Ultrasonic diagnosis of the single screw behavior during extrusion—A case study
Bibliographic record
Abstract
Abstract Ultrasonic diagnostic method of screw behavior during extrusion has been designed, developed, and carried out on a 63.5‐mm single screw extruder, equipped with either a basic conveying screw or a mixing screw. It was found that the screw behavior depends on the screw speed and the die pressure. Whereas initially at low speed, the screw centered by the hydrodynamic forces rotates smoothly in the axial position, at higher screw speeds and high die pressures the screw starts vibrating. Thus, (1) the screw tip vibrated with the amplitude of 10–210 μm as the screw speed varied from 5 to 100 revolutions per minute; (2) the screw vibrations in the vertical and horizontal directions were asymmetrical; (3) the vibration pattern repeated itself at every two revolutions; (4) the vibrations originated in the poorly aligned engagement in the gearbox sleeve when the screw was pushed deeply into it by backpressure; (5) once pushed in the screw oscillated at any screw speed or die pressure. POLYM. ENG. SCI., 2009. Published by the 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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".