A CFD Investigation on the Aerosol Drug Delivery in the Mouth–Throat Airway Using a Pressurized Metered-Dose Inhaler Device
Bibliographic record
Abstract
Inhalation therapy involving a pressurized metered-dose inhaler (pMDI) is one of the most commonly used and effective treatment methods for patients with asthma. The purpose of this study was to develop a computational fluid dynamics (CFD) model to characterize aerosol flow issued from a pMDI into a simulated mouth–throat geometry. The effects of air flow rate and cone angle were analyzed in detail. The behaviour of the multiphase flow initiated at the inhaler actuation nozzle and extended through the mouth–throat airway was simulated based on the Eulerian-Lagrangian discrete phase model, with the k-ω model applied for turbulency. We validated our model against published experimental measurements and cover the hydrodynamic aspect of the study. The recirculation we observed at the 90° bend inside the mouth–throat airway resulted in the selective retention of larger diameter particles, and the fluid flow patterns were correlated with drug deposition behaviour. Enhancing air flow rates up to three times reduced the aerodynamic particle diameters to 20%. We also observed that, as cone angle increased, mouth deposition increased; an 8° cone angle was the best angle for the lowest mouth–throat deposition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".