A novel aerosol induction-removal system for mitigating airborne disease transmission in shared indoor environments
Bibliographic record
Abstract
• A novel aerosol removal device based on an induction-removal concept is introduced. • It removes up to 94 % of airborne pathogens while ensuring occupant comfort. • It maintains effectiveness when slightly misaligned, unlike conventional PV systems. • Risk (At 30 min) reduced to 9.5 % vs. 47.6 % (PV), 38 % (PV-PE), and 91 % (baseline). Ensuring high indoor air quality is crucial for mitigating airborne disease transmission, particularly in shared environments. This study introduces a novel aerosol removal device based on an induction-removal (jet-sink) airflow concept, designed to actively direct exhaled pathogens into a localized purification system while maintaining occupant comfort. Unlike conventional personalized ventilation (PV) systems, which rely on high-velocity air jets that may cause discomfort, the proposed device manipulates the airflow near the individual to efficiently capture and remove contaminated aerosols. Fully transient computational fluid dynamics (CFD) simulations based on an Eulerian-Lagrangian approach were conducted over a 30-minute real-time period in a consultation setting, incorporating human effects such as thermal plumes, breathing, and aerosol dispersion. The performance of the novel aerosol removal device was compared against a conventional PV system, a PV-PE, and a baseline HVAC scenario. The novel device removed up to 94 % of exhaled aerosols, reducing the probability of infection to 9.5 %, compared to 47.6 % with PV, 38 % with PV-PE, and over 91 % in the baseline case. Additionally, the induction-removal system maintained its effectiveness even with slight occupant misalignment, whereas PV system exhibited a dramatic increase in infection risk when occupants shifted positions. By creating a controlled airflow pattern, this novel approach enhances aerosol capture and purification, offering a more reliable, adaptive, and comfortable solution for reducing airborne infection risks in enclosed spaces over extended exposure durations. This study highlights the potential of airflow engineering in improving indoor air quality and protecting occupant health.
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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 | 0.000 |
| 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 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".