Thirty-Seven Years of Fleet Operating and Maintenance Experience Using Phosphate Ester Fluids for Bearing Lubrication in Gas-Turbine/Turbo-Compressor Applications
Bibliographic record
Abstract
TransCanada operates one of the most sophisticated pipeline systems in the world with a network of approximately 57 000 km (35 500 miles) of wholly owned and 11 500 km (7000 miles) of partially owned natural gas pipeline, which connects virtually every major natural gas supply basin/market and transports 20 % of the natural gas consumed in North America. This pipeline system operates a fleet of several hundred gas-turbine/turbo-compressor packages, which, in a majority of cases, use phosphate-ester-based lubricants for bearing lubrication. Based on the number of installations, TransCanada is one of the largest users of phosphate-ester lubricants in the world. Phosphate esters have been used in this application because of their excellent fire-resistant and lubrication properties. Mineral-oil-based lubricants, alternatively, used in this application contain rust and oxidation inhibitors. These additives deplete over time, which is one factor that limits their useful operating life. Phosphate-ester lubricants do not generally contain additives and when used in conjunction with effective condition monitoring and maintenance, can have an operating life >20 years. This extraordinarily long operating life offers significant environmental benefits. Since 1958, TransCanada has accumulated over 30 × 106 h operating experience with phosphate-ester lubricants and has developed an extensive fluid management and conditioning program to ensure safe, reliable, and cost effective operation. A historical review of the condition-based fluid monitoring and maintenance programs will be presented with a focus on the evolution of these programs into their current modern and sophisticated forms. The associated reduced environmental footprint and cost savings will be detailed.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".