Scratch performance of natural rubber and natural rubber composites reinforced with nylon, kevlar, and carbon fabrics
Bibliographic record
Abstract
The scratch performance of natural rubber (NR) and fibre-reinforced NR was investigated using a scratch test with acoustic emission (AE). Both maximum penetration depth and maximum tangential force were characterised by two procedures. Procedure 1 applied the corner of a steel cube at face leading orientation. Procedure 2 applied a steel pyramid indenter with a spherical tip at the edge leading orientation. AE was adopted in Procedure 2 for evaluation of cutting damage mode that varied from ploughing/tearing the matrix to cutting both the matrix and fabric. The scratched regions of all specimens were observed using an optical microscope to estimate the damage level and examine damage mechanisms. The results show that scratch resistance improved as fibre content and fibre stiffness increased. The maximum tangential force depended on the damage modes. Two or more fabric layers could further increase penetration resistance, but the damage level is more serious in most cases.
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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".