Slip flow and shadowing effects in multilayered fibrous filter media
Bibliographic record
Abstract
Air filtration devices, including N95 facemasks and HEPA filters are often made of a small amount of nanofibers deposited on a layer of microfibers using techniques like melt-blowing or electrospinning. This multilayered structure enhances filter performance, mechanical properties, lifespans and cost efficiencies. At the surface of nanofibers, rarefied gas effects such as gas slippage, reduce pressure drop and increases capture efficiency. However, the influence of flow disturbances between fibers in multilayered filter media on filtration performance in the slip regime remains understudied. In this paper, direct numerical simulations of slip flows through three-dimensional digitalized filter media were carried out using a new lattice Boltzmann method. Results show that as the Knudsen number increases, flow redistributes from large pores to small pores, reducing pressure drop and increasing capture efficiency. Flow visualization revealed a shadowing effect exerted by coarse fibers on adjacent fine fibers, which increases the pressure drop caused by microfibers within the multilayered structure compared to their isolated counterparts. While the contribution of this flow shading to filter performance was measurable (5%), the impact of slip flow on the quality factor was far more substantial (80%).Copyright © 2026 American Association for Aerosol Research
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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 | 0.001 |
| 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".