Helical flow of polymer melts in extruders, part II: Model simulation and validation
Bibliographic record
Abstract
Abstract This paper is a sequel to the development of the mathematical model carried out in Part I of this work. The model describes the flow of a polymer melt inside the helical channel of an injection‐molding machine. In this initiative, we develop an iterative computational algorithm based on shooting Newton–Raphson method to simulate the mathematical model. The simulation results are validated against experimental data obtained from 10 different runs of an industrial injection molding machine processing two different polymers–‐ high‐density polyethylene and polyethylene terephthalate. It is observed that the simulation results are in good agreement with experimental data. This outcome demonstrates the utility of the developed mathematical model and simulation approach. From the standpoint of industrial practice, the direct benefit of this work is the ability to effectively calculate adequate shot size, recovery rate, and various state variables throughout the extent of the machine. © 2010 Wiley Periodicals, Inc. Adv Polym Techn 29:261–279, 2010; View this article online at wileyonlinelibrary.com . DOI 10.1002/adv.20193
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".