A simplified damage prediction framework for milling of unidirectional carbon fiber-reinforced plastics
Bibliographic record
Abstract
This article presents a simple framework for predicting the occurrence of delamination during milling of unidirectional carbon-fiber-reinforced plastics (CFRPs), based on a concept of effective critical cutting zone. To validate the concept, sets of milling experiments were conducted on unidirectional CFRP samples of varying fiber orientations and the delamination signature was measured through microscopic images. By observing the damage extent for different fiber orientation angles and different fiber cutting angles for up-milled and down-milled edges, and correlating them with different material removal mechanisms, it has been shown that the damage mainly depends on the portion of the fiber cutting angles that lie within the effective critical milling zone. Both the delamination and the normal cutting forces were found to be strongly dependent on the range of angles in this zone. In addition, it is shown that the cutting force may be used as a good approximation to determine the effect of machining/process parameters on the ensuing delamination damage during milling of CFRPs. For the tested samples, the normal cutting force decreased with an increase in the cutting speed and it increased with an increase in the feed rate of the cutting tool.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".