Experimental investigation of the cutting temperature and surface quality during milling of unidirectional carbon fiber reinforced plastic
Bibliographic record
Abstract
The surface machining of carbon fiber reinforced plastics materials is a challenging process, given the heterogeneity and anisotropic nature of composites, which, combined with the abrasiveness of the fibers, can produce some surface damage and extensive tool wear. The cutting temperature is one of the most important factors associated with the tool wear rate and machinability of these materials, which are also affected by the mechanical and thermal properties of the workpiece material and the cutting conditions. In this work, the cutting temperature, cutting forces, and composite surface roughness were measured under different cutting conditions for the end milling of unidirectional carbon fiber reinforced plastics. Cutting speeds ranging from 200 to 350 m/min; a feed rate of 0.063 mm/rev; fiber orientations of 0, 45, 90, and 135°; and a 0.5 mm depth of cut were considered. The results show that the cutting speed and fiber orientation have a significant influence on the cutting temperature and cutting forces. The maximum and minimum cutting forces and temperatures were achieved for fiber orientations of 90 and 0°, respectively.
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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 | 0.001 |
| 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".