Parametric simulation study of a wavy slot channel thermoplastic melt impregnator for carbon fibre-reinforced prepreg tape production
Bibliographic record
Abstract
Compared to pin-driven thermoplastic melt impregnation for fibre-reinforced tape manufacture, a cross-head slot channel die with crests can be used to reduce polymer degradation and tape porosity. In a slot channel, polymer melt is driven from the gate to the die exit by a static pressure gradient and drag at the fibre-tow interface. To inform the wavy slot die design, this paper augments pin-assisted melt impregnation models to introduce a process model combining static pressure in the melt, wedge-driven pressure, and crest pressure. Between crests, pressure develops in the wavy channel, analogous to theoretical pin-driven models. The static pressure gradient in the slot with a moving tow was examined by computational fluid dynamics. Parametrically studying the pulling speed, number of crests, crest length, melt viscosity, and melt inlet velocity shows that the interactive trends significantly change depending on the static pressure. When static pressure dominates, parameters that raise driving pressure, such as melt viscosity and melt inlet velocity, substantially improve the impregnation. Additionally, extended residence time by increasing the crest length and the number of crests improves the degree of impregnation. Meanwhile, wedge-driven impregnation is principally enhanced by the number of crests. The model is calibrated to fit experimental results using a single theoretical parameter when applying (i) Kozeny-Carman’s general permeability or (ii) Bruschke and Advani’s theoretical transverse permeability. Since static pressure in the wavy slot channel strongly benefits impregnation, the introduced model can inform the die design and operating conditions needed to elevate static pressure for minimum porosity. • Combined assessment of simulated static and theoretical contracting wedge pressure. • Impregnation at leading crests is dominantly driven by static pressure. • Impregnation at trailing crests is driven by pressure developed in the contracting wedge. • Fibre tow separation and spreading at crests increases transverse permeability. • Model informs die design and process parameter selection for effective impregnation.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".