Effects of Tool Geometry and Fluid on the Surface Morphology and Integrity in Scratching TiMMCs
Bibliographic record
Abstract
An experimental study is reported on the surface morphology and integrity in scratching of TiMMCs. The objective is to simulate the cutting of TiMMCs by individual grains in grinding operations. The results can also be utilised to understand the resistance to abrasion and wear of the materials. Experiments were performed at a fixed scratching speed vs = 20 m/s, and given depths of scratching ranging from 0.004 to 0.024 mm. Scratching tools with round and conical tips were selected for the tests with and without grinding fluid. Microscopic observations of the tool tips and the scratches were conducted. It was revealed that ploughing of the matrix and the re-deposition of the matrix on the scratched surface led to the mixing of the matrix with broken TiC particles. The use of grinding fluid influenced the TiC removal mechanisms in terms of 'comet tail' phenomenon and different severities of the particle breakage. The depth of scratch had a greater effect on the cupules formation. Comparison of the bottom of the scratches and the ground surfaces showed that the wheel wear had significant effects on the ground surface morphology and integrity. No evidence of whole particle dislodgements was observed.
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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".