Experimental Study on Grinding of a Nickel-Based Alloy Using Vitrified CBN Wheels
Bibliographic record
Abstract
An experimental study is reported on the grinding of a nickel-based alloy using vitrified CBN wheels. This work was motivated by switching the grinding of fir-tree root forms of jet engine blades from creep-feed grinding with conventional abrasive wheels to vitrified CBN wheels. The objective is to explore process limits and practical grinding parameters for judging the switch in terms of overall costs and productivity. Straight surface grinding experiments were conducted with water-based fluid on rectangular blocks at a fixed wheel speed vs = 45 m/s, various depths of cut a = 0.05 - 1.0 mm, and workspeeds vw = 2 - 40 mm/s. Grinding power, forces, surface roughness, and radial wheel wear were measured. Specific material removal rate of 8 mm3/(mm.s) was reached in rough grinding using a wheel dressed for achieving surface roughness Ra = 0.8 µm in finish grinding. It was found that shallow depths of cut combined with fast workspeeds, or less creep-feed modes, are more suitable for achieving high material removal rates with vitrified CBN grinding. Rough grinding is restricted by high grinding temperatures with newly dressed wheels and by chatters with worn wheels.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".