Fine Metallic Particle Emission when Milling Aluminium Alloys and Aluminium Metal Matrix Composites
Bibliographic record
Abstract
Machining activities generate aerosols that can be harmful, degrade the environment or slow down theproduction. The main objective of this study was to evaluate the effects of machining conditions (cutting parameters and workpieces materials) on metallic particle emission during milling to help determining the machining conditions leading to ecological and occupational safe machining practices. The workpieces materials tested were aluminium alloys (6061-T0, T4 and T6 and A319) and aluminiummetal matrix composites (MMC) containing hard particles (SiC) for wear resistance and nickel-coated graphite particles for improved friction and machinability. It is found that the reinforcement within the aluminium MMCs reduces the fine particle emission as compared to unreinforced aluminium alloys. In general, the quantity of the particle emitted depends on the machining parameters settings. Among the aluminium alloys, the particle emission appeared to be dependent on material’s ductility.
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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".