Some Effects of Start-Up and Shut-Down on Thrust Bearing Assemblies in Hydro-Generators
Bibliographic record
Abstract
The modernization of hydro-generators can involve the analysis of many different manufacturer’s designs of thrust bearings. Recent designs of bearing in common use are very reliable, but when failures do occur, it is often with older machines and within the first few minutes of start-up. This paper is a result of general design studies of various thrust bearing configurations subjected to transient operating conditions. It is shown that transient effects can induce an ‘overshoot’ of thermal deformation which can become unstable, leading to ‘thermal ratchetting.’ Examples are given of pads of various manufacturer’s bearings that have been subjected to this mechanism. Results from operating turbines, basic studies and measurements of the thermal bending of plates indicate that a peak deflection occurs well before thermal equilibrium is attained. The peaking phenomenon may be obscured in some designs or in cases where the run-up is gradual. The beneficial effects of using an oil-lift system during start-up are described. During shut-down it is important that the contact of hot, crowned pads against the runner be prevented. Minimum times for operation of the lift system are suggested, based on the thickness of the pads.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".