Wind Tunnel Study on Aerodynamic Particle Resuspension from Monolayer and Multilayer Deposits on Linoleum Flooring and Galvanized Sheet Metal
Bibliographic record
Abstract
Resuspension is an important source of indoor particles and the amount of dust loading is an important factor in resuspension emission rates. Field studies have shown that light to heavy dust loads can be found in the indoor environment, on both the surfaces of flooring and ventilation ducts. These diverse particle deposits can be broadly classified as either a monolayer, in which particles are sparsely deposited on a surface, or a multilayer, in which particles are deposited on top of one another and there is particle-to-particle adhesion and interaction. This experimental wind tunnel study explores the role of the type of particle deposit on aerodynamic resuspension from linoleum flooring and galvanized sheet metal. Resuspension fractions are reported for both monolayer and multilayer deposits exposed to a wide range of air velocities. The type of particle deposit is found to strongly influence resuspension. In general, the results show that resuspension from multilayer deposits can occur at significantly lower velocities compared with monolayer deposits. For example, resuspension fractions at an air velocity of 5 m/s for the canopy layer of multilayer deposits were similar to those found for monolayer deposits at 50 m/s. Additionally, for multilayer deposits, resuspension fractions for the canopy layer increased with increasing dust load and negligible resuspension occurred along the surface layer. It was found that the relationship between the particle deposit height and the viscous sublayer thickness of the airflow can help explain the differences in resuspension that were observed between the two types of deposits. The impact of the type of particle deposit on resuspension may have important implications for resuspension in the indoor environment, where a diversity of deposits can be found. Copyright 2013 American Association for Aerosol Research
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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 | 0.000 | 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) | 0.001 | 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".