Determination of rotary cutting depth on steel pipes with the abrasive water jet technique
Bibliographic record
Abstract
Abrasive water jet (AWJ) cutting is a green machining and processing technology that has found extensive applications. In this study, a well-designed cutting tool with multiple AWJ nozzles has been developed to determine the rotary multi-pass cutting depth on steel pipes that are used in petroleum industries. Experimentally, the multi-pass AWJ cutting depth is found to increase with pump pressure, nozzle diameter, and number of nozzles, but decrease with standoff distance. Also, the multi-pass cutting depth initially increases with rotation speed of the AWJ cutting tool or volumetric concentration of abrasive, and then begins to decline when rotation speed or volumetric concentration reaches a certain value. Mathematically, an empirical model is formulated to determine the rotary cutting depth initiated by multiple cutting passes based on the energy conservation theory. There exists a good agreement between the experimentally measured and theoretically calculated cutting depths with a percentage average absolute deviation of 7.0 per cent.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".