Orthogonal Experiment on the Surface Quality of Carbon Fiber Reinforced Plastic Cut by Abrasive Water Jet
Bibliographic record
Abstract
The abrasive water jet (AWJ) is an immensely popular tool to machine hard-to-cut materials.Taking the surface roughness as the metric of cutting quality, this paper designs and implements an orthogonal experiment for the AWJ cutting of carbon fiber reinforced plastic (CFRP), a lightweight composite widely adopted for high-precision applications.Four factors that affect cutting quality, namely, target distance, pump pressure, nozzle traversal speed, and abradant flow rate, were selected, and divided into five levels for the orthogonal design.Since different factors differ in the value on the same level, the orthogonal design was improved by the quasi-level method.The results of the orthogonal experiment show that the nozzle traversal speed exerted the greatest effect on cutting quality, followed in turn by pump pressure, abradant flow rate, and target distance; the optimal cutting quality could be achieved at the target distance of 7mm, the abradant flow rate of 5g/s, the pump pressure of 340MPa, and the nozzle traversal speed of 200mm/min.The research results provide experimental evidence for high-quality AWJ cutting of the CFRP.
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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 | 0.002 |
| 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".