Airflow characterization within the pleat channel of <scp>HEPA</scp> filters with mini pleats
Bibliographic record
Abstract
Abstract High efficiency particulate air (HEPA) pleated filters are used to ensure the containment of airborne contamination within nuclear facilities. These filters are often the last barrier before a potential release of radioactive substances into the environment. The present article focuses on the characterization of air velocity fields within mini‐pleats HEPA filters at the elementary pleat scale. Numerical simulations of the velocity fields in a pleat using two different codes, ANSYS CFX and GeoDict, based on two different simulation strategies have been performed. Computed velocity profiles within the pleat have then been compared to measurements performed using an experimental setup based on a μ‐PIV measurement technique. Results show that both codes are able to reproduce the measured profiles with a satisfying accuracy. However, GeoDict requires a much finer meshing than ANSYS CFX because the voxel size is constant for the whole domain. Simulation and experimental results confirm a self‐similarity profile along the pleat assessed as a hypothesis by other authors working on this topic.
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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".