Importance of Physical and Physiological Parameters in Simulated Particle Transport in the Alveolar Zone of the Human Lung
Bibliographic record
Abstract
The trajectory and deposition efficiency of micron-sized (1–5 µm) particles, inhaled into the pulmonary system, are accurately determined with the aid of a newly developed model and modified simulation techniques. This alveolar model, which has a simple but physiologically appropriate geometry, and the utilized fluid structure interaction (FSI) methods permit the precise simulation of tissue wall deformation and particle fluid interactions. The relation between tissue movement and airflow in the alveolated duct is solved by a two-way fluid structure interaction simulation technique, using ANSYS Workbench (Release 16.0, ANSYS INC., Pittsburgh, PA, USA, 2015). The dynamic transport of particles and their deposition are investigated as a function of aerodynamic particle size, tissue visco-elasticity, tidal breathing period, gravity orientation and particle–fluid interactions. It is found that the fluid flows and streamlines differ between the present flexible model and rigid models, and the two-way coupling particle trajectories vary relative to one-way particle coupling. In addition, the results indicate that modelling the two-way coupling particle system is important because the two-way discrete phase method (DPM) approach despite its complexity provides more extensive particle interactions and is more reliable than transport results from the one-way DPM approach. The substantial difference between the results of the two approaches is likely due to particle–fluid interactions, which re-suspend the sediment particles in the airway stream and hence pass from the current generation.
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.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".