Experimental characterization of the pore size distribution in fibrous reinforcements of composite materials
Bibliographic record
Abstract
This study uses capillary flow porometry to investigate the porous structure of engineering fabrics used in high-performance polymer composites. This technique consists of applying air pressure to a previously wetted sample to progressively expel the liquid from the pores. A porometry testing device commonly employed to characterize filtration media was used as the principal tool for this investigation. Four types of fibrous fabrics made of glass and carbon fibers with different textile architectures have been experimentally characterized with a through-thickness setup. This allowed obtaining the pore size distribution inside the tested material. In all the cases studied, the porometry technique was able to detect in a reproducible way a bimodal pore size distribution reflecting the presence of both micropores (inside the fiber yarns) and mesopores (between the yarns). Moreover, experimental results indicate that the method can be used to study the influence of the textile pattern on the pore size distribution. Overall, the study shows that capillary flow porometry can give valuable information on the dual scale structure of fibrous reinforcements, which plays a critical role during the impregnation stage of Liquid Composite Molding processes. Because of its simplicity and speed of execution, the proposed approach appears to be a promising way to complement other sophisticated techniques already used for composites such as microscopy and X-ray microtomography.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".