Experimental Measurements of Particle Deposition in Three Proximal Lung Bifurcation Models with an Idealized Mouth-Throat
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it