Grinding of Chromium Carbide Coatings Using Electroplated Diamond Wheels
Bibliographic record
Abstract
This paper reports an experimental study on grinding of chromium carbide coatings using electroplated diamond wheels. The work was motivated by machining carbide coatings in gas turbine engine applications. The objective is to explore the process conditions and parameters satisfying the ground surface quality requirements. Surface grinding experiments were conducted with water-based grinding fluid on chromium carbide coated on flat surfaces of aluminum blocks for rough grinding at a fixed wheel speed vs = 30 m/s, and finish grinding at vs = 30, 60 m/s. The effects of depth of cut and workspeed on grinding power, forces, and surface roughness were investigated for each of the wheel speeds. Material removal rate Q = 20 mm3/s for rough grinding at a grinding width b = 101.6 mm was achieved. It was found that the maximum material removal rate achievable in rough grinding was restricted by chatters, which was mainly due to the large grinding width. The specific energy ranged from 27 to 59 J/mm3 under the tested conditions. Surface roughness Ra = 3.5–3.8 μm were obtained for rough grinding, while Ra = 0.6–1.5 μm were achieved for finish grinding. Surface roughness was not sensitive to grinding parameters under the tested conditions, but was strongly dependent on the diamond grain sizes. Imposing axial wheel oscillations to the grinding motions reduced surface roughness by about 60% under the tested condition. It was proved that it is feasible to grind the chromium carbide coating with electroplated diamond wheels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".