Continuous Consolidation of Polypropylene/Glass Fibre Commingled Fabric
Bibliographic record
Abstract
Continuous consolidation of a polypropylene/glass fibre commingled fabric has been investigated using the roll forming process. For this manufacturing process, unconsolidated heated plies are progressively consolidated by passing through a series of rollers. First, compaction trials (performed to determine the most suitable processing parameters) have shown that the repeated application and release of pressure can significantly improve the level of consolidation by allowing trapped air to escape from the molten resin. The influence of the roller gaps, laminate temperature and processing speed has then been determined for the roll forming process. Quality of consolidation was assessed by observing polished micrographs of cross-sections and by determining the void content and flexural properties. Results showed that a roll gap sequence starting at 50% of the unconsolidated laminate thickness is satisfactory. For smaller roller gaps, results have shown that the fabric structure is altered by the squeezing flow of the resin. Results also showed that materials with high inlet temperatures and low process speeds have better levels of consolidation due to lower matrix viscosity and longer contact time with the rollers. Using optimum process parameters, continuous consolidation of 4 plies of 1485 g/m 2 fabric at a rate of 0.5 m/min led to a satisfying quality of composite, with less than 4% void content.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".