On the design of test molds based on unidirectional saturated flows to measure transverse permeability in liquid composite molding
Bibliographic record
Abstract
Abstract Impregnating fibrous preforms through thickness has become a main feature of some liquid composite molding process variants. Thus, the evaluation of transverse permeability is critical to optimize the fabrication and reduce manufacturing defects. Some problems connected with the design of testing devices need to be addressed to perform a reliable characterization. In this study, the efficiency of a typical one‐dimensional testing device to measure transverse permeability is evaluated numerically and experimentally. The paper introduces a novel methodology to identify the optimal mold configuration and evaluate the flow pattern inside the mold cavity. A dimensionless number called the “fill coefficient” is also proposed to evaluate quantitatively the effect of the mold structure on the transverse flow pattern. The measured transverse permeability is shown to increase with lower fill coefficients for saturated and unsaturated flows. The intrinsic transverse permeability is obtained when the fill coefficient is equal to one. The proposed methodology is verified by experiments performed in an existing tool. This confirms that the measured transverse permeability can be significantly affected by the above mentioned factors.
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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 | 0.001 | 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 | 0.000 |
| 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 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".