A model for permeability in fibre-reinforced plastics
Bibliographic record
Abstract
Increased use of continuous fibre-reinforced plastics (CoFRP) is being seen in the automotive industry due to their high strength specific properties. The manufacturing process, however, is still expensive due to the number of critical steps and material costs. Cost reduction is being combated by computational modelling of the infiltration and curing processes to predict void formation and other potential defects. The accuracy of these simulations is highly dependent on capturing the presence of the carbon sheets in the mould due to the large differences in permeability between flows parallel and normal to the fibre tows. This work presents a geometry-based method for locally orienting the fibre and thickness direction for 2D extruded CoFRP components. The capabilities of these methods will be presented by comparing the fibre orientation prediction for two geometries (i.e., hat channel and double dome) using three different draping schemes (i.e., 0°, 45°, and 90°) against the results of a validated draping simulation developed in LS-DYNA.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".