Multi-die thermoplastic pultrusion of carbon reinforced PolyEtherKetoneKetone bars at 1 m/min using preimpregnated tape
Bibliographic record
Abstract
This study aimed at achieving multi-die thermoplastic pultrusion at 1 m/min for advanced air mobility applications. PolyEtherKetoneKetone impregnated carbon fibre (C/PEKK) prepreg tape was used. The measured void content of the as-received tapes was 15.6 vol%. A finite element simulation was developed to determine the temperature profile of the pultrudate for different die temperature set points. Three pultrusion speeds were tested: 50, 500, and 1000 mm/min. The die temperatures were adjusted using the simulation to ensure reaching the processing temperature of 370 °C in the compaction dies regardless of the pultrusion speed. The measured void content of the pultrudates increased from 1.8 vol% to 2.8 vol% for the lowest to highest pultrusion speed. The final pultruded parts do not exhibit deconsolidation, as indicated by the consistent thickness values obtained across all experiments. It was observed that improving the surface finish required relocating the cooling die further downstream from the last heated die. The surface finish (Ra) at 500 mm/min was 3.11 μm, whereas the values obtained at 50 and 1000 mm/min were comparable. A flexural test in accordance with ASTM D790 did not show any significant variation with increasing pulling speed. The flexural strength ranged from 998 to 1041 MPa, while the flexural modulus remained between 106 and 109 GPa.
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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 | 0.000 |
| 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".