Analysis of mesoscopic pore size in 3D-interlock fabrics and validation of a predictive permeability model
Bibliographic record
Abstract
This paper reports an experimental investigation aiming to validate a predictive model of in-plane and transverse permeability for three-dimensional interlock fabrics as a function of fabric architecture. Composite specimens were fabricated and cut to conduct microscopic observations of pore dimensions for five three-dimensional interlock fabrics compressed to a fiber volume content of 58%. The pore cross-section height and width, the number of pores and the pore tortuosity were measured to evaluate an average pore size and distribution along the warp and weft directions for each fabric considered. The changes of these geometrical parameters are analyzed as a function of the fabric structure. A previously developed permeability analytical model is applied using the geometrical characteristics derived from the experimental observations. This allows comparing the experimental permeability to the theoretical predictions of the model and to the values calculated by the same model from the experimentally observed pore dimensions at the considered fiber volume content of 58%. The good agreement obtained in all cases between the measured and calculated values of permeability confirms the validity of the proposed analytical model.
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".