Effect of the fibre diameter polydispersity on the permeability of nonwoven filter media
Bibliographic record
Abstract
Abstract This paper studies the permeability values of air filter media obtained by 3‐D simulations using the GeoDict® code. 3‐D fibrous structures with different specific characteristics that can be encountered in air filtration (0.03 ≤ solid volume fraction [ α ] ≤ 0.25, monodisperse fibres [1 μm ≤ df ≤8 μm], or polydisperse fibres) were generated. For monodisperse fibres, the permeability values obtained were compared with various correlations identified in the literature. After confirming that Davies' or Jackson and James' relations allowed a good estimate of the permeability, it is shown that the modified Happel's correlation provides a better prediction. In the case of normal (standard deviation: σ ≤ 1.5) or lognormal fibre size distribution (geometric standard deviation: σ G ≤ 2), this modified Happel's correlation, in which the fibre diameter is replaced by an equivalent fibre diameter, leads to a relative deviation of less than ±8% and ±4% for lognormal and normal fibre distributions, respectively. The comparison with experimental permeability values obtained on real media provides quite encouraging results.
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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 | 0.003 |
| 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".