Injection molding of short coir fiber polypropylene biocomposites: Prediction of the mold filling phase
Bibliographic record
Abstract
The mold‐filling phase in injection molding is the most important one because the material flow behavior controls the final part structure. In this work, the effect of melt rheology on the flow front progression of coir fiber (2.5, 5, 10, and 15 wt%) filled polypropylene is investigated. The flow behavior is predicted using the incompressible Navier–Stokes equations to determine the flow front shape and position and the model proposed is in good agreement with the experimental results for the range of conditions studied. Finally, to provide a better understanding of the effect of different processing conditions (pressure, melt, and mold temperature) on the flow front evolution, several simulations were performed using Autodesk Moldflow Insight. POLYM. COMPOS., 40:4042–4055, 2019. © 2019 Society of Plastics Engineers
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".