Experimental Measurements of Particle Deposition in Three Proximal Lung Bifurcation Models with an Idealized Mouth-Throat
Bibliographic record
Abstract
In this paper, particle deposition in three idealized proximal lung bifurcation models with an idealized mouth-throat were investigated experimentally. These bifurcation models included (1) a small symmetric bifurcation, (2) an intermediate asymmetric bifurcation, and (3) a large symmetric bifurcation. An idealized mouth-throat geometry (the "Alberta geometry") was used as the inlet to these bifurcation models. Monodisperse aerosol particles of DEHS (di-2-ethylhexyl-sebecate) oil with mass median diameters in the range of 2.5-7.5 microm were employed at steady flow rates of 30-90 L/min. Particle deposition measurements were conducted by gravimetry. The results show that particle deposition in the mouth-throat and trachea accounts for the major portion of total deposition in the entire models used, and particle deposition fraction in the proximal lung bifurcations is lower compared with that deposited in the regions upstream (the mouth-throat and the trachea). Total particle deposition efficiency increases with increasing either inertial parameter or Stokes number. Total particle deposition varies appreciably from model to model. The laryngeal jet is the key factor dominating particle deposition within the trachea. An effect of Reynolds number on particle deposition efficiency in the trachea is observed. In addition, particle deposition in the bifurcation region is influenced little by the upstream flow condition, and therefore the effect of the laryngeal jet on deposition seemingly does not propagate to the bifurcations downstream.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".