Robotic polishing of turbine runners
Bibliographic record
Abstract
This paper presents the results of a partnership between Alstom and Hydro-Québec for the development of a new factory robotic polishing process. The goal is to improve turbine efficiency by reducing surface roughness to a level that is unattainable with conventional methods. Three entire axial-flow turbines for Hydro-Québec's Sarcelle power station were polished with this new technique at the Alstom manufacturing plant in Sorel-Tracy as a pilot project between July 2010 and March 2011. The surface finish was lowered from Ra = 15 μm to Ra = 0.1 μm, and the waviness left by numerical control machining was grinded away at an overall rate of 5 h/m2. The reduction of surface roughness from the standard IEC recommendation of Ra=3 μm to Ra=0.1 μm resulted in a 0.5% increase in turbine efficiency. This safe, new method proves its great potential for enhanced surface finish quality, productivity and worker safety.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".