INVESTIGATION OF EFFECT ON LATERAL DISPLACEMENT AND FORCES OF CUTTING MODE IN SAWABILITY OF METAL PROFILE USING CUTTING DISC
Bibliographic record
Abstract
In this study, the cutting performance of cutting discs used to cut metal materials depending on the cutting modes is determined with an experimental study. Tests are performed using a computer-controlled cutting machine. For the tests, peripheral speeds of 40, 60 and 80 m/sec and feed speeds of 0.3, 0.4, 0.5, 0.6, and 0.7 m/min. are preferred as cutting parameters. Up cutting and down cutting are taken into consideration as cutting modes. A three-point dynamometer is used to determine the forces applied on the disc during cutting. A KEYENCE laser displacement measuring device is used to measure lateral displacements of the cutting disc. According to the test results, feed speed is observed as a significant parameter in determining the cutting forces and lateral displacements. Up and down cutting modes used in the study has a significant effect on determining the forces applied on the cutting disc and lateral displacements of the disc. In particular, lateral displacements obtained in down cutting mode are observed to be greater than the displacements obtained in up cutting mode.
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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 | 0.003 |
| 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".