Compression molding of Carbon/Polyether ether ketone composites: Squeeze flow behavior of unidirectional and randomly oriented strands
Bibliographic record
Abstract
Compression molding of randomly oriented strands (ROS) of thermoplastic composite is a new process that enabled the formation of complex shapes with high fiber volume fraction. During compression molding of ROS, several deformation mechanisms occurred. This article focused on the macroscopic squeeze flow mechanism. It ruled how the material will flow and fill intricate features of the mold. The squeeze flow behavior under large strain was investigated for Unidirectional (UD) and ROS. An experimental characterization was performed using an instrumented hot press. Also, to predict the associated thickness reduction, existing models using equivalent viscosity and lubrication assumptions were used. The results showed that large deformation of UD and ROS composite materials is mainly governed by two regimes: a Non‐Newtonian fluid behavior at low strain followed by a yielded phase at large strain. Quantitative indicators were defined to analyze these two phases. They showed that current models available in the literature fail to predict accurately the squeeze flow of thermoplastic composites under high strain (>50%). Also, strands size (especially strand length) has a large effect on the squeeze flow mechanism. This article provided basic process window guidelines in terms of minimum pressure and achievable strain for compression molding of ROS parts. POLYM. COMPOS., 38:1828–1837, 2017. © 2015 Society of Plastics Engineers
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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) | 0.000 | 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".