Effects of Laval Nozzle on Precision Micro Cutting of Thin Metal Plate by Pulsed YAG Laser
Bibliographic record
Abstract
The stagnation pressure, which is the sum of static and dynamic pressures, has a great influence on machining performance in laser cutting. Therefore, increasing the velocity of assist gas is effective in reducing the height of dross. In this paper, Laval nozzle was newly designed, because it can increase the velocity of assist gas flow spouted from nozzle tip. Effects of Laval nozzle on assist gas flow and the machining results in precision cutting of thin metal plate by a pulsed YAG laser were experimentally investigated. Assist gas flow from Laval nozzle does not have Mach Shock Disk and goes more straight than a traditional convergent nozzle. Therefore, the pressure on a workpiece increases, since assist gas flow from Laval nozzle can utilize energy more efficiently. However, caution is necessary in setting the cylinder gas pressure, since Laval nozzle has many unstable regions, where the pressure on the workpiece changes periodically. Using Laval nozzle makes it possible to reduce the height of dross even under low cylinder gas pressure condition compared to convergent nozzle. Thus the consumption of flow quantity of assist gas can be reduced, when the same height of dross is desired. Moreover, it was pointed out that the convexed inner wall of nozzle leads to the reduction of dross generation and unstable region.
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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) | 0.001 | 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".