flow, as well as additional numerical results from the community, will be appended to the online database as they become available in the future.

Particle deposition in a realistic geometry of the human conducting airways: Effects of inlet velocity profile, inhalation flowrate and electrostatic charge.

Understanding the multitude of factors that control pulmonary deposition is important in assessing the therapeutic or toxic effects of inhaled particles. The use of increasingly sophisticated in silico models has improved our overall understanding, but model realism remains elusive. In this work, we use Large Eddy Simulations (LES) to investigate the deposition of inhaled aerosol particles with diameters of dp=0.1,0.5,1,2.5,5 and 10µm (particle density of 1200kg/m(3)). We use a reconstructed geometry of the human airways obtained via computed tomography and assess the effects of inlet flow conditions, particle size, electrostatic charge, and flowrate. While most computer simulations assume a uniform velocity at the mouth inlet, we found that using a more realistic inlet profile based on Laser Doppler Anemometry measurements resulted in enhanced deposition, mostly on the tongue. Nevertheless, flow field differences due to the inlet conditions are largely smoothed out just a short distance downstream of the mouth inlet as a result of the complex geometry. Increasing the inhalation flowrate from sedentary to activity conditions left the mean flowfield structures largely unaffected. Nevertheless, at the higher flowrates turbulent intensities persisted further downstream in the main bronchi. For dp>2.5µm, the overall Deposition Fractions (DF) increased with flowrate due to greater inertial impaction in the oropharynx. Below dp=1.0µm, the DF was largely independent of particle size; it also increased with flowrate, but remained significantly lower. Electrostatic charge increased the overall DF of smaller particles by as much as sevenfold, with most of the increase located in the mouth-throat. Moreover, significant enhancement in deposition was found in the left and right lung sub-regions of our reconstructed geometry. Although there was a relatively small impact of inhalation flowrate on the deposition of charged particles for sizes dp<2.5µm, impaction prevailed over electrostatic deposition for larger particles as the flowrate was increased. Overall, we report a significant interplay between particle size, electrostatic charge, and flowrate. Our results suggest that in silico models should be customized for specific applications, ensuring all relevant physical effects are accounted for in a self-consistent fashion.