Propagation of Mouth-Generated Aerosols in a Modularly Constructed Hospital Room
Bibliographic record
Abstract
Modular construction methods have been widely used in the civil engineering industry due to ease of assembly, the convenience of design, and allowing for flexibility in placement while making the construction more sustainable. With the increasing number of COVID-19 cases, the capacity of the hospital is decreasing as more intensive care units (ICU) are allocated to COVID-19 cases. This limited capacity can be addressed by using modular construction to provide field hospitals. This paper adopts transient Lagrangian computational fluid dynamics simulations to investigate the importance of having an appropriate ventilation system in place to ensure sustainable infection control against airborne viruses and pathogens within a modular room. The performance of having a ventilation system using 10, 20, and 40 air changes per hour (ACH) was examined. In addition, different room configurations were also compared to provide useful guidelines for air conditioning units placement. It was determined that as the ACH rate increases while maintaining a direct flow field between the inlet and outlet, the rate of aerosol removal increases. Furthermore, the flowfield in which can be controlled by the placement of the inlet and outlet can impact the removal of aerosols, as it dictates how far the droplets travel before being removed from the enclosure.
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 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".